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Transport Policy 17 (2010) 224–229

Contents lists available at ScienceDirect

Transport Policy

0967-07

doi:10.1

E-m1 Pe

journal homepage: www.elsevier.com/locate/tranpol

Regional traffic impacts of logistics-related land use

Tina Wagner 1

Hamburg University of Technology, Institute for Transport Planning and Logistics, Schwarzenbergstraße 95 (E), 21073 Hamburg, Germany

a r t i c l e i n f o

Available online 16 February 2010

Keywords:

Truck trip generation

Traffic impact assessment

Logistics-related land use

0X/$ - see front matter & 2010 Elsevier Ltd. A

016/j.tranpol.2010.01.012

ail address: wagner_t@web.de

rmanent address: Hutten 49, 20355 Hambur

a b s t r a c t

The outsourcing of logistics activities to logistics service providers leads to a demand for new logistics-

related land development. At the moment (minimising) regional traffic generation is not a major

decision criterion for site selection and development. For a sound traffic impact assessment,

information on trip generation of logistics facilities like transfer depots, distribution centres and

warehouses is necessary. Surveys conducted in the case study region Hamburg, Germany, provide such

information. Applying the survey results, different logistics land use development scenarios are

assessed in this paper. The results show that strategic location of logistics areas can reduce traffic and

traffic impacts.

& 2010 Elsevier Ltd. All rights reserved.

1. Introduction

A high demand for new logistics and distribution facilities (e.g.warehouses, distribution centres, transfer depots) can currentlybe observed in many German and other European regions(Cushmann and Wakefield, 2006; Jones Lang Lasalle, 2006a). Thisis caused by the ongoing globalisation of production, Europeanintegration as well as restructuring and outsourcing in thelogistics market. Companies streamline their logistics organisationby reducing warehousing space and minimising the stratification ofdistribution. Also, contracts with logistics providers tend to be shorterthan before in order to enable flexible responses to market changes inthe industrial and retail sector. In consequence, logistics providersshift from own account property to rented property. Logistics-relatedproperty is therefore increasingly developed and operated byspecialised companies (e.g. Prologis or Gazely).

Logistics-related developments are often perceived as spaceconsuming, noisy and traffic intensive. While existing company plotsizes differ, new logistics facilities often tend to be space consuming.According to a study by Jones Lang Lasalle (2006b), the outsourcingof logistics activities to logistics service providers leads to a demandfor new, optimised sites larger than 5 ha. This is mostly due to thecentralisation of distribution and automatisation of warehouses. Inaddition, multi-user logistics parks that offer warehousing space inshort time contracts are becoming more popular.

Whereas the location of e.g. a national distribution centreprimarily depends on factors like the logistics organisation ofcompanies and centrality within the service area, the location of aregional distribution centre or transfer depot is also influenced by

ll rights reserved.

g, Germany.

land availability and price, land use conflicts, access to infra-structure and traffic volumes within that region. During the(re-)location of logistics companies, strong opposition fromresidents can usually be observed. With the development ofnew, modern warehouses, where most of the goods handling isdone inside, noise and emissions from goods handling aregenerally reduced. However, the impacts from the trafficgenerated by logistics facilities still need to be considered. Locally,peaks of heavy vehicle traffic as well as lorries parked in theneighbourhood have to be dealt with. Additionally, over-nightshipping provided by courier services and distribution centresleads to night-time long haul trips and early-morning deliverytours as well as daily connections. With extended operating hoursof transfer depots and distribution centres, the night-timeimpacts from moving vehicles and other activities increase. Withdaily connections, the number of trips generated at a particularsite also increases. At the regional level, the development of newsites for logistics centres can result in regional traffic growth.

