MaterialConsumptionandCarbonEmissionsAssociatedwiththe...
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Research Article Material Consumption and Carbon Emissions Associated with the Infrastructure Construction of 34 Cities in Northeast China Heming Wang, 1,2 Yao Wang , 1 Cong Fan, 1 Xinzhe Wang, 1 Yao Wei, 1 Zhihe Zhang, 1 Jiashi Wang, 1 Fengmei Ma, 2,3 and Qiang Yue 1 1 State Environmental Protection Key Laboratory of Eco-Industry, Northeastern University, Shenyang, China 2 Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, Australia 3 College of Economics and Management, Shenyang Agricultural University, Shenyang, China Correspondence should be addressed to Yao Wang; [email protected] Received 18 June 2020; Revised 27 July 2020; Accepted 5 August 2020; Published 7 October 2020 Guest Editor: Jianhong (Cecilia) Xia Copyright©2020HemingWangetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Over the past three decades, China has experienced rapid economic growth along with a rapid increase in urbanization and living standards, leading to a boom in infrastructure demand. A large part of China’s newly constructed infrastructure is through urban construction; thus, cities have become a major source of material consumption and carbon emissions. Understanding the relationship between material consumption, carbon emissions, and the economic growth of cities is key to ensuring that the construction of infrastructure satisfies the needs for both economic development and dematerialization. In this study, we first accounted for material consumption and the carbon emissions of infrastructure construction of 34 cities in Northeast China and characterized spatial and temporal changes from 2010–2017. e material use and carbon emissions of infrastructure construction declined by 34.6% and 30.2% during this period. Specifically, material consumption decreased from 305.2 million tonnes to 199.6 million tonnes, and carbon emissions decreased from 77.7 million tonnes to 54.3 million tonnes. Furthermore, we used a decoupling indicator to evaluate the decoupling of material consumption or carbon emissions from GDP in these cities. We found that most cities have achieved the absolute decoupling of material consumption and carbon emissions from GDP over the study period. Finally, we proposed several policy recommendations for promoting the sustainable development of the infrastructure of cities. To ensure that cities realize low-carbon urbanization, policymakers need to promote modular buildings and low-emission construction materials. is paper also serves as a practical reference for the improvement of relevant materials and carbon emissions management strategies for other developing regions. 1. Introduction Infrastructure has a transformative impact on social de- velopment and living standards and provides a variety of services, including construction, energy, water, and waste management [1]. At the same time, it also provides a means of storage for the extraction of natural resources from the environment. e scale of Chinese infrastructure con- struction has shown unprecedented growth to meet the growing demands of society and the economy and ac- commodate the continual improvement in living standards. However, the widespread use of construction materials has an important impact on resource consumption [2–4]. Furthermore, infrastructure development also results in substantial resource-related and environmental problems, such as increasing the scarcity of natural resources [5], land use [6], climate change [7], mercury emissions [8, 9], SO 2 emissions [10], and CO 2 emissions [11–14]. Related impacts can also occur during the construction phase (materials production, manufacturing, and construction), in the use phase, and finally in the post-construction phase when in- frastructure needs to be replaced [15, 16]. ese impacts are especially notable for China. Indeed, investment and con- struction of infrastructure have grown rapidly since the start of the gradualist economic reform in 1978, as the economy has developed rapidly and the average income of citizens has Hindawi Complexity Volume 2020, Article ID 4364912, 20 pages https://doi.org/10.1155/2020/4364912
Transcript of MaterialConsumptionandCarbonEmissionsAssociatedwiththe...
Research ArticleMaterial Consumption and Carbon Emissions Associated with theInfrastructure Construction of 34 Cities in Northeast China
Heming Wang12 Yao Wang 1 Cong Fan1 Xinzhe Wang1 Yao Wei1 Zhihe Zhang1
Jiashi Wang1 Fengmei Ma23 and Qiang Yue1
1State Environmental Protection Key Laboratory of Eco-Industry Northeastern University Shenyang China2Commonwealth Scientific and Industrial Research Organisation (CSIRO) Canberra Australia3College of Economics and Management Shenyang Agricultural University Shenyang China
Correspondence should be addressed to Yao Wang wangyao_2018hotmailcom
Received 18 June 2020 Revised 27 July 2020 Accepted 5 August 2020 Published 7 October 2020
Guest Editor Jianhong (Cecilia) Xia
Copyright copy 2020HemingWang et al-is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Over the past three decades China has experienced rapid economic growth along with a rapid increase in urbanization and livingstandards leading to a boom in infrastructure demand A large part of Chinarsquos newly constructed infrastructure is through urbanconstruction thus cities have become a major source of material consumption and carbon emissions Understanding therelationship between material consumption carbon emissions and the economic growth of cities is key to ensuring that theconstruction of infrastructure satisfies the needs for both economic development and dematerialization In this study we firstaccounted for material consumption and the carbon emissions of infrastructure construction of 34 cities in Northeast China andcharacterized spatial and temporal changes from 2010ndash2017-ematerial use and carbon emissions of infrastructure constructiondeclined by 346 and 302 during this period Specifically material consumption decreased from 3052 million tonnes to 1996million tonnes and carbon emissions decreased from 777 million tonnes to 543 million tonnes Furthermore we used adecoupling indicator to evaluate the decoupling of material consumption or carbon emissions fromGDP in these cities We foundthat most cities have achieved the absolute decoupling of material consumption and carbon emissions from GDP over the studyperiod Finally we proposed several policy recommendations for promoting the sustainable development of the infrastructure ofcities To ensure that cities realize low-carbon urbanization policymakers need to promote modular buildings and low-emissionconstruction materials -is paper also serves as a practical reference for the improvement of relevant materials and carbonemissions management strategies for other developing regions
1 Introduction
Infrastructure has a transformative impact on social de-velopment and living standards and provides a variety ofservices including construction energy water and wastemanagement [1] At the same time it also provides a meansof storage for the extraction of natural resources from theenvironment -e scale of Chinese infrastructure con-struction has shown unprecedented growth to meet thegrowing demands of society and the economy and ac-commodate the continual improvement in living standardsHowever the widespread use of construction materials hasan important impact on resource consumption [2ndash4]
Furthermore infrastructure development also results insubstantial resource-related and environmental problemssuch as increasing the scarcity of natural resources [5] landuse [6] climate change [7] mercury emissions [8 9] SO2emissions [10] and CO2 emissions [11ndash14] Related impactscan also occur during the construction phase (materialsproduction manufacturing and construction) in the usephase and finally in the post-construction phase when in-frastructure needs to be replaced [15 16] -ese impacts areespecially notable for China Indeed investment and con-struction of infrastructure have grown rapidly since the startof the gradualist economic reform in 1978 as the economyhas developed rapidly and the average income of citizens has
HindawiComplexityVolume 2020 Article ID 4364912 20 pageshttpsdoiorg10115520204364912
increased [17] Construction in China accounts for nearlyhalf of the worldrsquos new buildings on an annual basis [18 19]-ere is no doubt that these construction activities directlylead to increases in the overall level of CO2 emissions inChina However the key to slowing global warming is tocontrol and reduce CO2 emissions China has pledged toreduce the CO2 per unit of GDP by 60ndash65 of the 2005 levelby 2030 [20] To achieve this goal understanding the currentstatus and characteristics of carbon emissions during in-frastructure construction is imperative
Cities have become the center of economic and socialactivities at the country and regional level after the IndustrialRevolution and the development of urban infrastructureprovides the foundation for the operation and developmentof cities Over the past 30 years Chinarsquos infrastructuredevelopment has rapidly developed as the scale of invest-ment the scope of construction and the construction levelof infrastructure have continuously increased A large part ofChinarsquos newly constructed infrastructure consists of urbanconstruction to accommodate urban economic activities andurban expansion [21 22] Construction materials such assteel and cement are the most utilized resources in urbanareas after water by mass [4 23] -erefore a deeper un-derstanding of the relationship between material con-sumption and CO2 emissions in the context of the economicdevelopment of Chinarsquos urban infrastructure construction iscrucial for low-carbon development and policymaking
In recent years a number of papers have investigatedmaterial flows and stocks at various scales including global[24ndash26] national [27 28] regional [29] and urban levels[30ndash32] Material flow analysis is the most popular andstandardized approach for analyzing inflow and outflowdata such as the import export and transfer of material in asystem [33 34]-is method can be further divided into top-down and bottom-up approaches which are used to studythe relationship between material flow and CO2 emissionsRemote sensing (RS) and geographic information system(GIS) tools have also been used to address data shortages andto compile local infrastructure information to study materialflow at different spatial scales
In Table 1 we provide a summary of the material flows ininfrastructure studies at different scales temporal scopesand sector coverage Additionally research on the materialflow of infrastructure has also been focused on the CO2emissions of construction For example Shi and Huangmeasured the CO2 emissions associated with the con-struction of Chinarsquos buildings and road network usingdynamic material flow analysis [38 54] Guo studied thestock changes and lifecycle greenhouse gas emissions (GHG)emissions of the urban road system showing that the twomajor periods with GHG emissions are production andmaintenance [55]
Although these studies provide a solid foundation ofaccounting methods and have enhanced our understandingof material flows and CO2 emissions associated with in-frastructure a few major gaps remain that require furtherresearch First these previous studies have mostly focusedon the embodied CO2 emissions associated with a single typeof infrastructure or material in a specific area rather than the
infrastructure system as a whole at the city level Second therelationship between material consumption the carbonemissions of infrastructure construction and economicdevelopment has been seldom discussed -ird few studieshave examined cities in Northeast China In China a largenumber of people have moved from rural areas to cities-is along with economic development has led to theincreased development of infrastructure and in turn theconsumption of more materials and the emission of moreCO2 -erefore understanding the material consumptionand carbon emissions associated with infrastructure con-struction is important for promoting the sustainable de-velopment of cities
Here we used a bottom-up accounting method to es-timate the material consumption of seven major infra-structures and 10 types of materials estimate the CO2emissions of infrastructure construction and analyze therelationship between material consumption CO2 emissionsand GDP in 34 selected cities in Northeast China Specifi-cally we aimed to thoroughly characterize material con-sumption and carbon emissions as well as identify potentialways for optimizing infrastructure resources and promotingsustainable urbanization
2 Methods and Data
21 Study Area -e prefecture-level city is one of the majoradministrative divisions in China between the level of theprovince and county Northeast China consists of threeprovincesmdashLiaoning Jilin and Heilongjiangmdasheach ofwhich includes 14 eight and 12 prefecture-level cities re-spectively -e study area in this paper includes all 34prefecture-level cities in the three provinces of NortheastChina (Figure 1) By 2017 these 34 cities in Northeast Chinahad approximately 73 of the countryrsquos population andcontributed to 63 of national GDP (httpwwwstatsgovcn) demonstrating the important role that this region playsin the Chinese economy-e list of prefecture-level cities foreach province is shown in Table 2
