Linnaeus University DissertationsNo 281/2017

Uniben Yao Ayikoe Tettey

Primary energy use of residential buildings - implications of materials, modelling and design approaches

linnaeus university press

Lnu.seisbn: 978-91-88357-66-3

Primary energy use of residential buildings

- implications of m

aterials, modelling and design approaches

Uniben Yao A

yikoe Tettey

[framsida]Linnaeus University Dissertations

Linnaeus University Press

[rygg]

[baksida]

Lnu.seISBN:

Primary energy use of residential buildings - implications of materials, modelling and design

approaches

Linnaeus University Dissertations No 281/2017

PRIMARY ENERGY USE OF RESIDENTIAL

BUILDINGS - IMPLICATIONS OF

MATERIALS, MODELLING AND DESIGN

APPROACHES

UNIBEN YAO AYIKOE TETTEY

LINNAEUS UNIVERSITY PRESS

Linnaeus University Dissertations No 281/2017

PRIMARY ENERGY USE OF RESIDENTIAL

BUILDINGS - IMPLICATIONS OF

MATERIALS, MODELLING AND DESIGN

APPROACHES

UNIBEN YAO AYIKOE TETTEY

LINNAEUS UNIVERSITY PRESS

i

Abstract Buildings can play an essential role in the transition to a sustainable society. Different strategies, including improved energy efficiency in buildings, substitution of carbon intensive materials and fuels, efficient energy supply among others can be employed for this purpose. In this thesis, the implications of different insulation materials, modelling and design strategies on primary energy use of residential buildings are studied using life cycle and system perspective. Specifically, the effects of different insulation materials on production primary energy and CO2 emission of buildings with different energy performance are analysed. The results show that application of extra insulation materials to building envelope components reduces the operating primary energy use but more primary energy is required for the insulation material production. This also slightly increases the CO2 emissions from material production. The increases in primary energy use and CO2 emissions are mainly due to the variations in the quantities, types and manufacturing processes of the insulation materials. Thus, choice of renewable based materials with energy efficient manufacturing is important to reduce primary energy use and GHG emissions for building material production.

Uncertainties related to building modelling input parameters and assumptions and how they influence energy balance calculations of residential buildings are explored. The implications on energy savings of different energy efficiency measures are also studied. The results show that input data and assumptions used for energy balance simulations of buildings vary widely in the Swedish context giving significant differences in calculated energy demand for buildings. Among the considered parameters, indoor air temperature, internal heat gains and efficiency of ventilation heat recovery (VHR) have significant impacts on the simulated building energy performance as well as on the energy efficiency measures. The impact of parameter interactions on calculated space heating of buildings is rather small but increases with more parameter combinations and more energy efficient buildings. Detailed energy characterisation of household equipment and technical installations used in a building is essential to accurately calculate the energy demand, particularly for a low energy building.

Primary energy use of residential buildings - implications of materials, modelling and design approaches Doctoral dissertation, Department of Built Environment and Energy Technology, Linnaeus University, Växjö, 2017 ISBN: 978-91-88357-66-3 Published by: Linnaeus University Press, 351 95 Växjö Printed by: DanagårdLiTHO AB, 2017

i

Abstract Buildings can play an essential role in the transition to a sustainable society. Different strategies, including improved energy efficiency in buildings, substitution of carbon intensive materials and fuels, efficient energy supply among others can be employed for this purpose. In this thesis, the implications of different insulation materials, modelling and design strategies on primary energy use of residential buildings are studied using life cycle and system perspective. Specifically, the effects of different insulation materials on production primary energy and CO2 emission of buildings with different energy performance are analysed. The results show that application of extra insulation materials to building envelope components reduces the operating primary energy use but more primary energy is required for the insulation material production. This also slightly increases the CO2 emissions from material production. The increases in primary energy use and CO2 emissions are mainly due to the variations in the quantities, types and manufacturing processes of the insulation materials. Thus, choice of renewable based materials with energy efficient manufacturing is important to reduce primary energy use and GHG emissions for building material production.