Being an important economic sector, logistics companies areincreasingly coming into the focus of property developers andmunicipal business developers (refer to Hesse, 2004 for a detailedmodel of logistics land development). Local and regional autho-rities often aim for job generation and value creation whenpromoting and developing sites for logistics-related land use.Whereas possible regional economic gains of the logistic sectorare currently of high political significance, careful integration ofnew sites into the urban and regional environment is generallyneglected (Hesse, 2006). In particular, traffic generation is not amajor decision criterion for site selection and development. Thisis due mainly to two reasons. Firstly, in regions where space isscarce, finding suitable sites is difficult and traffic generation isperceived as a secondary problem. Secondly, there is very limitedplanning knowledge on trip generation of logistics-related land

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T. Wagner / Transport Policy 17 (2010) 224–229 225

uses and on how trip generation relates to the characteristics andsize of logistics centres.

The purpose of this paper, which is based on the Ph.D. thesis ofthe author (Wagner, 2009), is to present a methodology for thetraffic impact assessment of logistics-related land uses. In theHamburg case study region a company survey and traffic countswere conducted in order to generate planning parameters oflogistics-related land use. Using the results of the surveys twodifferent scenarios of the location of 210 ha new logistics-relatedland were compared regarding their traffic impacts. The followingsection on methods and materials describes the case study area, thesurveys and derived results, focussing on trip generation rates andtheir use, as well as the applied method for the traffic impactassessment. In Section 3 the traffic impacts of the two scenarios arepresented and the potential role of traffic impact assessment inregional planning is discussed.

2. Materials and methods

2.1. Case study: logistics site development in the Hamburg region

The region under consideration in this study is the City ofHamburg and its surrounding area. Hosting Europe’s secondbiggest seaport, Hamburg is a major transport hub. Containerturnover in the port is expected to double between 2005 and 2015to reach 18 million standard containers (TEU) per year. In thesame period, the additional demand for logistics and distributionfacilities is expected to be 400 ha (Burgerschaft der Freien undHansestadt Hamburg, 2005). Some of these facilities will bedirectly related to the port (190 ha); others will primarily servegoods distribution to the urban area (210 ha).

In the City of Hamburg, land availability is limited andpotential land use conflicts are high. As a consequence, hinterlandcommunities more willing to accept the development of logisticsareas are competing to attract new logistics companies, resultingin traffic-intensive developments in hinterland areas. In the widerHamburg region, many sites are currently considered for thedevelopment of new logistics areas, some reaching sizes of up to100 ha. Because the region spans three German states and 14administrative districts, there is no coordinated regional planningfor industrial and commercial areas.

Fig. 1 gives an overview of the region, its main transportcorridors and potential logistics development sites. In addition,the location of the industrial sites, where traffic was counted (seeSection 2.2), and the scenarios included in the traffic impactassessment (see Section 2.3) are highlighted.

Applying the results of two surveys (see Section 2.2) as inputvalues for a traffic impact assessment, different logistics land usedevelopment scenarios are assessed in order to answer thefollowing questions:

2 In the keywords truck is used but in the text, the British English term lorry is

used instead of truck.

� 3

How much traffic is generated by new logistics areas?

The companies were chosen based on the economic sector they belong to �

according to the NACE classification. The relevant sectors for logistics services are:

wholesale and retail trade; repair of motor vehicles, motorcycles and personal and

household goods and transport, storage and communication. The following sub-

groups according to the NACE code were selected:51.2Wholesale of agricultural

raw materials and live animals51.3Wholesale of food, beverages and tobacco51.4-

Wholesale of household goods51.5Wholesale of non-agricultural intermediate

products, waste and scrap51.8Wholesale of machinery, equipment and suppli-

es51.9Other wholesale60.1Transport via railways60.24Freight transport by road

61Water transport 62Air transport 63.1Cargo handling and storage 63.4Activities

of other transport agencies 64.1Post and courier activitiesThe selection of

economic sectors is based on Wrobel (2004). Additionally, some distribution

centres of retailers were included in the survey.4 For a detailed description of the company survey refer to Wagner (2008a).5 For a detailed description of the traffic counts refer to Wagner (2008b).