22 Data Sources -is article divides the infrastructure ofChina into three main units based on their importance andavailability of data building transportation and publicfacility (Figure 2) -e dataset included infrastructure-re-lated data for 34 prefecture-level cities in the three north-eastern provinces of China in 2010 2012 2015 and 2017Statistical data regarding the size of their subtypes includingthe floor areas of newly built residential and non-residentialbuildings length of road systems tap water pipelines sewerpipelines gas distribution pipelines and street lamp datawere primarily collected from Statistical Yearbooks pub-lished by local statistical departments and institutes [56ndash59]and the ldquoChina Urban Construction Statistical Yearbook(2010ndash2018)rdquo Population data for cities came from theannual average population estimates noted in the ldquoChinaStatistical Yearbook (2010ndash2018)rdquo which represented thepopulation that was using urban infrastructure -e tenmain types of construction materials were considered for
2 Complexity
accounting as they reflect the specificity of the infrastruc-ture-ematerial intensity of each type of infrastructure andmaterial was compiled from published literature (Table S1)-e carbon emission intensity of construction materials wasestimated by calculating the carbon emission coefficient-ecarbon emission intensity of construction materials wasexpressed as the CO2 emitted per unit of constructionmaterials during production and processing from the lifecycle assessment (LCA) database and published papersAdditional carbon emission intensity data are shown inTable S2
23 Estimates of Material Consumption and Embodied Car-bon Emissions -e material consumption of infrastructureconstruction was calculated using the bottom-up accountingmethod -e mathematical equations used to estimate
Chinarsquos infrastructure construction material consumptionand embodied carbon emissions were the following
Skij A
kj times MIij (1)
where S is the building material consumption A is the newfloor space of buildings completed and MI is the materialintensity -e indices k i and j are the year buildingfunctional type and construction material type respectively
Rkaj P
kaj times MIaj + N
kaj times MIaj (2)
where R is the material consumption for roads P is thelength of newly constructed road and N is the roadmaintenance length -e indices k and a are the year andtype of road respectively
Gkcj Q
kcj times MIcj (3)
Table 1 Studies on the material flow of infrastructure Top-down top-down account method Bottom-up bottom-up account methodRS remote sensing GIS geographical information system
Scale Method Study area Temporal scope Material Sector coverage Reference
Global Top-down Global 1900ndash2010 Constructionmaterials
Buildings infrastructure andmachinery [25]
RS Global 2012 Steel Buildings and infrastructure [39]
Country
GIS-basedbottom-up Japan 1945ndash2010 Construction
materials Buildings and infrastructure [40]
Bottom-up -e United States andJapan 1930ndash2005 Construction
materials Buildings [41]
Bottom-up China 1950ndash2050 Constructionmaterials Buildings and transport network [36]
GIS-basedbottom-up Japan 1965ndash2010 Construction
materials Buildings and infrastructure [42]
Bottom-up China 2000ndash2010 Steel Buildings [43]
Bottom-up EU25 2004ndash2009 Constructionmaterials
Residential buildings andtransportation networks [44]
Bottom-up China 1900ndash2100 Steel Buildings [45]
Top-down Japan 1970ndash2000 Constructionmaterials Buildings [46]
RegionBottom-up 31 provinces in China 1978ndash2008 Construction
materialsResidential buildings and
infrastructure [47]
RS 30 provinces in China 1992ndash2008 Constructionmaterials Buildings and infrastructure [48]
City
GIS-basedbottom-up Vienna (Austria) 1918ndash2013 Construction
materials Buildings [49]
Bottom-up Rio de Janeiro (Brazil) 2010 Constructionmaterials Residential buildings [50]
GIS-basedbottom-up Chiclayo (Peru) 2007 Construction
materials Buildings [51]
GIS-basedbottom-up Wakayama (Japan) 1855ndash2004 Construction
materials Buildings [52]
Bottom-up Beijing (China) 1949ndash2008 Constructionmaterials Residential buildings [53]
Bottom-up Beijing Shanghai andTianjin (China) 1978ndash2013 Construction
materials Buildings and infrastructure [54]
GIS-basedbottom-up Philadelphia (US) 2004ndash2012 Construction
materials Buildings [55]
RS Canberra (Australia) 1955 1981 2015 Constructionmaterials Buildings [56]
Complexity 3
0 250 500 1000 1500 2000Kilometers
Kilometers
N
S
EW
N
S
EW
120deg0prime0PrimeE 130deg0prime0PrimeE
50deg0prime0PrimeN
45deg0prime0PrimeN
40deg0prime0PrimeN
NO data
Study area
0 75150 300 450 600
(a) (b)
Figure 1 Map of the study area
Table 2 Cities within each of the three provinces of Northeast China examined in this study
Provinces Prefecture-level cities covered
Liaoning Shenyang Dalian Anshan Fushun Benxi Dandong Jinzhou Yingkou Fuxin Liaoyang Panjin Tieling ChaoyangHuludao
Jilin Changchun Jilin Siping Liaoyuan Tonghua Baishan Songyuan BaichengHeilongjiang Harbin Qiqihar Jixi Hegang Shuangyashan Daqing Yichun Jiamusi Qitaihe Mudanjiang Heihe Suihua
Infrastructure construction dataset
Building Transportation Public facility
Tap waterpipelines
Sewerpipelines
Gas distributionpipelines Street lampsRoadsNon-residential
buildingsResidentialbuildings
Material intensityTen types of material composition indicators
Carbon emission intensityLife cycle assessment database
Resu
lts
Construction material consumption
Embodied carbon footprint
Figure 2 -e framework underlying the material consumption and carbon emissions of infrastructure construction
4 Complexity
where G is the material consumption of public facilities andQ is the newly added length or unit of public facilities -eindex c corresponds to the type of public facility
Ek
1113944j
Skij times ej + 1113944
j
Rkaj times ej + 1113944
j
Gkcj times ej (4)
where E is the embodied carbon of infrastructure con-struction and e is the embodied carbon emissions intensityof the material
24 Decoupling Indicator -e decoupling analysis methodwas used to provide an indicator for analyzing the degree towhich environmental load and economic growth weredecoupled In recent years growing concerns relating toresource use and climate change have prompted organiza-tions to use decoupling analysis for research and develop-ment [60] ldquoDecouplingrdquo involves breaking the link betweenenvironmental hazards and economic development Gen-erally there are two modes of decoupling resourcedecoupling (or dematerialization) and decreasing negativeenvironmental impacts such as CO2 emissions Lu et alderived a pair of decoupling indicators for resource use andCO2 emissions from the IPAT equation [61ndash63] -edecoupling indicator is given by the following formula
D t
gtimes(1 + g) (5)
where D is decoupling indicator (Dm represents thedecoupling of the materials consumption of infrastructureconstruction and GDP and De represents the decoupling ofCO2 emissions of infrastructure construction and GDP) g isthe geometric average growth rate of GDP and t is thegeometric average rate of decline in the material con-sumption or CO2 emissions per unit GDP According to thevalues of D (Dm or De) the degree to which materialconsumption is decoupled from CO2 emissions and GDPcan be divided into three states absolute decoupling relativedecoupling and non-decoupling (Table 3) [64]
3 Results and Discussion
31OverviewofMaterialConsumption -e ten categories ofconstruction materials of the seven subtypes within the threetypes of infrastructure for 34 cities and trends of materialconsumption from 2010ndash2017 are shown in Figures 3 and 4Over the past seven years the total material consumption ofinfrastructure construction in 34 cities has decreased by346 from 3052 million tonnes in 2010 to 1996 milliontonnes in 2017 -e overall trends can be divided into threestages -e growth rate of GDP (338) was faster than thatof the consumption of construction materials (114) from2010ndash2012 (Figure S1) indicating that the economic de-velopment caused by infrastructure construction has in-creased From 2012ndash2015 GDP growth slowed sharply to63 At the same time the material consumption of in-frastructure also showed negative growth with the rate ofdecline reaching 103 However from 2015ndash2017 theoverall infrastructure material consumption and
construction scale of 34 cities along with GDP declined by78 and 346 respectively -is decline primarily stemsfrom the fact that the amount of infrastructure investmentand the scale of construction in Northeast China are largelydependent on the development of local economies [65]
Buildings are the unit with the greatest amount ofmaterials (Figure 3) At the same time the improvement inliving standards has promoted an increase in the con-struction of non-residential buildings indeed the annualmaterial accumulation of non-residential buildings exceedsthat of residential buildings every year -e second largestuse comes from transportation in which the share of totalmaterial consumption has increased slightly from 98 in2010 to 162 in 2017 Transportation was followed bypublic facilities including tap water pipelines sewer pipe-lines gas distribution pipes and street lamps whichaccounted for 51 of total material consumption in 2010and 119 in 2017 -is increase may be related to the factthat the proportion of natural gas in Chinarsquos primary energyconsumption has increased to 10 by 2020 [66] Con-struction of the China-Russia East Natural Gas Line began in2015 and this project has undoubtedly led to the con-struction of public facilities [67]
Sand and gravel cement brick and steel are the top fourmaterials that have been accumulated for use in infra-structure accounting for 96ndash98 of all materials used(Figure 4) Because of changes in the size of buildingsconstructed the amount of cement used decreased from169 in 2010 to 148 in 2017 -e proportion of steelconsumption increased from 37 in 2010 to 58 in 2017reflecting the wide application of steel in infrastructure -eimpact of infrastructure development on the environment issubstantial and these materials including cement and steelconsume several different resources such as fossil fuels andwater during the production process -erefore extendingthe lifespan of infrastructure with proper maintenance isnecessary
32 Spatiotemporal Variation in Material Use -e devel-opment of 34 cities in Northeast China has been uneven-us analyzing the consumption of construction materialsin different cities separately is necessary for characterizingthe material management problems faced during the de-velopment of different cities
-e total consumption of infrastructure constructionmaterials of cities in Northeast China is shown in Figure 5Shenyang Changchun and Harbin were the largest con-sumers of construction materials with total consumptionmore than 20 million tonnes within these cities in 2010
Table 3 Division of the degree of decoupling based on the values ofthe decoupling indicator of material consumption or CO2 emis-sions (Dm or De)
Degree of decoupling Economic growth Economic declineAbsolute decoupling Dge 1 Dle 0Relative decoupling 0ltDlt 1 0ltDlt 1Non-decoupling Dle 0 Dge 1
Complexity 5
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
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[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
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18 Complexity
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[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
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[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
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[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
increased [17] Construction in China accounts for nearlyhalf of the worldrsquos new buildings on an annual basis [18 19]-ere is no doubt that these construction activities directlylead to increases in the overall level of CO2 emissions inChina However the key to slowing global warming is tocontrol and reduce CO2 emissions China has pledged toreduce the CO2 per unit of GDP by 60ndash65 of the 2005 levelby 2030 [20] To achieve this goal understanding the currentstatus and characteristics of carbon emissions during in-frastructure construction is imperative
Cities have become the center of economic and socialactivities at the country and regional level after the IndustrialRevolution and the development of urban infrastructureprovides the foundation for the operation and developmentof cities Over the past 30 years Chinarsquos infrastructuredevelopment has rapidly developed as the scale of invest-ment the scope of construction and the construction levelof infrastructure have continuously increased A large part ofChinarsquos newly constructed infrastructure consists of urbanconstruction to accommodate urban economic activities andurban expansion [21 22] Construction materials such assteel and cement are the most utilized resources in urbanareas after water by mass [4 23] -erefore a deeper un-derstanding of the relationship between material con-sumption and CO2 emissions in the context of the economicdevelopment of Chinarsquos urban infrastructure construction iscrucial for low-carbon development and policymaking