Uncertainties related to building modelling input parameters and assumptions and how they influence energy balance calculations of residential buildings are explored. The implications on energy savings of different energy efficiency measures are also studied. The results show that input data and assumptions used for energy balance simulations of buildings vary widely in the Swedish context giving significant differences in calculated energy demand for buildings. Among the considered parameters, indoor air temperature, internal heat gains and efficiency of ventilation heat recovery (VHR) have significant impacts on the simulated building energy performance as well as on the energy efficiency measures. The impact of parameter interactions on calculated space heating of buildings is rather small but increases with more parameter combinations and more energy efficient buildings. Detailed energy characterisation of household equipment and technical installations used in a building is essential to accurately calculate the energy demand, particularly for a low energy building.

Primary energy use of residential buildings - implications of materials, modelling and design approaches Doctoral dissertation, Department of Built Environment and Energy Technology, Linnaeus University, Växjö, 2017 ISBN: 978-91-88357-66-3 Published by: Linnaeus University Press, 351 95 Växjö Printed by: DanagårdLiTHO AB, 2017

iii

Preface This thesis is based on research work conducted within the Sustainable Built Environment Research group at the Department of Built Environment and Energy Technology, Linnaeus University, Sweden. Financial support from the Center for Research and Development in Ronneby (Cefur), Växjö Municipality, Växjöbostäder, Växjö Energi AB and Swedish Energy Agency is gratefully acknowledged.

I sincerely express my gratitude to my main supervisor, Prof. Leif Gustavsson, and to my assistant supervisor, Docent Ambrose Dodoo for their guidance, advice and support, which were not only limited to this work. Thank you, Prof. Leif Gustavsson for the opportunity to embark on this journey.

I would like to say a big thank you to staff and colleagues in different departments within the Faculty of Technology for their cooperation and assistance. You have contributed in diverse ways to this journey. Fond memories of the “fika” times will, specially stay with me.

I am greatly indebted to my father for inspiring me to pursue knowledge (I know you would have been glad to witness this - RIP). I am equally indebted to my dear mother, brothers, uncles, aunties and friends for their prayers, support and encouragement.

Thank you so much, Miriam – you are indeed the love of my life. I am infinitely grateful for all the sacrifices you continue to make.

Above all, glory and honour to God, our heavenly Father for His amazing love, grace through Jesus Christ and fellowship of the Holy Spirit.

Uniben Yao Ayikoe Tettey Växjö, February 2017

ii

The design and construction of new buildings present many possibilities to minimise both heating and cooling demands over the lifecycle of buildings, and also in the context of climate change. Various design strategies and measures are analysed for buildings with different energy performance under different climate scenarios. These include household equipment and technical installations based on best available technology, bypassing the VHR unit, solar shading of windows, combinations of window u- and g-values, different proportions of glazed window areas and façade orientations and mechanical cooling. The results show that space heating and cooling demands vary significantly with the energy performance of buildings as well as climate scenarios. Space heating demand decreases while space cooling demand and the risk of overheating increase considerably with warmer climate. The space cooling demand and overheating risk are more significant for buildings with higher energy performance. Significant reductions are achieved in the operation final energy demands and overheating is avoided or greatly reduced when different design strategies and measures are implemented cumulatively under different climate change scenarios.

The primary energy efficiency of heat supply systems depends on the heat production technology and type of fuel use. Analysis of the interaction between different design strategies and heat supply options shows that the combination of design strategies giving the lowest primary energy use for space heating and cooling varies between heat supply from district heating with combined heat and power (CHP) and heat only boilers (HOB). The primary energy use for space heating is significantly lower when the heat supply is from CHP rather than HOB. Operation primary energy use is significantly reduced with slight increase in production primary energy when the design strategies are implemented. The results suggest that significant primary energy reductions are achievable under climate change, if new buildings are designed with appropriate strategies. Keywords: primary energy use, material production, simulation, input parameters, design strategies, climate change, overheating, residential buildings

iii

Preface This thesis is based on research work conducted within the Sustainable Built Environment Research group at the Department of Built Environment and Energy Technology, Linnaeus University, Sweden. Financial support from the Center for Research and Development in Ronneby (Cefur), Växjö Municipality, Växjöbostäder, Växjö Energi AB and Swedish Energy Agency is gratefully acknowledged.