Can a strategic location of logistics areas reduce traffic andtraffic impacts?

2.2. Planning parameters of logistics and distribution facilities

Aiming at a deeper insight into the characteristics and tripgeneration of logistics-related land uses, two surveys wereconducted in the Hamburg region in 2007 and statisticallyevaluated regarding dependencies between trip generation andcompany characteristics. As a major result of these surveys,

general trip-generation rates could be calculated and differenttypes of logistics-related land use were identified and described.

A company survey was carried out in order to find out whichtypes of services are offered by logistics companies, what patternsof land use they show, how many lorry2 trips they generate andhow the trips are performed (vehicle type, time of day, etc.). In all860 companies of the transport and trade sector were contactedvia e-mail or phone, 64 of which (i.e. 7.5%) participated in thesurvey.3 Additionally, expert interviews were conducted in 20large companies. Only companies of the trade and transportsector with more than 20 and 10 employees, respectively, situatedin industrial or commercial areas were included. Overall, it wasfound that a wide range of logistics companies exists andconsequently there are highly varying requirements on spaceand infrastructure.4

In addition to the company survey, a traffic count wasperformed in two industrial areas (Hamburg Allermohe andValluhn-Gallin, see Fig. 1), where many logistics facilities arelocated. It was possible to show that the traffic volumes, theirdiurnal distribution and the use of different vehicle types areconnected to location and company characteristics in the differentareas.5

The trip generation of Hamburg Allermohe, a densely devel-oped industrial area close to Hamburg containing many regionaltransfer depots and regional and national trade distributioncentres, is about 110 daily lorry trips per hectare of developedreal estate. The trip generation of the industrial area Valluhn-Gallin located in a rural area containing some large distributionfacilities is only 10 daily lorry trips per hectare developed.

The different characteristics of the areas are also reflected inthe distribution of trips by vehicle type. In both cases, the share ofheavy goods vehicles of total traffic volumes was about 20%. Theshare of smaller lorries and vans added up to almost 25% inHamburg Allermohe and only 10% in Valluhn-Gallin. The remain-ing traffic volumes were car traffic.

For using trip-generation rates from empirical analyses toestimate traffic impacts from new site developments, Hoopergives several recommendations (refer to Hooper and Institute ofTransportation Engineers, 1998):

Regression equations should be used if the data plot containsmore than 20 data points or the R2 is at least 0.75 and thestandard deviation is less than or equal to 110% of the weightedaverage rate.

Weighted average rates should be preferred if at least threedata points are available and the standard deviation is less than orequal to 110% of the weighted average rate.

If only a few data points are available (less than three) or landuse types other than the ones provided are needed, it isrecommended that local data are collected.

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Fig. 1. Map of the Hamburg case study region. Source: author.

T. Wagner / Transport Policy 17 (2010) 224–229226

Fig. 2 illustrates the data plots and R2 of the correlationbetween lorry trip generation and number of employees derivedfrom the company survey. For both transport and trade-relatedlogistics service providers R2 is below 0.75. Besides the number ofemployees, plot size, floor space and handling floor space weretested as independent variables, but produced a far lower R2.

Table 1 summarises the average rates, weighthed average ratesand standard deviations of lorry trips per employee and per hectareas well as employees per hectare. Interpreting and using theserates, it has to be considered that the land use types analysed here,namely trade and transport-related logistics companies, are ratherdiverse, which is reflected in high standard deviations. The figuresare based, however, on a representative mixture of logisticscompanies and thus the planning parameters in this table areperceived as sufficiently exact for a rough estimation of trafficimpacts at an early planning stage.

Furthermore, the comparison with other sources and theresults of the traffic counts mentioned above shows that allderived trip-generation rates are more or less in the same range. Adirect comparison is, however, not possible due to differences inthe reference land use. Bosserhoff (2000, p. 43), whose work is themajor German source for trip-generation estimates, suggests10–15 daily lorry trips per hectare developed real estate for

transport-related land use and 40–90 daily lorry trips per hectareof developed land dedicated to hauliers and logistics centres. Asdaily lorry trip-generation rates per employee, he suggests 2–4 forstorage facilities and 2–9 for shippers’ facilities.