In recent years a number of papers have investigatedmaterial flows and stocks at various scales including global[24ndash26] national [27 28] regional [29] and urban levels[30ndash32] Material flow analysis is the most popular andstandardized approach for analyzing inflow and outflowdata such as the import export and transfer of material in asystem [33 34]-is method can be further divided into top-down and bottom-up approaches which are used to studythe relationship between material flow and CO2 emissionsRemote sensing (RS) and geographic information system(GIS) tools have also been used to address data shortages andto compile local infrastructure information to study materialflow at different spatial scales
In Table 1 we provide a summary of the material flows ininfrastructure studies at different scales temporal scopesand sector coverage Additionally research on the materialflow of infrastructure has also been focused on the CO2emissions of construction For example Shi and Huangmeasured the CO2 emissions associated with the con-struction of Chinarsquos buildings and road network usingdynamic material flow analysis [38 54] Guo studied thestock changes and lifecycle greenhouse gas emissions (GHG)emissions of the urban road system showing that the twomajor periods with GHG emissions are production andmaintenance [55]
Although these studies provide a solid foundation ofaccounting methods and have enhanced our understandingof material flows and CO2 emissions associated with in-frastructure a few major gaps remain that require furtherresearch First these previous studies have mostly focusedon the embodied CO2 emissions associated with a single typeof infrastructure or material in a specific area rather than the
infrastructure system as a whole at the city level Second therelationship between material consumption the carbonemissions of infrastructure construction and economicdevelopment has been seldom discussed -ird few studieshave examined cities in Northeast China In China a largenumber of people have moved from rural areas to cities-is along with economic development has led to theincreased development of infrastructure and in turn theconsumption of more materials and the emission of moreCO2 -erefore understanding the material consumptionand carbon emissions associated with infrastructure con-struction is important for promoting the sustainable de-velopment of cities
Here we used a bottom-up accounting method to es-timate the material consumption of seven major infra-structures and 10 types of materials estimate the CO2emissions of infrastructure construction and analyze therelationship between material consumption CO2 emissionsand GDP in 34 selected cities in Northeast China Specifi-cally we aimed to thoroughly characterize material con-sumption and carbon emissions as well as identify potentialways for optimizing infrastructure resources and promotingsustainable urbanization
2 Methods and Data
21 Study Area -e prefecture-level city is one of the majoradministrative divisions in China between the level of theprovince and county Northeast China consists of threeprovincesmdashLiaoning Jilin and Heilongjiangmdasheach ofwhich includes 14 eight and 12 prefecture-level cities re-spectively -e study area in this paper includes all 34prefecture-level cities in the three provinces of NortheastChina (Figure 1) By 2017 these 34 cities in Northeast Chinahad approximately 73 of the countryrsquos population andcontributed to 63 of national GDP (httpwwwstatsgovcn) demonstrating the important role that this region playsin the Chinese economy-e list of prefecture-level cities foreach province is shown in Table 2
22 Data Sources -is article divides the infrastructure ofChina into three main units based on their importance andavailability of data building transportation and publicfacility (Figure 2) -e dataset included infrastructure-re-lated data for 34 prefecture-level cities in the three north-eastern provinces of China in 2010 2012 2015 and 2017Statistical data regarding the size of their subtypes includingthe floor areas of newly built residential and non-residentialbuildings length of road systems tap water pipelines sewerpipelines gas distribution pipelines and street lamp datawere primarily collected from Statistical Yearbooks pub-lished by local statistical departments and institutes [56ndash59]and the ldquoChina Urban Construction Statistical Yearbook(2010ndash2018)rdquo Population data for cities came from theannual average population estimates noted in the ldquoChinaStatistical Yearbook (2010ndash2018)rdquo which represented thepopulation that was using urban infrastructure -e tenmain types of construction materials were considered for
2 Complexity
accounting as they reflect the specificity of the infrastruc-ture-ematerial intensity of each type of infrastructure andmaterial was compiled from published literature (Table S1)-e carbon emission intensity of construction materials wasestimated by calculating the carbon emission coefficient-ecarbon emission intensity of construction materials wasexpressed as the CO2 emitted per unit of constructionmaterials during production and processing from the lifecycle assessment (LCA) database and published papersAdditional carbon emission intensity data are shown inTable S2
23 Estimates of Material Consumption and Embodied Car-bon Emissions -e material consumption of infrastructureconstruction was calculated using the bottom-up accountingmethod -e mathematical equations used to estimate
Chinarsquos infrastructure construction material consumptionand embodied carbon emissions were the following
Skij A
kj times MIij (1)
where S is the building material consumption A is the newfloor space of buildings completed and MI is the materialintensity -e indices k i and j are the year buildingfunctional type and construction material type respectively
Rkaj P
kaj times MIaj + N
kaj times MIaj (2)
where R is the material consumption for roads P is thelength of newly constructed road and N is the roadmaintenance length -e indices k and a are the year andtype of road respectively
Gkcj Q
kcj times MIcj (3)
Table 1 Studies on the material flow of infrastructure Top-down top-down account method Bottom-up bottom-up account methodRS remote sensing GIS geographical information system
Scale Method Study area Temporal scope Material Sector coverage Reference
Global Top-down Global 1900ndash2010 Constructionmaterials
Buildings infrastructure andmachinery [25]
RS Global 2012 Steel Buildings and infrastructure [39]
Country
GIS-basedbottom-up Japan 1945ndash2010 Construction
materials Buildings and infrastructure [40]
Bottom-up -e United States andJapan 1930ndash2005 Construction
materials Buildings [41]
Bottom-up China 1950ndash2050 Constructionmaterials Buildings and transport network [36]
GIS-basedbottom-up Japan 1965ndash2010 Construction
materials Buildings and infrastructure [42]
Bottom-up China 2000ndash2010 Steel Buildings [43]
Bottom-up EU25 2004ndash2009 Constructionmaterials
Residential buildings andtransportation networks [44]
Bottom-up China 1900ndash2100 Steel Buildings [45]
Top-down Japan 1970ndash2000 Constructionmaterials Buildings [46]
RegionBottom-up 31 provinces in China 1978ndash2008 Construction
materialsResidential buildings and
infrastructure [47]
RS 30 provinces in China 1992ndash2008 Constructionmaterials Buildings and infrastructure [48]
City
GIS-basedbottom-up Vienna (Austria) 1918ndash2013 Construction
materials Buildings [49]
Bottom-up Rio de Janeiro (Brazil) 2010 Constructionmaterials Residential buildings [50]
GIS-basedbottom-up Chiclayo (Peru) 2007 Construction
materials Buildings [51]
GIS-basedbottom-up Wakayama (Japan) 1855ndash2004 Construction
materials Buildings [52]
Bottom-up Beijing (China) 1949ndash2008 Constructionmaterials Residential buildings [53]
Bottom-up Beijing Shanghai andTianjin (China) 1978ndash2013 Construction
materials Buildings and infrastructure [54]
GIS-basedbottom-up Philadelphia (US) 2004ndash2012 Construction
materials Buildings [55]
RS Canberra (Australia) 1955 1981 2015 Constructionmaterials Buildings [56]
Complexity 3
0 250 500 1000 1500 2000Kilometers
Kilometers
N
S
EW
N
S
EW
120deg0prime0PrimeE 130deg0prime0PrimeE
50deg0prime0PrimeN
45deg0prime0PrimeN
40deg0prime0PrimeN
NO data
Study area
0 75150 300 450 600
(a) (b)
Figure 1 Map of the study area
Table 2 Cities within each of the three provinces of Northeast China examined in this study
Provinces Prefecture-level cities covered
Liaoning Shenyang Dalian Anshan Fushun Benxi Dandong Jinzhou Yingkou Fuxin Liaoyang Panjin Tieling ChaoyangHuludao
Jilin Changchun Jilin Siping Liaoyuan Tonghua Baishan Songyuan BaichengHeilongjiang Harbin Qiqihar Jixi Hegang Shuangyashan Daqing Yichun Jiamusi Qitaihe Mudanjiang Heihe Suihua
Infrastructure construction dataset
Building Transportation Public facility
Tap waterpipelines
Sewerpipelines
Gas distributionpipelines Street lampsRoadsNon-residential
buildingsResidentialbuildings
Material intensityTen types of material composition indicators
Carbon emission intensityLife cycle assessment database
Resu
lts
Construction material consumption
Embodied carbon footprint
Figure 2 -e framework underlying the material consumption and carbon emissions of infrastructure construction
4 Complexity
where G is the material consumption of public facilities andQ is the newly added length or unit of public facilities -eindex c corresponds to the type of public facility
Ek
1113944j
Skij times ej + 1113944
j
Rkaj times ej + 1113944
j
Gkcj times ej (4)
where E is the embodied carbon of infrastructure con-struction and e is the embodied carbon emissions intensityof the material
24 Decoupling Indicator -e decoupling analysis methodwas used to provide an indicator for analyzing the degree towhich environmental load and economic growth weredecoupled In recent years growing concerns relating toresource use and climate change have prompted organiza-tions to use decoupling analysis for research and develop-ment [60] ldquoDecouplingrdquo involves breaking the link betweenenvironmental hazards and economic development Gen-erally there are two modes of decoupling resourcedecoupling (or dematerialization) and decreasing negativeenvironmental impacts such as CO2 emissions Lu et alderived a pair of decoupling indicators for resource use andCO2 emissions from the IPAT equation [61ndash63] -edecoupling indicator is given by the following formula
D t
gtimes(1 + g) (5)
where D is decoupling indicator (Dm represents thedecoupling of the materials consumption of infrastructureconstruction and GDP and De represents the decoupling ofCO2 emissions of infrastructure construction and GDP) g isthe geometric average growth rate of GDP and t is thegeometric average rate of decline in the material con-sumption or CO2 emissions per unit GDP According to thevalues of D (Dm or De) the degree to which materialconsumption is decoupled from CO2 emissions and GDPcan be divided into three states absolute decoupling relativedecoupling and non-decoupling (Table 3) [64]
3 Results and Discussion
31OverviewofMaterialConsumption -e ten categories ofconstruction materials of the seven subtypes within the threetypes of infrastructure for 34 cities and trends of materialconsumption from 2010ndash2017 are shown in Figures 3 and 4Over the past seven years the total material consumption ofinfrastructure construction in 34 cities has decreased by346 from 3052 million tonnes in 2010 to 1996 milliontonnes in 2017 -e overall trends can be divided into threestages -e growth rate of GDP (338) was faster than thatof the consumption of construction materials (114) from2010ndash2012 (Figure S1) indicating that the economic de-velopment caused by infrastructure construction has in-creased From 2012ndash2015 GDP growth slowed sharply to63 At the same time the material consumption of in-frastructure also showed negative growth with the rate ofdecline reaching 103 However from 2015ndash2017 theoverall infrastructure material consumption and
construction scale of 34 cities along with GDP declined by78 and 346 respectively -is decline primarily stemsfrom the fact that the amount of infrastructure investmentand the scale of construction in Northeast China are largelydependent on the development of local economies [65]
Buildings are the unit with the greatest amount ofmaterials (Figure 3) At the same time the improvement inliving standards has promoted an increase in the con-struction of non-residential buildings indeed the annualmaterial accumulation of non-residential buildings exceedsthat of residential buildings every year -e second largestuse comes from transportation in which the share of totalmaterial consumption has increased slightly from 98 in2010 to 162 in 2017 Transportation was followed bypublic facilities including tap water pipelines sewer pipe-lines gas distribution pipes and street lamps whichaccounted for 51 of total material consumption in 2010and 119 in 2017 -is increase may be related to the factthat the proportion of natural gas in Chinarsquos primary energyconsumption has increased to 10 by 2020 [66] Con-struction of the China-Russia East Natural Gas Line began in2015 and this project has undoubtedly led to the con-struction of public facilities [67]