I sincerely express my gratitude to my main supervisor, Prof. Leif Gustavsson, and to my assistant supervisor, Docent Ambrose Dodoo for their guidance, advice and support, which were not only limited to this work. Thank you, Prof. Leif Gustavsson for the opportunity to embark on this journey.

I would like to say a big thank you to staff and colleagues in different departments within the Faculty of Technology for their cooperation and assistance. You have contributed in diverse ways to this journey. Fond memories of the “fika” times will, specially stay with me.

I am greatly indebted to my father for inspiring me to pursue knowledge (I know you would have been glad to witness this - RIP). I am equally indebted to my dear mother, brothers, uncles, aunties and friends for their prayers, support and encouragement.

Thank you so much, Miriam – you are indeed the love of my life. I am infinitely grateful for all the sacrifices you continue to make.

Above all, glory and honour to God, our heavenly Father for His amazing love, grace through Jesus Christ and fellowship of the Holy Spirit.

Uniben Yao Ayikoe Tettey Växjö, February 2017

ii

The design and construction of new buildings present many possibilities to minimise both heating and cooling demands over the lifecycle of buildings, and also in the context of climate change. Various design strategies and measures are analysed for buildings with different energy performance under different climate scenarios. These include household equipment and technical installations based on best available technology, bypassing the VHR unit, solar shading of windows, combinations of window u- and g-values, different proportions of glazed window areas and façade orientations and mechanical cooling. The results show that space heating and cooling demands vary significantly with the energy performance of buildings as well as climate scenarios. Space heating demand decreases while space cooling demand and the risk of overheating increase considerably with warmer climate. The space cooling demand and overheating risk are more significant for buildings with higher energy performance. Significant reductions are achieved in the operation final energy demands and overheating is avoided or greatly reduced when different design strategies and measures are implemented cumulatively under different climate change scenarios.

The primary energy efficiency of heat supply systems depends on the heat production technology and type of fuel use. Analysis of the interaction between different design strategies and heat supply options shows that the combination of design strategies giving the lowest primary energy use for space heating and cooling varies between heat supply from district heating with combined heat and power (CHP) and heat only boilers (HOB). The primary energy use for space heating is significantly lower when the heat supply is from CHP rather than HOB. Operation primary energy use is significantly reduced with slight increase in production primary energy when the design strategies are implemented. The results suggest that significant primary energy reductions are achievable under climate change, if new buildings are designed with appropriate strategies. Keywords: primary energy use, material production, simulation, input parameters, design strategies, climate change, overheating, residential buildings

v

List of Papers This doctoral thesis is based on the following papers:

I. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Effects of different

insulation materials on primary energy and CO2 emission of a multi-storey residential building. Energy and Buildings, 2014. 82(0): p. 369-377.

II. Dodoo, A., Tettey, U.Y.A., Gustavsson, L. On input parameters,

methods and assumptions for energy balance and retrofit analyses for residential buildings. Energy and Buildings, 2017. 137: p. 76-89.

III. Dodoo, A., Tettey, U.Y.A., Gustavsson, L. Influence of simulation

assumptions and input parameters on energy balance calculations of residential buildings. Energy (In press).

IV. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Primary energy

implications of different design strategies for an apartment building. Energy, 2016. 104: p. 132-148.

V. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Energy use implications of

different design strategies for multi-storey residential buildings under future climates. Journal article manuscript.

v

List of Papers This doctoral thesis is based on the following papers:

I. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Effects of different

insulation materials on primary energy and CO2 emission of a multi-storey residential building. Energy and Buildings, 2014. 82(0): p. 369-377.

II. Dodoo, A., Tettey, U.Y.A., Gustavsson, L. On input parameters,

methods and assumptions for energy balance and retrofit analyses for residential buildings. Energy and Buildings, 2017. 137: p. 76-89.