To get an impression of the lorry traffic intensity of logistics-related land use, it can be compared to lorry trip-generation ratesof other land use types. Bosserhoff (2000, p. 42) states that anindustrial park generates 0.6–0.8 daily lorry trips per employee or10–12 daily lorry trips per hectare developed land. Commercialland uses—except for wholesalers—generate up to 2 daily lorrytrips per employee. Office-type land uses have a low lorry trip-generation rate of 0.1 daily lorry trips per employee.

2.3. Traffic impact assessment—method and assumptions

The planning parameters presented in Table 1 are a prerequi-site for the traffic impact assessment (TIA) of new site develop-ments for logistics. Based on the general trip-generation rates,different spatial logistics site development options in the Ham-burg region were evaluated.

The starting point for traffic impact assessment is the definitionof the project or development paths considered and the estimationof number of employees expected. Two spatial options (scenarios)

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0

50

100

150

200

250

300

0Employees

Dai

ly lo

rry

trips

TRADE related logistics companies (n=21)

0

100

200

300

400

500

600

0Employees

Dai

ly lo

rry

trips

TRANSPORT related logistics companies (n=35)

100 200 300 400

R2 = 0.69 R2 = 0.54

50 100 150 200 250

Fig. 2. Data plots of lorry trip generation by number of employees. Source: own analysis based on a company survey in the Hamburg region in 2007.

Table 1Employee rates and lorry trip-generation rates of logistics companies.

Planning parameter Relation of logisticscompanies to land-use type

Average Weighted average

Standard deviation(% of weighted average)

Daily lorry trips per employee Transport (n=35) 2.9 1.8 2.8 (150%)

Trade (n=22) 1.4 1.4 1.2 (89%)

Daily lorry trips per hectare Transport (n=31) 117 56 130 (231%)

Trade (n=19) 63 39 56 (143%)

Employees per hectare Transport (n=32) 54 31 48 (155%)

Trade (n=20) 58 29 53 (183%)

Source: own analysis based on a company survey in the Hamburg region in 2007.

T. Wagner / Transport Policy 17 (2010) 224–229 227

for the development of 210 ha of new logistics space are evaluated.Scenario A defines the more realistic option where severalpotential sites close to the major highways in the hinterland ofHamburg are developed. Scenario B bundles the 210 ha into acentrally located and well-connected freight village with anintegrated rail transhipment terminal. This opens up the possibi-lity of reducing trip generation by shifting goods traffic from roadto rail, reducing goods traffic through the cooperation of logisticscompanies and shifting commuter traffic from road to publictransport. Since the trip-reduction potential of freight villages isonly of a theoretical nature, two sub-scenarios are looked at: tripreduction is achieved (scenario B+) or not achieved (scenario B�).

Based on the number of employees, daily vehicle movementsand their split between long and short haul and according tovehicle types can be estimated. Commuter trips can also becalculated based on assumptions regarding the share of personalmotorised travel (60–100%), which depends on the site accessi-bility for non-motorised and public transport.

In order to estimate vehicle kilometres travelled, a study areathat covers a region of less than 100 km distance to the Hamburgcity centre and respective traffic zones was defined. The totalnumber of trips is then distributed according to origin–destina-tion matrices derived from the company survey as well ascommuter statistics and multiplied with distance matricesgenerated with the network analyst of ArcGIS 9.2. In this step ofthe calculation, it has to be considered that not every incomingand outgoing trip actually carries goods. Sometimes, empty lorriesenter or leave the logistics centres. This is done by applying afactor for loaded lorries (estimated from expert interviews) andassigning a constant distance of 30 km to empty lorry trips.