Sand and gravel cement brick and steel are the top fourmaterials that have been accumulated for use in infra-structure accounting for 96ndash98 of all materials used(Figure 4) Because of changes in the size of buildingsconstructed the amount of cement used decreased from169 in 2010 to 148 in 2017 -e proportion of steelconsumption increased from 37 in 2010 to 58 in 2017reflecting the wide application of steel in infrastructure -eimpact of infrastructure development on the environment issubstantial and these materials including cement and steelconsume several different resources such as fossil fuels andwater during the production process -erefore extendingthe lifespan of infrastructure with proper maintenance isnecessary
32 Spatiotemporal Variation in Material Use -e devel-opment of 34 cities in Northeast China has been uneven-us analyzing the consumption of construction materialsin different cities separately is necessary for characterizingthe material management problems faced during the de-velopment of different cities
-e total consumption of infrastructure constructionmaterials of cities in Northeast China is shown in Figure 5Shenyang Changchun and Harbin were the largest con-sumers of construction materials with total consumptionmore than 20 million tonnes within these cities in 2010
Table 3 Division of the degree of decoupling based on the values ofthe decoupling indicator of material consumption or CO2 emis-sions (Dm or De)
Degree of decoupling Economic growth Economic declineAbsolute decoupling Dge 1 Dle 0Relative decoupling 0ltDlt 1 0ltDlt 1Non-decoupling Dle 0 Dge 1
Complexity 5
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
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[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
accounting as they reflect the specificity of the infrastruc-ture-ematerial intensity of each type of infrastructure andmaterial was compiled from published literature (Table S1)-e carbon emission intensity of construction materials wasestimated by calculating the carbon emission coefficient-ecarbon emission intensity of construction materials wasexpressed as the CO2 emitted per unit of constructionmaterials during production and processing from the lifecycle assessment (LCA) database and published papersAdditional carbon emission intensity data are shown inTable S2
23 Estimates of Material Consumption and Embodied Car-bon Emissions -e material consumption of infrastructureconstruction was calculated using the bottom-up accountingmethod -e mathematical equations used to estimate
Chinarsquos infrastructure construction material consumptionand embodied carbon emissions were the following
Skij A
kj times MIij (1)
where S is the building material consumption A is the newfloor space of buildings completed and MI is the materialintensity -e indices k i and j are the year buildingfunctional type and construction material type respectively
Rkaj P
kaj times MIaj + N
kaj times MIaj (2)
where R is the material consumption for roads P is thelength of newly constructed road and N is the roadmaintenance length -e indices k and a are the year andtype of road respectively
Gkcj Q
kcj times MIcj (3)
Table 1 Studies on the material flow of infrastructure Top-down top-down account method Bottom-up bottom-up account methodRS remote sensing GIS geographical information system
Scale Method Study area Temporal scope Material Sector coverage Reference
Global Top-down Global 1900ndash2010 Constructionmaterials
Buildings infrastructure andmachinery [25]
RS Global 2012 Steel Buildings and infrastructure [39]
Country
GIS-basedbottom-up Japan 1945ndash2010 Construction
materials Buildings and infrastructure [40]
Bottom-up -e United States andJapan 1930ndash2005 Construction
materials Buildings [41]
Bottom-up China 1950ndash2050 Constructionmaterials Buildings and transport network [36]
GIS-basedbottom-up Japan 1965ndash2010 Construction
materials Buildings and infrastructure [42]
Bottom-up China 2000ndash2010 Steel Buildings [43]
Bottom-up EU25 2004ndash2009 Constructionmaterials
Residential buildings andtransportation networks [44]
Bottom-up China 1900ndash2100 Steel Buildings [45]
Top-down Japan 1970ndash2000 Constructionmaterials Buildings [46]
RegionBottom-up 31 provinces in China 1978ndash2008 Construction
materialsResidential buildings and
infrastructure [47]
RS 30 provinces in China 1992ndash2008 Constructionmaterials Buildings and infrastructure [48]
City
GIS-basedbottom-up Vienna (Austria) 1918ndash2013 Construction
materials Buildings [49]
Bottom-up Rio de Janeiro (Brazil) 2010 Constructionmaterials Residential buildings [50]
GIS-basedbottom-up Chiclayo (Peru) 2007 Construction
materials Buildings [51]
GIS-basedbottom-up Wakayama (Japan) 1855ndash2004 Construction
materials Buildings [52]
Bottom-up Beijing (China) 1949ndash2008 Constructionmaterials Residential buildings [53]
Bottom-up Beijing Shanghai andTianjin (China) 1978ndash2013 Construction
materials Buildings and infrastructure [54]
GIS-basedbottom-up Philadelphia (US) 2004ndash2012 Construction
materials Buildings [55]
RS Canberra (Australia) 1955 1981 2015 Constructionmaterials Buildings [56]
Complexity 3
0 250 500 1000 1500 2000Kilometers
Kilometers
N
S
EW
N
S
EW
120deg0prime0PrimeE 130deg0prime0PrimeE
50deg0prime0PrimeN
45deg0prime0PrimeN
40deg0prime0PrimeN
NO data
Study area
0 75150 300 450 600
(a) (b)
Figure 1 Map of the study area
Table 2 Cities within each of the three provinces of Northeast China examined in this study
Provinces Prefecture-level cities covered
Liaoning Shenyang Dalian Anshan Fushun Benxi Dandong Jinzhou Yingkou Fuxin Liaoyang Panjin Tieling ChaoyangHuludao
Jilin Changchun Jilin Siping Liaoyuan Tonghua Baishan Songyuan BaichengHeilongjiang Harbin Qiqihar Jixi Hegang Shuangyashan Daqing Yichun Jiamusi Qitaihe Mudanjiang Heihe Suihua
Infrastructure construction dataset
Building Transportation Public facility
Tap waterpipelines
Sewerpipelines
Gas distributionpipelines Street lampsRoadsNon-residential
buildingsResidentialbuildings
Material intensityTen types of material composition indicators
Carbon emission intensityLife cycle assessment database
Resu
lts
Construction material consumption
Embodied carbon footprint
Figure 2 -e framework underlying the material consumption and carbon emissions of infrastructure construction
4 Complexity
where G is the material consumption of public facilities andQ is the newly added length or unit of public facilities -eindex c corresponds to the type of public facility
Ek
1113944j
Skij times ej + 1113944
j
Rkaj times ej + 1113944
j
Gkcj times ej (4)
where E is the embodied carbon of infrastructure con-struction and e is the embodied carbon emissions intensityof the material
24 Decoupling Indicator -e decoupling analysis methodwas used to provide an indicator for analyzing the degree towhich environmental load and economic growth weredecoupled In recent years growing concerns relating toresource use and climate change have prompted organiza-tions to use decoupling analysis for research and develop-ment [60] ldquoDecouplingrdquo involves breaking the link betweenenvironmental hazards and economic development Gen-erally there are two modes of decoupling resourcedecoupling (or dematerialization) and decreasing negativeenvironmental impacts such as CO2 emissions Lu et alderived a pair of decoupling indicators for resource use andCO2 emissions from the IPAT equation [61ndash63] -edecoupling indicator is given by the following formula
D t
gtimes(1 + g) (5)
where D is decoupling indicator (Dm represents thedecoupling of the materials consumption of infrastructureconstruction and GDP and De represents the decoupling ofCO2 emissions of infrastructure construction and GDP) g isthe geometric average growth rate of GDP and t is thegeometric average rate of decline in the material con-sumption or CO2 emissions per unit GDP According to thevalues of D (Dm or De) the degree to which materialconsumption is decoupled from CO2 emissions and GDPcan be divided into three states absolute decoupling relativedecoupling and non-decoupling (Table 3) [64]
3 Results and Discussion
31OverviewofMaterialConsumption -e ten categories ofconstruction materials of the seven subtypes within the threetypes of infrastructure for 34 cities and trends of materialconsumption from 2010ndash2017 are shown in Figures 3 and 4Over the past seven years the total material consumption ofinfrastructure construction in 34 cities has decreased by346 from 3052 million tonnes in 2010 to 1996 milliontonnes in 2017 -e overall trends can be divided into threestages -e growth rate of GDP (338) was faster than thatof the consumption of construction materials (114) from2010ndash2012 (Figure S1) indicating that the economic de-velopment caused by infrastructure construction has in-creased From 2012ndash2015 GDP growth slowed sharply to63 At the same time the material consumption of in-frastructure also showed negative growth with the rate ofdecline reaching 103 However from 2015ndash2017 theoverall infrastructure material consumption and
construction scale of 34 cities along with GDP declined by78 and 346 respectively -is decline primarily stemsfrom the fact that the amount of infrastructure investmentand the scale of construction in Northeast China are largelydependent on the development of local economies [65]
Buildings are the unit with the greatest amount ofmaterials (Figure 3) At the same time the improvement inliving standards has promoted an increase in the con-struction of non-residential buildings indeed the annualmaterial accumulation of non-residential buildings exceedsthat of residential buildings every year -e second largestuse comes from transportation in which the share of totalmaterial consumption has increased slightly from 98 in2010 to 162 in 2017 Transportation was followed bypublic facilities including tap water pipelines sewer pipe-lines gas distribution pipes and street lamps whichaccounted for 51 of total material consumption in 2010and 119 in 2017 -is increase may be related to the factthat the proportion of natural gas in Chinarsquos primary energyconsumption has increased to 10 by 2020 [66] Con-struction of the China-Russia East Natural Gas Line began in2015 and this project has undoubtedly led to the con-struction of public facilities [67]
Sand and gravel cement brick and steel are the top fourmaterials that have been accumulated for use in infra-structure accounting for 96ndash98 of all materials used(Figure 4) Because of changes in the size of buildingsconstructed the amount of cement used decreased from169 in 2010 to 148 in 2017 -e proportion of steelconsumption increased from 37 in 2010 to 58 in 2017reflecting the wide application of steel in infrastructure -eimpact of infrastructure development on the environment issubstantial and these materials including cement and steelconsume several different resources such as fossil fuels andwater during the production process -erefore extendingthe lifespan of infrastructure with proper maintenance isnecessary
32 Spatiotemporal Variation in Material Use -e devel-opment of 34 cities in Northeast China has been uneven-us analyzing the consumption of construction materialsin different cities separately is necessary for characterizingthe material management problems faced during the de-velopment of different cities
-e total consumption of infrastructure constructionmaterials of cities in Northeast China is shown in Figure 5Shenyang Changchun and Harbin were the largest con-sumers of construction materials with total consumptionmore than 20 million tonnes within these cities in 2010
Table 3 Division of the degree of decoupling based on the values ofthe decoupling indicator of material consumption or CO2 emis-sions (Dm or De)
Degree of decoupling Economic growth Economic declineAbsolute decoupling Dge 1 Dle 0Relative decoupling 0ltDlt 1 0ltDlt 1Non-decoupling Dle 0 Dge 1
Complexity 5
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
0 250 500 1000 1500 2000Kilometers
Kilometers
N
S
EW
N
S
EW
120deg0prime0PrimeE 130deg0prime0PrimeE
50deg0prime0PrimeN
45deg0prime0PrimeN
40deg0prime0PrimeN
NO data
Study area
0 75150 300 450 600
(a) (b)
Figure 1 Map of the study area
Table 2 Cities within each of the three provinces of Northeast China examined in this study
Provinces Prefecture-level cities covered
Liaoning Shenyang Dalian Anshan Fushun Benxi Dandong Jinzhou Yingkou Fuxin Liaoyang Panjin Tieling ChaoyangHuludao
Jilin Changchun Jilin Siping Liaoyuan Tonghua Baishan Songyuan BaichengHeilongjiang Harbin Qiqihar Jixi Hegang Shuangyashan Daqing Yichun Jiamusi Qitaihe Mudanjiang Heihe Suihua
Infrastructure construction dataset
Building Transportation Public facility
Tap waterpipelines
Sewerpipelines
Gas distributionpipelines Street lampsRoadsNon-residential
buildingsResidentialbuildings
Material intensityTen types of material composition indicators
Carbon emission intensityLife cycle assessment database
Resu
lts
Construction material consumption
Embodied carbon footprint
Figure 2 -e framework underlying the material consumption and carbon emissions of infrastructure construction
4 Complexity
where G is the material consumption of public facilities andQ is the newly added length or unit of public facilities -eindex c corresponds to the type of public facility
Ek
1113944j
Skij times ej + 1113944
j
Rkaj times ej + 1113944
j
Gkcj times ej (4)
where E is the embodied carbon of infrastructure con-struction and e is the embodied carbon emissions intensityof the material