III. Dodoo, A., Tettey, U.Y.A., Gustavsson, L. Influence of simulation

assumptions and input parameters on energy balance calculations of residential buildings. Energy (In press).

IV. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Primary energy

implications of different design strategies for an apartment building. Energy, 2016. 104: p. 132-148.

V. Tettey, U.Y.A., Dodoo, A., Gustavsson, L. Energy use implications of

different design strategies for multi-storey residential buildings under future climates. Journal article manuscript.

vii

Table of contents Abstract ............................................................................................................ i Preface ............................................................................................................ iii List of Papers .................................................................................................. v Table of contents ........................................................................................... vii

1. Introduction ............................................................................................... 1 1.1. Background .......................................................................................... 1 1.2. Building energy use and climate impact .............................................. 3 1.3. Literature review .................................................................................. 4 1.4. Knowledge gaps................................................................................... 8 1.5. Aim and objective ................................................................................ 9

2. Methodological framework and approaches ............................................ 11 2.1. Life cycle perspective ........................................................................ 11 2.2. Energy system analysis ...................................................................... 12 2.3. Energy supply systems ...................................................................... 13 2.4. Allocation in CHP production ........................................................... 14 2.5. System boundaries and functional unit .............................................. 15 2.6. Analysed parameters .......................................................................... 15 2.7. Studied buildings ............................................................................... 16

2.7.1. Wälludden building ................................................................... 16 2.7.2. Lindvägen building .................................................................... 16 2.7.3. Täppan building ......................................................................... 17

2.8. Primary energy analysis and CO2 emission ....................................... 18 2.8.1 Building materials production primary energy .......................... 18 2.8.2 Building materials production CO2 emission ............................ 19 2.8.3 Final and primary energy use for building operation ................ 20

3. Results ..................................................................................................... 23 3.1. Production primary energy use and CO2 emission of insulation materials ........................................................................................................ 23 3.2. Parameters and assumptions for energy balance calculations............ 26 3.3. Space heating and cooling demand under different design strategies 35 3.4. Space heating and cooling demand under climate change ................. 37 3.5. Operation primary energy use under different design strategies and heat supply options........................................................................................ 41

vii

Table of contents Abstract ............................................................................................................ i Preface ............................................................................................................ iii List of Papers .................................................................................................. v Table of contents ........................................................................................... vii

1. Introduction ............................................................................................... 1 1.1. Background .......................................................................................... 1 1.2. Building energy use and climate impact .............................................. 3 1.3. Literature review .................................................................................. 4 1.4. Knowledge gaps................................................................................... 8 1.5. Aim and objective ................................................................................ 9

2. Methodological framework and approaches ............................................ 11 2.1. Life cycle perspective ........................................................................ 11 2.2. Energy system analysis ...................................................................... 12 2.3. Energy supply systems ...................................................................... 13 2.4. Allocation in CHP production ........................................................... 14 2.5. System boundaries and functional unit .............................................. 15 2.6. Analysed parameters .......................................................................... 15 2.7. Studied buildings ............................................................................... 16

2.7.1. Wälludden building ................................................................... 16 2.7.2. Lindvägen building .................................................................... 16 2.7.3. Täppan building ......................................................................... 17

2.8. Primary energy analysis and CO2 emission ....................................... 18 2.8.1 Building materials production primary energy .......................... 18 2.8.2 Building materials production CO2 emission ............................ 19 2.8.3 Final and primary energy use for building operation ................ 20

3. Results ..................................................................................................... 23 3.1. Production primary energy use and CO2 emission of insulation materials ........................................................................................................ 23 3.2. Parameters and assumptions for energy balance calculations............ 26 3.3. Space heating and cooling demand under different design strategies 35 3.4. Space heating and cooling demand under climate change ................. 37 3.5. Operation primary energy use under different design strategies and heat supply options........................................................................................ 41