Based on trips and vehicle kilometres generated within thestudy area, regional traffic impacts are calculated from standar-dised cost values (taken from Arnold, 2004: 834 for lorry operation

costs; from Maibach and Schreyer, 2007: 57; 84 for air pollutionand climate change) and local traffic impacts are discussed.

The different spatial scenarios and the study area are depictedin Fig. 1 (see Section 2.1). The planning parameters used andassumptions made regarding trip distribution are summarised inTable 2.

3. Results and discussion

3.1. Traffic impacts of the development scenarios

Depending on the scenario, 210 ha new logistics-related landuses generate 8900–10,100 lorry trips and 6900–10,600 car tripsper day. Within the study area 485,000–658,000 lorry kilometresand 185,000–329,000 car kilometres are generated per day. Thisleads to 4100–5700 Euros additional external cost from airpollution and 900–1200 Euros additional external costs fromclimate change per day.

The comparative illustration of the results in Fig. 3 shows thatscenario B� produces less regional traffic impacts and lorryoperation costs than scenario A, due to the good location of thefreight village. Further reduction can be achieved if modal shift oflong-haul goods traffic from road to rail, a reduction of lorry tripsthrough company cooperation and modal shift of commutertraffic through the provision of good public transport access areactually realised in the freight village (scenario B+). However,whereas regional traffic impacts can be reduced throughcolocating all logistics service providers in a suitably locatedfreight village, local traffic impacts from incoming and outgoinglorries are extremely high due to their spatial concentration.

As Fig. 4 illustrates, location plays an important role for theamount of lorry kilometres generated. This is particularly true, if a

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Table 2Planning parameters and assumptions for the traffic impact assessment.

Comparison of regional spatial development paths

Site characteristicsArea considered 210 ha

Logistics-related land use and its share of site development Sector 1 (50%) Sector 2 (50%)

Short description of sector/type Transport related Trade related

Employees per hectare 31 29

Daily trip generationLorry trips per employee 1.8 1.4

LHTa RTb LHT RT

Share of LHT/RT (%) 45 55 50 50

Reduction through modal shift (%)n 10 – 20 –

Reduction through cooperation (%)n – 10 – 10

Factor for loaded lorries 1/1.5

Commuter trips per employeenn 2.5

Average presence (% of employees)nn 80

Share of personal MTc (%)nn 60–100

Persons per carnn 1.1

Lorry trip distribution (aggregated level)Hamburg city (%) – 25 – 39

Hamburg city—port (%) 3 15 2 4

Hamburg city—RTTd (%) – 3 – 3

Metropolitan area (% – 42 – 44

North (%) 19 5 25 4

East (%) 20 3 20 4

South west (%) 19 3 18 1

South (%) 39 4 35 1

Sources: nSonntag and Meimbresse (1999), nnBosserhoff (2000). Others: author.

a LHT=long haul traffic.b RT=regional traffic.c MT=motorised traffic.d RTT=rail transhipment terminal.

0.7

1.2

1.3

0.9

1.2

1.1

1.0

Lorry trips[10,000]

Car trips [10,000]

Lorry km[500,000]

Car km [500,000]

Air pollution[2,000 €]

Climate change[10,000 €]

Lorry operation[1,000,000 €]

Scenario A

Scenario B-

Scenario B+

Fig. 3. Daily traffic impacts of the development of 210 ha logistics-related land

use. Source: author

80

90

100

110

120

130

0Distance to Hamburg city centre [km]

Lorr

y km

per

em

ploy

ee a

nd d

ay

10 20 30 40 50 60

Fig. 4. Lorry kilometre generated depending on site location. Source: author

T. Wagner / Transport Policy 17 (2010) 224–229228

consistent mixture of logistics-related land use types is looked at (byapplying the average lorry trip-generation rate). A comparison ofspecific logistics facilities like transfer depots, distribution centres,

warehouses, etc. results in different findings, because trip distributionis variable. However, the tendency is still that lorry kilometresgenerated increase with increasing distance to the city centre.