24 Decoupling Indicator -e decoupling analysis methodwas used to provide an indicator for analyzing the degree towhich environmental load and economic growth weredecoupled In recent years growing concerns relating toresource use and climate change have prompted organiza-tions to use decoupling analysis for research and develop-ment [60] ldquoDecouplingrdquo involves breaking the link betweenenvironmental hazards and economic development Gen-erally there are two modes of decoupling resourcedecoupling (or dematerialization) and decreasing negativeenvironmental impacts such as CO2 emissions Lu et alderived a pair of decoupling indicators for resource use andCO2 emissions from the IPAT equation [61ndash63] -edecoupling indicator is given by the following formula
D t
gtimes(1 + g) (5)
where D is decoupling indicator (Dm represents thedecoupling of the materials consumption of infrastructureconstruction and GDP and De represents the decoupling ofCO2 emissions of infrastructure construction and GDP) g isthe geometric average growth rate of GDP and t is thegeometric average rate of decline in the material con-sumption or CO2 emissions per unit GDP According to thevalues of D (Dm or De) the degree to which materialconsumption is decoupled from CO2 emissions and GDPcan be divided into three states absolute decoupling relativedecoupling and non-decoupling (Table 3) [64]
3 Results and Discussion
31OverviewofMaterialConsumption -e ten categories ofconstruction materials of the seven subtypes within the threetypes of infrastructure for 34 cities and trends of materialconsumption from 2010ndash2017 are shown in Figures 3 and 4Over the past seven years the total material consumption ofinfrastructure construction in 34 cities has decreased by346 from 3052 million tonnes in 2010 to 1996 milliontonnes in 2017 -e overall trends can be divided into threestages -e growth rate of GDP (338) was faster than thatof the consumption of construction materials (114) from2010ndash2012 (Figure S1) indicating that the economic de-velopment caused by infrastructure construction has in-creased From 2012ndash2015 GDP growth slowed sharply to63 At the same time the material consumption of in-frastructure also showed negative growth with the rate ofdecline reaching 103 However from 2015ndash2017 theoverall infrastructure material consumption and
construction scale of 34 cities along with GDP declined by78 and 346 respectively -is decline primarily stemsfrom the fact that the amount of infrastructure investmentand the scale of construction in Northeast China are largelydependent on the development of local economies [65]
Buildings are the unit with the greatest amount ofmaterials (Figure 3) At the same time the improvement inliving standards has promoted an increase in the con-struction of non-residential buildings indeed the annualmaterial accumulation of non-residential buildings exceedsthat of residential buildings every year -e second largestuse comes from transportation in which the share of totalmaterial consumption has increased slightly from 98 in2010 to 162 in 2017 Transportation was followed bypublic facilities including tap water pipelines sewer pipe-lines gas distribution pipes and street lamps whichaccounted for 51 of total material consumption in 2010and 119 in 2017 -is increase may be related to the factthat the proportion of natural gas in Chinarsquos primary energyconsumption has increased to 10 by 2020 [66] Con-struction of the China-Russia East Natural Gas Line began in2015 and this project has undoubtedly led to the con-struction of public facilities [67]
Sand and gravel cement brick and steel are the top fourmaterials that have been accumulated for use in infra-structure accounting for 96ndash98 of all materials used(Figure 4) Because of changes in the size of buildingsconstructed the amount of cement used decreased from169 in 2010 to 148 in 2017 -e proportion of steelconsumption increased from 37 in 2010 to 58 in 2017reflecting the wide application of steel in infrastructure -eimpact of infrastructure development on the environment issubstantial and these materials including cement and steelconsume several different resources such as fossil fuels andwater during the production process -erefore extendingthe lifespan of infrastructure with proper maintenance isnecessary
32 Spatiotemporal Variation in Material Use -e devel-opment of 34 cities in Northeast China has been uneven-us analyzing the consumption of construction materialsin different cities separately is necessary for characterizingthe material management problems faced during the de-velopment of different cities
-e total consumption of infrastructure constructionmaterials of cities in Northeast China is shown in Figure 5Shenyang Changchun and Harbin were the largest con-sumers of construction materials with total consumptionmore than 20 million tonnes within these cities in 2010
Table 3 Division of the degree of decoupling based on the values ofthe decoupling indicator of material consumption or CO2 emis-sions (Dm or De)
Degree of decoupling Economic growth Economic declineAbsolute decoupling Dge 1 Dle 0Relative decoupling 0ltDlt 1 0ltDlt 1Non-decoupling Dle 0 Dge 1
Complexity 5
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
where G is the material consumption of public facilities andQ is the newly added length or unit of public facilities -eindex c corresponds to the type of public facility
Ek
1113944j
Skij times ej + 1113944
j
Rkaj times ej + 1113944
j
Gkcj times ej (4)
where E is the embodied carbon of infrastructure con-struction and e is the embodied carbon emissions intensityof the material
24 Decoupling Indicator -e decoupling analysis methodwas used to provide an indicator for analyzing the degree towhich environmental load and economic growth weredecoupled In recent years growing concerns relating toresource use and climate change have prompted organiza-tions to use decoupling analysis for research and develop-ment [60] ldquoDecouplingrdquo involves breaking the link betweenenvironmental hazards and economic development Gen-erally there are two modes of decoupling resourcedecoupling (or dematerialization) and decreasing negativeenvironmental impacts such as CO2 emissions Lu et alderived a pair of decoupling indicators for resource use andCO2 emissions from the IPAT equation [61ndash63] -edecoupling indicator is given by the following formula
D t
gtimes(1 + g) (5)
where D is decoupling indicator (Dm represents thedecoupling of the materials consumption of infrastructureconstruction and GDP and De represents the decoupling ofCO2 emissions of infrastructure construction and GDP) g isthe geometric average growth rate of GDP and t is thegeometric average rate of decline in the material con-sumption or CO2 emissions per unit GDP According to thevalues of D (Dm or De) the degree to which materialconsumption is decoupled from CO2 emissions and GDPcan be divided into three states absolute decoupling relativedecoupling and non-decoupling (Table 3) [64]
3 Results and Discussion
31OverviewofMaterialConsumption -e ten categories ofconstruction materials of the seven subtypes within the threetypes of infrastructure for 34 cities and trends of materialconsumption from 2010ndash2017 are shown in Figures 3 and 4Over the past seven years the total material consumption ofinfrastructure construction in 34 cities has decreased by346 from 3052 million tonnes in 2010 to 1996 milliontonnes in 2017 -e overall trends can be divided into threestages -e growth rate of GDP (338) was faster than thatof the consumption of construction materials (114) from2010ndash2012 (Figure S1) indicating that the economic de-velopment caused by infrastructure construction has in-creased From 2012ndash2015 GDP growth slowed sharply to63 At the same time the material consumption of in-frastructure also showed negative growth with the rate ofdecline reaching 103 However from 2015ndash2017 theoverall infrastructure material consumption and
construction scale of 34 cities along with GDP declined by78 and 346 respectively -is decline primarily stemsfrom the fact that the amount of infrastructure investmentand the scale of construction in Northeast China are largelydependent on the development of local economies [65]
Buildings are the unit with the greatest amount ofmaterials (Figure 3) At the same time the improvement inliving standards has promoted an increase in the con-struction of non-residential buildings indeed the annualmaterial accumulation of non-residential buildings exceedsthat of residential buildings every year -e second largestuse comes from transportation in which the share of totalmaterial consumption has increased slightly from 98 in2010 to 162 in 2017 Transportation was followed bypublic facilities including tap water pipelines sewer pipe-lines gas distribution pipes and street lamps whichaccounted for 51 of total material consumption in 2010and 119 in 2017 -is increase may be related to the factthat the proportion of natural gas in Chinarsquos primary energyconsumption has increased to 10 by 2020 [66] Con-struction of the China-Russia East Natural Gas Line began in2015 and this project has undoubtedly led to the con-struction of public facilities [67]
Sand and gravel cement brick and steel are the top fourmaterials that have been accumulated for use in infra-structure accounting for 96ndash98 of all materials used(Figure 4) Because of changes in the size of buildingsconstructed the amount of cement used decreased from169 in 2010 to 148 in 2017 -e proportion of steelconsumption increased from 37 in 2010 to 58 in 2017reflecting the wide application of steel in infrastructure -eimpact of infrastructure development on the environment issubstantial and these materials including cement and steelconsume several different resources such as fossil fuels andwater during the production process -erefore extendingthe lifespan of infrastructure with proper maintenance isnecessary
32 Spatiotemporal Variation in Material Use -e devel-opment of 34 cities in Northeast China has been uneven-us analyzing the consumption of construction materialsin different cities separately is necessary for characterizingthe material management problems faced during the de-velopment of different cities
-e total consumption of infrastructure constructionmaterials of cities in Northeast China is shown in Figure 5Shenyang Changchun and Harbin were the largest con-sumers of construction materials with total consumptionmore than 20 million tonnes within these cities in 2010
Table 3 Division of the degree of decoupling based on the values ofthe decoupling indicator of material consumption or CO2 emis-sions (Dm or De)
Degree of decoupling Economic growth Economic declineAbsolute decoupling Dge 1 Dle 0Relative decoupling 0ltDlt 1 0ltDlt 1Non-decoupling Dle 0 Dge 1
Complexity 5
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
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[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Compared with 2010 most cities have reduced the con-sumption of infrastructure construction materials in 2017However cities with large total material consumption havestill been concentrated in cities with greater degrees ofeconomic development in the region such as Changchun
Shenyang and Harbin indicating that infrastructureconstruction is one of the factors driving economic de-velopment Figure 6 shows the per capita consumption ofurban infrastructure construction materials -e percapita material consumption in cities such as Yingkou
400
350
300
250
200
150
100
50
0
Mill
ion
tonn
es
Sand and gravelWoodNon-residential buildingsGas disitribution pipelinesBuildings
BrickGlassRoadsPublic facilitySteel
PlasticTap water pipelinesLimeCeramicSewer pipelines
CementAsphaltResidential buildingsStreet lampsTransportation
Material Subtype Type2010
Material Subtype Type2012
Material Subtype Type2015
Material Subtype Type2017
Figure 3 -e distribution of material consumption structure across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017
(a) (b)
(c) (d)
Figure 4 Distribution of construction material consumption across infrastructure types in 34 cities in Northeast China in 2010 2012 2015and 2017 Note the width of the streamline represents the amount of material consumption (a) Year of 2010 (b) Year of 2012 (c) Year of2015 (d) Year of 2017 -e units in the figure are million tonnes
6 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Total material consumption(2010)
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Unit million tonnesN
o da
ta
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2012)
N
S
EW
(b)Total material consumption
(2015)N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
(c)
N
S
EW
Unit million tonnes
No
data
00ndash
50
50ndash
100
100
ndash15
0
150
ndash20
0
gt20
0
Kilometers0 75 150 300 450 600
Total material consumption(2017)
(d)
Figure 5 Spatial patterns of the total material consumption of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 7
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
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[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Per capita material consumption(2010)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita material consumption(2012)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita material consumption
(2015)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita material consumption(2017)
Unit tonnescap
No
data
00ndash
10
10ndash
20
20ndash
30
30ndash
40
gt40
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 6 Spatial patterns of per capita material consumption of the infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
8 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
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[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Daqing and Shenyang was much higher than the averageuse which made these cities the largest per capita con-sumers of materials in 2010 In 2017 in contrast to thepattern for total material consumption the top threelargest per capita consumers of materials were BaishanChangchun and Mudanjiang Per capita material con-sumption relative to the degree of infrastructure devel-opment reflected an uneven distribution of the scale ofinfrastructure construction across 34 cities in NortheastChina -e distribution of total material consumption andper capita material consumption of infrastructure wasconsistent with the disparity in economic developmentacross cities In general cities with a high degree ofeconomic development such as Shenyang Changchunand Harbin can take full advantage of radiation effects tocoordinate regional development
For the 14 cities in Liaoning province trends in thetotal material consumption and per capita materialconsumption of infrastructure construction can be di-vided into two stages From 2010 to 2012 the 14 citiesexperienced rapid growth in the material use of infra-structure -e average rate of increase for this two-yearperiod was 186 -e average annual growth rates ofinfrastructure material consumption per capita and GDPwere 189 and 153 respectively During this periodthe large-scale construction of infrastructure has pro-moted the development of the local economy and ur-banization In the second period from 2012ndash2017 totalmaterial consumption and per capita consumption de-clined at an average annual rate of 196 and 193respectively For the eight cities in Jilin province totalmaterial consumption decreased between 2010 and 2015while material consumption increased between 2015 and2017 In contrast total consumption and per capitaconsumption of infrastructure construction materials inHeilongjiangrsquos 12 cities decreased from 2010ndash2017 -etotal material consumption decreased from 91 milliontonnes in 2010 to 68 million tonnes in 2017 -is decreasemay stem from the fact that the average annual populationdecreased on an annual basis and the decrease in the sizeof the city has been more pronounced
Material intensity of use is an indicator of material ef-ficiency that is most often expressed as the amount ofmaterial consumption per unit of economic output [68]Greater material intensity of use corresponds to less effi-ciency in the degree to which material use contributes toGDP growth Figure 7 shows the material intensity of use ofurban infrastructure construction materials From 2010 to2017 cities with the highest GDP among the 34 cities such asDalian Changchun and Shenyang had lower material in-tensity of use values which usually corresponded to lowermaterial intensities Cities with a greater degree of economicdevelopment thus enjoy lower material consumption in-tensity while several cities with higher total material con-sumption had higher material consumption intensityDeveloping cities can improve resource efficiency by con-trolling the extensive sprawl of urban land improving thecompactness of cities and reducing their dependence onmaterials [69]
33 Embodied Carbon Footprint Based on the above anal-ysis steel brick and cement account for a large proportionof infrastructure materials which are the primary causes ofCO2 emissions and other toxic pollutants in the mining andmanufacturing processes [70ndash72] -is paper further esti-mates the amount of CO2 emissions by the infrastructureconstruction activities of 34 cities Figures 8 and 9 map theamount of total CO2 emissions and per capita CO2 emissionsof 34 cities in Northeast China across several sample yearsIn 2010 Shenyang Harbin and Changchun had the highestlevels of CO2 emissions while Qitaihe Liaoyuan and Heihehad the lowest levels of CO2 emissions Cities with thehighest CO2 emissions generated from infrastructure con-struction were Shenyang Changchun and Harbin whichwas consistent with the pattern observed in total materialconsumption across cities from 2010 to 2015 Similarlyduring this period most cities showed high levels of CO2emissions stemming from the construction of infrastructure-e emissions per capita varied among cities because ofdifferences in city size and material consumption Shenyangshowed the greatest change in per capita emissions amongcities which largely stemmed from its higher urbanizationrate However changes in total CO2 emissions and per capitaemissions were notable between 2015 and 2017 with mostcities showing reduced CO2 emissions associated with re-ductions in infrastructure construction A few exceptionssuch as Changchun still maintained a high level of CO2emissions During this period the growth rate of GDP inmost cities declined and even showed negative growthleading to decreased investment in infrastructure con-struction -e reduction in infrastructure investment di-rectly led to a decline in the scale of infrastructureconstruction As a result both total emissions and per capitaemissions decreased In addition the reduction in materialconsumption intensity in each city improved material effi-ciency and played an important role in reducing the carbonfootprint [25]
-e carbon emissions intensity (CEI) defined as CO2 perunit of GDP is an important indicator for capturing therelationship between carbon emissions and the economy[73] For example Shenyang is one of the highest emitters ofCO2 In 2017 Shenyangrsquos emission level was 13 times higherthan that of Huludaorsquos emission level However HuludaorsquosCEI was 61 times higher than that of Shenyangrsquos CEIChinarsquos 13th Five-Year Plan (2016ndash2020) introduced a newnational carbon intensity indicator assessment system andproposed energy reduction targets based on carbon inten-sity Hence focusing on CEI facilitates the consideration ofCO2 mitigation strategies independent of their economicimpact Figure 10 shows the CEI distribution of 34 cities inNortheast China from 2010 to 2017 Overall CEI decreasedfrom 2010 to 2017 -e three cities with the highest CEIvalues were Yingkou Tonghua and Suihua which allexhibited CEI values greater than 03 tonnes104 CNY in2010 By 2017 the CEI of most cities had declined to less than02 tonnes104 CNY Notably only Huludao continued toshow a CEI above 04 tonnes104 CNY and this stability wasdriven in part by the lower degree of economic developmentin this city within Liaoning province
Complexity 9
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
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[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Material consumption intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Material consumption intensity(2012)
Unit tonnes104 CNYN
o da
ta
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Material consumption intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Material consumption intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 7 Spatial patterns of the material consumption intensity of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
10 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Total carbon emissions(2010)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Total carbon emissions(2012)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(b)Total carbon emissions
(2015)
Unit million tonnes
No
data
gt60
Kilometers0 75 150 300 450 600
N
S
EW
00ndash
15
15ndash
30
30ndash
45
45ndash
60
(c)
Total carbon emissions(2017)
Unit million tonnes
No
data
00ndash
15
15ndash
30
30ndash
45
45ndash
60
gt60
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 8 Spatial patterns of the total CO2 emissions associated with infrastructure construction of 34 cities in Northeast China in 20102012 2015 and 2017
Complexity 11
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Among the 34 cities in Northeast China with greaterdegrees of economic development Shenyang DalianChangchun and Harbin showed high levels of total
emissions and per capita emissions from infrastructureconstruction but CEI values were lower than the provincialaverage-is finding indicates that infrastructure tends to be
Per capita carbon emissions(2010)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Per capita carbon emissions(2012)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(b)Per capita carbon emissions
(2015)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Per capita carbon emissions(2017)
Unit tonnescap
No
data
00ndash
03
03ndash
06
06ndash
09
09ndash
12
gt12
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 9 Spatial patterns of total per capita CO2 emissions of infrastructure construction of 34 cities in Northeast China in 2010 2012 2015and 2017
12 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
Carbon emissions intensity(2010)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(a)
Carbon emissions intensity(2012)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(b)Carbon emissions intensity
(2015)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(c)
Carbon emissions intensity(2017)
Unit tonnes104 CNY
No
data
00ndash
01
01ndash
02
02ndash
03
03ndash
04
gt04
Kilometers0 75 150 300 450 600
N
S
EW
(d)
Figure 10 Spatial patterns of carbon emissions intensity (CEI) of infrastructure construction of 34 cities in Northeast China in 2010 20122015 and 2017
Complexity 13
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
built in cities showing robust economic performance thatwould thus profit more from urban economic services andtechnical development In contrast cities with higher CEIvalues showed much lower levels of infrastructure con-struction with lower levels of urbanization from 2010ndash2017
34 Decoupling Analysis Here the results of the decouplinganalysis of material consumption and the CO2 emissions ofinfrastructure construction from GDP in 34 cities of threeprovinces in Northeast China from 2010ndash2017 are presentedBased on GDPmaterial consumption and carbon emissionsdata for 34 cities we calculated the values of g and t for eachcity -e decoupling indicators (Dm and De) were calculatedby equation (5) In this study there is a strong correlationbetween material consumption and carbon emissions ininfrastructure construction -e two decoupling states ofeach city will appear similar to some extent
Figure 11 shows the decoupling of the material con-sumption of infrastructure construction from economicgrowth in 34 cities of Northeast China from 2010ndash2017Among cities that showed economic growth during thestudy period a total of 21 cities achieved the absolutedecoupling of the material consumption of infrastructureconstruction from GDP growth Among cities showingabsolute decoupling the decoupling level of Liaoyang wasthe highest (Dm of 225) Meanwhile cities that managed todecouple carbon emissions and GDP growth were also thesame as those that had managed to decouple the materialconsumption of infrastructure built and GDP growth(Figure 12) During this period the decoupling of these 10cities indicates that there was an improvement in the sus-tainable infrastructure construction of economic develop-ment Because of the slow economic growth (only 1ndash10)the government has focused on ensuring that the devel-opment of the economy is in harmony with the materialconsumption of infrastructure built and the environmentwhich has facilitated the growth of the economy to someextent but has reduced the pressure on the environment-erefore growth in material consumption and carbonemissions reduced and the sustainability of developmentimproved
Songyuan Baishan and Qiqihar achieved the relativedecoupling of the material consumption of infrastructureand carbon emissions of infrastructure construction andpositive economic growth -e environmental impact alsoincreased along with GDP but the growth rate was lowerthan that of GDP In this period Huludao LiaoyuanShuangyashan Mudanjiang and Jiamusi did not achieve thedecoupling of the material consumption or carbon emis-sions from GDP indicating that the growth rate of theenvironmental impact as a consequence of GDP growth hasexceeded the growth rate in GDP -e eight cities in therelatively decoupling and non-decoupling areas were moredependent on infrastructure construction for economicdevelopment but the problem was that the structure ofeconomic development was relatively simple Furthermoreeconomic growth was accompanied by an acceleration ofenvironmental disruption
Four cities had achieved the absolute decoupling ofmaterial consumption or carbon emissions of infrastructureconstruction and economy among cities with negativeeconomic growth which reduced the pressure on the en-vironment to some extent Economic development in thesecities is heavily dependent on carbon-intensive industry-us improving the technical aspects of economic devel-opment should be a priority for reducing material use andcarbon emissions However Qitaihe achieved non-decou-pling despite its economic downturnWith the advantages ofbeing close to Harbin there is an urgent need for this city topromote economic development by expanding the scale ofincoming investment to adapt to the existing industrialstructure