3.2. Potential role of traffic impact assessment in regional planning

Up to now, traffic impacts are not usually considered at aregional planning level. There has also been a lack of regional land-use policy—at least in Germany. Land-use planning aiming at

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location decisions that reduce regional traffic (impacts) has onlyrecently been becoming the focus of planning policy. There are twoobstacles in particular for logistics land-use planning minimisingregional traffic (impacts): the distribution of planning power andeconomic competition between local authorities on the one handand the lack of specific planning parameters for logistics land use (asthose generated in the surveys described in Section 2.2) on the other.

Such planning parameters enable an early comparison ofdifferent local and regional strategies for new logistics develop-ments. Not only different sites but also different types of logisticsland uses, like transport-related and trade-related logistics serviceproviders, can be compared. Whereas the trip-generation ratesderived in this study might be transferred to other monocentricregions, trip distribution will differ according to the spatialstructure of a region that determines trip sources, ends andchaining. However, the statistical analyses of the survey revealedthat trip generation of the two general logistics-related land-usecategories shows a broad range. As a consequence, planningparameters for specific logistics facilities like transfer depots,regional distribution centres, national distribution centres ormulti-user warehouses should also be made available. Such anapproach is presented in Wagner, 2009.

Given the often short-term contracts of logistics serviceproviders and shipping companies, considering the variability oftrip generation of different logistics facilities is crucial. Trafficimpact assessments should not be based on a (sometimes alreadyknown) first user but also consider potential future users. Thisparticularly applies for smaller site developments. The trafficimpacts of larger developments like freight villages, in contrast,will certainly be more constant in time, because the traffic impactsof many different (changing) logistics facilities will even out.

Traffic impact assessment based on specific planning para-meters for logistics land use provides a planning tool forcommunities to estimate local impacts of different sectoral sitedevelopments and a decision support tool for regional authoritiesaiming at spatial/sectoral development that reduces regionaltraffic impact. Since traffic impact is only one decision factor forsite selection and development, the integration of traffic impactassessments as presented here into a broader cost benefit analysiswill provide a more holistic decision support tool.

If local authorities can agree on a regional strategy for thelocation of new logistics developments that minimises regionaltraffic impacts, the strategy needs to be implemented. Differentplanning instruments might support such an implementation:

�

An existing common land-use strategy for the communities ina region can support the implementation of a specific regionallocation strategy for logistics-related developments; � Colocation of logistics developments in a suitably sited and

accessible freight village should reduce the regional traffic impacts(see Section 3.1). However, this also generates high local trafficimpacts, which need to be carefully assessed and addressed.

� A location policy that considers the expected traffic of a potential

usage can be a powerful planning tool. In Switzerland, forexample, sites are identified and defined in the regional planthat are generally suitable for high trip-generating uses. For eachsite either the trip generation or the size of the development (i.e.floor space) is restricted (BAFU und ARE, 2006).

4. Conclusion

In growth regions like Hamburg, land availability is limitedand potential land use conflicts are high. As a consequence,

demand for new logistics areas is often satisfied in hinterlandcommunities. This form of development complicates both trafficand space efficiencies.

Both location and type of logistics-related use of newdevelopments determine their traffic impacts, which are highcompared with other land uses. In order to better integratelogistics developments into urban and regional planning, sitecharacteristics and traffic patterns of logistics-related land useswere investigated in the Hamburg region. From the empiricalanalyses, average trip-generation rates were derived for transportand trade-related logistics companies and standard types oflogistics-related land uses have been defined and described. Suchplanning parameters can be used as input values for comparativetraffic impact assessment. However, because of the high diversityof logistics companies, further surveys on a larger scale arerecommended. A methodological improvement could be theintegration of trip-generation and trip-distribution estimationinto regional land use and transport models. This will, however,not be straightforward, because the level of detail of modelledland use types is usually not sufficient to include different types oflogistics-related land uses. In addition, in most regions no suchmodels are actually maintained.

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