35Policy Implications Northeast China developed into oneof the largest industrial centers during the First Five-YearPlan (1953ndash1957) andmade outstanding contributions to theChinese economy [74] However as a consequence of re-source depletion environmental pollution and commercialreconstruction the economic development of NortheastChina experienced a recession in the 1990s -e imple-mentation of the strategy of ldquoRevitalizing the Old IndustrialBase of Northeast Chinardquo proposed in 2003 provided aunique opportunity to facilitate the development of theNortheast region [75] At the same time economic recoveryin the Northeast depended on infrastructure constructionand indirectly resulted in the emission of a large amount ofCO2 -us means by which economic growth could beaccelerated while suppressing material consumption andcarbon emissions should receive increased attention frompolicymakers and researchers
-e northeastern region of China has experienced rapidurbanization and industrialization which has been ac-companied by a large amount of material consumptionassociated with infrastructure construction and carbonemissions Based on the above research we provide thefollowing suggestions for promoting the coordinated de-velopment of the economy resources and the environmentin Northeast China
(1) According to the above results steel brick andcement account for a large proportion of infra-structure materials which impose a huge load on theenvironment -erefore the local governmentshould increase its direct investment in research onenergy-saving and low-emission construction ma-terials in view of future urban infrastructure con-struction Innovative energy-efficient constructiontechnologies and material applications will greatlybenefit urban ecology Given that the economicdevelopment of the 34 focal cities in Northeast Chinawill still need to rely on infrastructure constructionin the coming decades there is a need to identifyinfrastructure alternatives study material flows anduse less energy-intensive construction materials -eincrease in prices caused by resource depletion willbecome an obstacle to promoting economic devel-opment identifying alternative sociotechnical
14 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
systems and reducing GHG emissions -ereforethe utilization of green modular buildings and low-emission construction materials is of great impor-tance in developing cities All of these relevantpolicies need to be developed so that the findings ofscientists are bridged with the interests of local of-ficials [76]
(2) From 2010 to 2017 the population size of most citiesin Northeast China also decreased (see Tables S4 forpopulation change data) -e decline in urbanpopulations is one of the characteristics of urbanshrinkage [77ndash79] City shrinkage involves the dual
loss of population quantity and quality Additionallyin some shrinking cities the reduction in demandmay be detrimental for the control of the materialconsumption of infrastructure construction whichslows the decoupling of materials and the environ-mental impact on GDP Hence policymakers andcity planners should improve the infrastructureplanning system to protect from the risk of over-exploitation thereby increasing the utilization rate ofinfrastructure in the context of population outflow
(3) Cities with low per capita carbon emissions that haveachieved the absolute decoupling of material
Liaoyang (001 225)Fushun (001 1721)Dandong
ShenyangChaoyang
YingkouJinzhouDalian
PanjinFuxin
HuludaoAnshan
Tieling
Benxi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(a)
TonghuaSiping
JilinBaicheng Changchun
Liaoyuan
Baishan
Songyuan
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
Dm
g
(b)
HegangQitaihe
Daqing
Yichun HarbinSuihua
Heihe
JiamusiMudanjiang
Shuangyashan
QiqiharJixi
10
8
6
4
2
0
ndash2
ndash4
ndash6
ndash8
ndash10
ndash12
ndash005 0 005 01 015
Dm = 1
Dm = ndash1
g
Dm
(c)
Figure 11 Decoupling chart of the material consumption of infrastructure construction for 34 cities in Northeast China during 2010ndash2017(Dm) (a) shows the decoupling of the material consumption of infrastructure construction in 14 cities of Liaoning province (b) shows thedecoupling of material consumption of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the materialconsumption of infrastructure construction in 12 cities of Heilongjiang province Dm the decoupling indicator for the material con-sumption of infrastructure g geometric average of the growth rate of gross domestic product (GDP) in a certain period
Complexity 15
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
consumption from GDP such as Suihua Dandongand Heihe which are in less-developed states andlosing population should pay more attention toeffectively use the existing infrastructure -is is avital piece of information for those cities inNortheast China to rationally allocate investment toestablish a comprehensive and efficient infrastruc-ture network and enhance management level basedon existing infrastructure rather than blindlyexpanding the scale of construction SpecificallyHuludao Liaoyuan Shuangyashan and Qitaihe haveachieved non-decoupling -ese types of citiesshould adjust the structure of their economic
development improve the efficiency of infrastruc-ture construction material use and change theircurrent excessive dependence on infrastructure fordriving the economy In contrast Anshan Benxiand Daqing are cities well known for the decouplingof their ldquononmetal and metal industryrdquo productionmaterial consumption carbon emissions associatedwith infrastructure construction and GDP -esecities have experienced negative economic growthduring this period -rough special subsidies andlower taxes policymakers need to encourageadjusting the industrial structure and establishing asynergistic feedback mechanism between urban
Liaoyang (001 2162)Fushun (001 2061)De
De = 1
De = ndash1
13
11
9
7
5
3
1
ShenyangChaoyang
Yingkou
DalianPanjinFuxin
Jinzhou
HuludaoTieling
Benxi
Anshan
ndash005 1 005 01 015ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
g
Dandong
(a)
De13
11
9
7
5
3
1
ndash005 005 01 0151
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
De = 1
De = ndash1
g
Siping Tonghua
JilinSongyuan Baicheng Changchun
BaishanLiaoyuan
(b)
De13
11
9
7
5
3
11
ndash3
ndash5
ndash7
ndash9
ndash11
ndash13
Hegang
YichunHarbin Suihua
HeiheQiqiharJixiQitaihe
ShuangyashanMudanjiang Jiamusi
Daqing
De = 1
De = ndash1ndash005 005 01 015
g
(c)
Figure 12 Decoupling chart of the carbon emissions of infrastructure construction for 34 cities in Northeast China from 2010ndash2017 (De)(a) shows the decoupling of the carbon emissions of infrastructure construction in 14 cities of Liaoning province (b) shows the decouplingof the carbon emissions of infrastructure construction in eight cities in Jilin province (c) shows the decoupling of the carbon emissions ofinfrastructure construction in 12 cities in Heilongjiang province De decoupling indicator for the material consumption of infrastructureg geometric average of gross domestic product (GDP) growth rate in a certain period
16 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
infrastructure systems and industry with the aim ofpromoting economic development
36 Limitations -is study aims to analyze temporal-spatialmaterial consumption and carbon emissions in 34 cities andthe decoupling conditions of material use and carbonemissions from GDP for infrastructure construction -ereare still some limitations in this study -is study ignores thematerial loss generated by transportation and constructionin other stages because of the lack of data In addition it ishard to access data to take no account of the disposal of sometypes of public facilities such as sewer pipes and gas dis-tribution pipes-e lack of datamight slightly underestimatethe total material consumption and carbon emissions -esefactors will be considered in future research to adequatelyand accurately estimate the material consumption andcarbon emissions in infrastructure construction at the cityscale
4 Conclusions
In this study we examined the material consumption andcarbon emissions associated with the infrastructure con-struction of 34 cities in Northeast China
-e material consumption of infrastructure built hasincreased rapidly from 3052 million tonnes to 3399million tonnes from 2010ndash2012 and then slightly de-creased to 3049 million tonnes from 2012ndash2015 fol-lowed by a significant decline to 1996 million tonnes by2017 -e total carbon emissions of infrastructure con-struction reached 777 million tonnes 870 milliontonnes 813 million tonnes and 543 million tonnesacross several sample years respectively Material con-sumption and carbon emissions varied among cities andmost carbon emissions were concentrated in ShenyangDalian Changchun and Harbin Additionally the ma-terial consumption intensity and carbon emission in-tensity of infrastructure construction in most citiesdecreased indicating that the efficiency of material useand emission efficiency had increased -e proportion ofenergy-intensive materials such as cement brick andsteel continued to increase which may thus have com-paratively higher environmental impacts
We also found that the overall distribution of infra-structure construction was uneven -e distribution of in-frastructure construction was consistent with the disparity ineconomic development across cities Based on the overalltrend in development from 2010ndash2017 across the 34 citiesthere is still a long way to go before the complete decouplingof material consumption or carbon emissions with GDP canbe achieved Over the next few decades there is an urgentneed to increase the application of green modular buildingsand improve the infrastructure planning system given thatan increased amount of infrastructure is being built tosupport the development of the urban economy -is studyprovides comparable spatial-temporal city-level materialconsumption and carbon emissions data for future researchon the relationships between economic development and
infrastructure construction in Northeast China Moreoverthis paper also aimed to provide practical values that couldserve as references for other cities to achieve sustainabledevelopment
Data Availability
-e data used to support the findings of this study areavailable from the corresponding author and governmentstatistical yearbook upon request
Conflicts of Interest
-e authors declare that they have no conflicts of interest
Acknowledgments
-is research was supported by the National Natural ScienceFoundation of China (52070034 41871204 and 71403175)and Fundamental Research Funds for the Central Univer-sities (N182502045) -e authors appreciate the helpfulfeedback from the editor and anonymous reviewers
Supplementary Materials
Table S1 material intensity in different infrastructures inChina Table S2 embodied carbon emission intensity ofconstruction materials in China (tCO2t) Table S3 values ofGDP in 34 cities at four points during the study period (20102012 2015 and 2017) (unit 1times 104 yuan) Table S4 values ofpopulation in 34 cities at four points during the study period(2010 2012 2015 and 2017) (unit 1times 104 person) Figure S1in three time periods GDP and population growth rate of 34cities in Northeast China (Supplementary Materials)
References
[1] S -acker D Adshead M Fay et al ldquoInfrastructure forsustainable developmentrdquo Nature Sustainability vol 2 no 4pp 324ndash331 2019
[2] H Wang H Schandl X Wang et al ldquoMeasuring progress ofChinarsquos circular economyrdquo Resources Conservation andRecycling vol 163 2020
[3] M Porhincak and A Estokova ldquoComparative analysis ofenvironmental performance of building materials towardssustainable constructionrdquo in Proceedings of the 16th Inter-national Conference on Process Integration Modelling andOptimisation for Energy Saving and Pollution ReductionModelling and Optimisation for Energy Saving and PollutionReduction P Varbanov J J Klemes P Seferlis A IPapadopoulos S Voutetakis and S Pierucci Eds AidicServizi Srl Milano Italy pp 1291ndash1296 October 2013
[4] H Schandl Y Lu N Che et al ldquoShared socio-economicpathways and their implications for global materials userdquoResources Conservation and Recycling vol 160 Article ID104866 2020
[5] W Zhao H Yu S Liang W Zhang and Z Yang ldquoResourceimpacts of municipal solid waste treatment systems in Chi-nese cities based on hybrid life cycle assessmentrdquo ResourcesConservation and Recycling vol 130 pp 215ndash225 2018
[6] J Yang W L Liu Y H Li X M Li and Q S Ge ldquoSimulatingintraurban land use dynamics under multiple scenarios based
Complexity 17
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
on fuzzy cellular automata a case study of Jinzhou DistrictDalianrdquo Complexity vol 2018 Article ID 7202985 2018
[7] J Yang S H Jin X M Xiao et al ldquoLocal climate zoneventilation and urban land surface temperatures towards aperformance-based and wind-sensitive planning proposal inmegacitiesrdquo Sustainable Cities and Society vol 47 2019
[8] L Chen S Liang M Liu et al ldquoTrans-provincial healthimpacts of atmospheric mercury emissions in Chinardquo NatureCommunications vol 10 p 1484 2019
[9] J Qi Y Wang S Liang et al ldquoPrimary suppliers drivingatmospheric mercury emissions through global supplychainsrdquo One Earth vol 1 no 2 pp 254ndash266 2019
[10] Y Yu L Zhou W Zhou et al ldquoDecoupling environmentalpressure from economic growth on city level the case study ofChongqing in Chinardquo Ecological Indicators vol 75 pp 27ndash352017
[11] S Chen B Chen K Feng et al ldquoPhysical and virtual carbonmetabolism of global citiesrdquo Nature Communications vol 11p 182 2020
[12] C Lin J Qi S Liang et al ldquoSaving less in China facilitatesglobal CO2 mitigationrdquo Nature Communications vol 11p 1358 2020
[13] H Wang H Dai L Dong et al ldquoCo-benefit of carbonmitigation on resource use in Chinardquo Journal of CleanerProduction vol 174 pp 1096ndash1113 2018
[14] Y Yu D Chen B Zhu and S Hu ldquoEco-efficiency trends inChina 1978ndash2010 decoupling environmental pressure fromeconomic growthrdquo Ecological Indicators vol 24 pp 177ndash1842013
[15] D B Muller G Liu A N Loslashvik et al ldquoCarbon emissions ofinfrastructure developmentrdquo Environmental Science ampTechnology vol 47 no 20 pp 11739ndash11746 2013
[16] L Jiang B Xue Z Ma L Yu B Huang and X Chen ldquoA life-cycle based co-benefits analysis of biomass pellet productionin Chinardquo Renewable Energy vol 154 pp 445ndash452 2020
[17] A Ansar B Flyvbjerg A Budzier and D Lunn ldquoDoes in-frastructure investment lead to economic growth or economicfragility evidence from Chinardquo Oxford Review of EconomicPolicy vol 32 no 3 pp 360ndash390 2016
[18] H Zhang L Li T Chen and V Li ldquoWhere will Chinarsquos realestate market go under the economyrsquos new normalrdquo Citiesvol 55 pp 42ndash48 2016
[19] J E Fernandez ldquoResource consumption of new urban con-struction in Chinardquo Journal of Industrial Ecology vol 11no 2 pp 99ndash115 2007
[20] J P Xi ldquoWork together to build a win-win equitable andbalanced governance mechanism on climate changerdquo inProceedings of the United Nations Climate Change ConferenceParis France November 2015
[21] Z Han Y Long X Wang and J Hou ldquoUrban redevelopmentat the block level methodology and its application to allChinese citiesrdquo Environment amp Planning B Urban Analytics ampCity Science 2019
[22] J Han W-Q Chen L Zhang and G Liu ldquoUncovering thespatiotemporal dynamics of urban infrastructure develop-ment a high spatial resolution material stock and flowanalysisrdquo Environmental Science amp Technology vol 52 no 21pp 12122ndash12132 2018
[23] H Schandl M Fischer-Kowalski J West et al ldquoGlobalmaterial flows and resource productivity forty years of evi-dencerdquo Journal of Industrial Ecology vol 22 no 4pp 827ndash838 2018
[24] F Krausmann D Wiedenhofer C Lauk et al ldquoGlobal so-cioeconomic material stocks rise 23-fold over the 20th century
and require half of annual resource userdquo Proceedings of theNational Academy of Sciences vol 114 no 8 pp 1880ndash18852017
[25] H Schandl S Hatfield-Dodds T Wiedmann et alldquoDecoupling global environmental pressure and economicgrowth scenarios for energy use materials use and carbonemissionsrdquo Journal of Cleaner Production vol 132 pp 45ndash562016
[26] A Miatto H Schandl T Fishman and H Tanikawa ldquoGlobalpatterns and trends for non-metallic minerals used forconstructionrdquo Journal of Industrial Ecology vol 21 no 4pp 924ndash937 2017
[27] T Dai and W Wang ldquo-e characteristics and trends ofsocioeconomic metabolism in Chinardquo Journal of IndustrialEcology vol 22 no 5 pp 1228ndash1240 2017
[28] H Wang S Hashimoto Y Moriguchi Q Yue and Z LuldquoResource use in growing Chinardquo Journal of IndustrialEcology vol 16 no 4 pp 481ndash492 2012
[29] F Ma H Wang B Zhu et al ldquoMaterial footprint of a fast-industrializing region in China Part 1 exploring the mate-rialization process of Liaoning Provincerdquo Resources Con-servation and Recycling vol 134 pp 228ndash238 2018
[30] T M Baynes and J K Musango ldquoEstimating current andfuture global urban domestic material consumptionrdquo Envi-ronmental Research Letters vol 13 2018
[31] Q Liu Z Cao X Liu et al ldquoProduct and metal stocks ac-cumulation of Chinarsquos megacities patterns drivers andimplicationsrdquo Environmental Science amp Technology vol 53no 8 pp 4128ndash4139 2019
[32] J Guo T Fishman Y Wang et al ldquoUrban development andsustainability challenges chronicled by a century of con-struction material flows and stocks in Tiexi Chinardquo Journal ofIndustrial Ecology vol 351 2020
[33] E Muller L M Hilty R Widmer M Schluep andM Faulstich ldquoModeling metal stocks and flows a review ofdynamic material flow analysis methodsrdquo EnvironmentalScience amp Technology vol 48 no 4 pp 2102ndash2113 2014
[34] M Fischer-Kowalski F Krausmann S Giljum et alldquoMethodology and indicators of economy-wide material flowaccountingrdquo Journal of Industrial Ecology vol 15 no 6pp 855ndash876 2011
[35] H Liang L Dong H Tanikawa N Zhang Z Gao andX Luo ldquoFeasibility of a new-generation nighttime light datafor estimating in-use steel stock of buildings and civil engi-neering infrastructuresrdquo Resources Conservation and Recy-cling vol 123 pp 11ndash23 2017
[36] H Tanikawa T Fishman K Okuoka and K Sugimoto ldquo-eweight of society over time and space a comprehensive ac-count of the construction material stock of Japanrdquo Journal ofIndustrial Ecology vol 19 pp 778ndash791 2015
[37] T Fishman H Schandl H Tanikawa P Walker andF Krausmann ldquoAccounting for the material stock of nationsrdquoJournal of Industrial Ecology vol 18 no 3 pp 407ndash420 2014
[38] F Shi T Huang H Tanikawa J Han S Hashimoto andY Moriguchi ldquoToward a low carbon-dematerialization so-cietyrdquo Journal of Industrial Ecology vol 16 no 4pp 493ndash505 2012
[39] T Fishman H Schandl and H Tanikawa ldquo-e socio-eco-nomic drivers of material stock accumulation in Japanrsquosprefecturesrdquo Ecological Economics vol 113 pp 76ndash84 2015
[40] J He Q Yue Y Li F Zhao and H Wang ldquoDriving forceanalysis of carbon emissions in Chinarsquos building industry2000-2015rdquo Sustainable Cities and Society vol 60 Article ID102268 2020
18 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
[41] D Wiedenhofer J K Steinberger N Eisenmenger andW Haas ldquoMaintenance and expansion modeling materialstocks and flows for residential buildings and transportationnetworks in the EU25rdquo Journal of Industrial Ecology vol 19no 4 pp 538ndash551 2015
[42] M Hu S Pauliuk T Wang G Huppes E van der Voet andD BMuller ldquoIron and steel in Chinese residential buildings adynamic analysisrdquo Resources Conservation and Recyclingvol 54 no 9 pp 591ndash600 2010
[43] S Hashimoto H Tanikawa and Y Moriguchi ldquoFrameworkfor estimating potential wastes and secondary resources ac-cumulated within an economy-a case study of constructionminerals in Japanrdquo Waste Management vol 29 no 11pp 2859ndash2866 2009
[44] J Han and W-N Xiang ldquoAnalysis of material stock accu-mulation in Chinarsquos infrastructure and its regional disparityrdquoSustainability Science vol 8 no 4 pp 553ndash564 2013
[45] H Liang H Tanikawa Y Matsuno and L Dong ldquoModelingin-use steel stock in Chinarsquos buildings and civil engineeringinfrastructure using time-series of DMSPOLS nighttimelightsrdquo Remote Sensing vol 6 no 6 pp 4780ndash4800 2014
[46] F Kleemann J Lederer H Rechberger and J Fellner ldquoGIS-based analysis of Viennarsquos material stock in buildingsrdquoJournal of Industrial Ecology vol 21 no 2 pp 368ndash380 2017
[47] K Condeixa A Haddad and D Boer ldquoMaterial flow analysisof the residential building stock at the city of Rio de JaneirordquoJournal of Cleaner Production vol 149 pp 1249ndash1267 2017
[48] C Mesta R Kahhat and S Santa-Cruz ldquoGeospatial char-acterization of material stock in the residential sector of aLatin-American cityrdquo Journal of Industrial Ecology vol 23no 1 pp 280ndash291 2019
[49] H Tanikawa and S Hashimoto ldquoUrban stock over timespatial material stock analysis using 4d-GISrdquo Building Re-search amp Information vol 37 no 5-6 pp 483ndash502 2009
[50] H Dan Y Fang Y Zhao et al ldquoInput stocks and outputflows of urban residential building system in Beijing cityChina from 1949 to 2008rdquo Resources Conservation amp Recy-cling vol 54 pp 1177ndash1188 2010
[51] C Huang J Han and W-Q Chen ldquoChanging patterns anddeterminants of infrastructuresrsquo material stocks in Chinesecitiesrdquo Resources Conservation and Recycling vol 123pp 47ndash53 2017
[52] K A Marcellus-Zamora P M Gallagher S Spatari andH Tanikawa ldquoEstimating materials stocked by land-use typein historic urban buildings using spatio-temporal analyticaltoolsrdquo Journal of Industrial Ecology vol 20 no 5pp 1025ndash1037 2016
[53] H Schandl R Marcos-Martinez T Baynes Z Yu A MiattoandH Tanikawa ldquoA spatiotemporal urbanmetabolismmodelfor the Canberra suburb of Braddon in Australiardquo Journal ofCleaner Production vol 265 p 121770 2020
[54] T Huang F Shi H Tanikawa J Fei and J Han ldquoMaterialsdemand and environmental impact of buildings constructionand demolition in China based on dynamic material flowanalysisrdquo Resources Conservation and Recycling vol 72pp 91ndash101 2013
[55] Z Guo D Hu Z Zhang P Zhang and X Zhang ldquoMaterialmetabolism and lifecycle GHG emissions of urban roadsystem (URS)rdquo Journal of Cleaner Production vol 165pp 243ndash253 2017
[56] NBS Statistical Yearbook-2010 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2011
[57] NBS Statistical Yearbook-2012 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2013
[58] NBS Statistical Yearbook-2015 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2016
[59] NBS Statistical Yearbook-2017 (Each City of 34 Prefecture-Level Cities in Northeast China) China Statistics Press Bei-jing China 2018
[60] OECD Indicators to Measure Decoupling of EnvironmentalPressure from Economic Growth OECD Paris France 2002
[61] Z Lu H Wang and Q Yue ldquoDecoupling indicatorsquantitative relationships between resource use wasteemission and economic growthrdquo Resources Science vol 33pp 2ndash9 2011
[62] B Commoner ldquo-e environmental cost of economic growthrdquoChemistry in Britain vol 8 no 2 p 52 1972
[63] P Ehrlich and J Holdren A Bulletin Dialogue on the ldquoClosingCirclerdquo Critique One Dimensional Ecology Bulletin of theAtomic Scientists Chicago IL USA 1972
[64] H Wang S Hashimoto Q Yue Y Moriguchi and Z LuldquoDecoupling analysis of four selected countriesrdquo Journal ofIndustrial Ecology vol 17 no 4 pp 618ndash629 2013
[65] K Shan Q Wu P Cao and Q Guo ldquoEmpirical analysis ofregional economic competitiveness at the northeastern Chinaand inner Mongoliardquo in Electronic Information and ElectricalEngineering B J Chen V Hu and D Kong Eds pp769ndash773 Atlantis Press Paris France 2012
[66] C Council ldquoNational action plan for energy developmentstrategyrdquo 2014
[67] Q Zhang Z Li G Wang and H Li ldquoStudy on the impacts ofnatural gas supply cost on gas flow and infrastructure de-ployment in Chinardquo Applied Energy vol 162 pp 1385ndash13982016
[68] C Zhang W-Q Chen and M Ruth ldquoMeasuring materialefficiency a review of the historical evolution of indicatorsmethodologies and findingsrdquo Resources Conservation andRecycling vol 132 pp 79ndash92 2018
[69] R Gudipudi T Fluschnik A G C Ros C Walther andJ P Kropp ldquoCity density and CO2 efficiencyrdquo Energy Policyvol 91 pp 352ndash361 2016
[70] Q Tang P Shi Z Yuan S Shi X Xu and T KatsumildquoPotential of zero-valent iron in remediation of Cd(II) con-taminated soil from laboratory experiment mechanism studyto field applicationrdquo Soils and Foundations vol 59 no 6pp 2099ndash2109 2019
[71] W Sun Y Zhou J Lv and J Wu ldquoAssessment of multi-airemissions case of particulate matter (dust) SO2 NO and CO2from iron and steel industry of Chinardquo Journal of CleanerProduction vol 232 pp 350ndash358 2019
[72] W Sun Q Wang Z Zheng and J Cai ldquoMaterial-energy-emission nexus in the integrated iron and steel industryrdquoEnergy Conversion and Management vol 213 Article ID112828 2020
[73] F Dong B Yu T Hadachin et al ldquoDrivers of carbonemission intensity change in Chinardquo Resources Conservationand Recycling vol 129 pp 187ndash201 2018
[74] P Zhang ldquoRevitalizing old industrial base of Northeast Chinaprocess policy and challengerdquo Chinese Geographical Sciencevol 18 no 2 pp 109ndash118 2008
[75] B Xue X Xiao and J Li ldquoIdentification method and em-pirical study of urban industrial spatial relationship based onPOI big data a case of Shenyang City Chinardquo Geography andSustainability 2020
Complexity 19
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
[76] B Xue ldquoHoning the climate change messagerdquo Sciencevol 348 no 6237 p 872 2015
[77] Y-M Joo and B Seo ldquoDual policy to fight urban shrinkageDaegu South Koreardquo Cities vol 73 pp 128ndash137 2018
[78] Y Long W Zhai Y Shen and X Ye ldquoUnderstanding unevenurban expansion with natural cities using open datardquoLandscape and Urban Planning vol 177 pp 281ndash293 2018
[79] Y Long and Y Ye ldquoMeasuring human-scale urban form andits performancerdquo Landscape and Urban Planning vol 191no 3 2019
20 Complexity
![Decision …downloads.hindawi.com/journals/complexity/2020/9602526.pdfcriteria,cangrouppatterns,wheregroupsaresetsofsimilar patterns[54,59,60].Clusteringalgorithms arewidelyap-plied](https://static.fdocuments.us/doc/165x107/5f3f6490fc08093e7c56f69c/decision-criteriacangrouppatternswheregroupsaresetsofsimilar-patterns545960clusteringalgorithms.jpg)