1

1. Introduction

1.1. Background The construction and building sectors are material and energy intensive. Globally, civil works and building construction activities account for 60% of the total raw materials extractions and buildings represent about 40% of these [1]. The extraction and use of these natural resources present many challenges, including emission of greenhouse gases (GHGs), environmental degradation and energy security among others. World population and economic growth continue to put increased pressure on natural resources and the environment [2]. Different types of fuels accounted for about 96% of the global primary energy use in 2014 and fossil fuels contributed about 81% with oil, coal and natural gas accounting for 31%, 29% and 21%, respectively [3]. The global primary energy supply (including international aviation and international marine bunkers) between 1971 and 2014 is shown in Figure 1, by fuel types. Despite a significant contribution from renewable fuels to global energy supply, still fossil fuels dominate global primary energy use at 79% and 74% under the International Energy Agency’s (IEA) current and new policies scenarios, respectively by 2040 [4].

The energy sector is a major contributor to global GHG emissions, accounting for around two-thirds of total GHG emissions [5]. Rising population and economic growth are suggested as main drivers of increases in anthropogenic CO2 emissions [6]. Atmospheric concentration of CO2 emissions has increased by 40% since pre-industrial times, mainly from fossil fuel emissions [7]. In 2014, coal, oil and natural gas accounted for about 46%, 34% and 20%, respectively, of the total CO2 emission from fuel combustion globally [3].

viii

3.6. Operation primary energy use under different design strategies and climate scenarios ........................................................................................... 44

4. Discussion and Conclusions .................................................................... 45 4.1. Primary energy use and CO2 emission for materials production ....... 45 4.2. Input parameter values and assumptions ........................................... 46 4.3. Climate scenarios and design strategies ............................................ 47 4.4. Primary energy use for building production and operation ............... 48 4.5. Uncertainties ...................................................................................... 49

5. Future work ............................................................................................. 51 References ..................................................................................................... 53 Appended papers ........................................................................................... 61

1

1. Introduction

1.1. Background The construction and building sectors are material and energy intensive. Globally, civil works and building construction activities account for 60% of the total raw materials extractions and buildings represent about 40% of these [1]. The extraction and use of these natural resources present many challenges, including emission of greenhouse gases (GHGs), environmental degradation and energy security among others. World population and economic growth continue to put increased pressure on natural resources and the environment [2]. Different types of fuels accounted for about 96% of the global primary energy use in 2014 and fossil fuels contributed about 81% with oil, coal and natural gas accounting for 31%, 29% and 21%, respectively [3]. The global primary energy supply (including international aviation and international marine bunkers) between 1971 and 2014 is shown in Figure 1, by fuel types. Despite a significant contribution from renewable fuels to global energy supply, still fossil fuels dominate global primary energy use at 79% and 74% under the International Energy Agency’s (IEA) current and new policies scenarios, respectively by 2040 [4].

The energy sector is a major contributor to global GHG emissions, accounting for around two-thirds of total GHG emissions [5]. Rising population and economic growth are suggested as main drivers of increases in anthropogenic CO2 emissions [6]. Atmospheric concentration of CO2 emissions has increased by 40% since pre-industrial times, mainly from fossil fuel emissions [7]. In 2014, coal, oil and natural gas accounted for about 46%, 34% and 20%, respectively, of the total CO2 emission from fuel combustion globally [3].

viii

3.6. Operation primary energy use under different design strategies and climate scenarios ........................................................................................... 44

4. Discussion and Conclusions .................................................................... 45 4.1. Primary energy use and CO2 emission for materials production ....... 45 4.2. Input parameter values and assumptions ........................................... 46 4.3. Climate scenarios and design strategies ............................................ 47 4.4. Primary energy use for building production and operation ............... 48 4.5. Uncertainties ...................................................................................... 49

5. Future work ............................................................................................. 51 References ..................................................................................................... 53 Appended papers ........................................................................................... 61

3

change. At the recently concluded Conference of Parties (COP21) in Paris, renewed commitments were reached to keep global warming below 2°C above pre-industrial levels while continued efforts are pursued to limit it to 1.5°C [8]. Rogelj et al. [10] assessed national plans submitted by countries to address the climate change challenge beyond 2020 in line with the Paris agreement. They suggest that the national plans collectively lower GHG emissions compared to current policies but still fall short of achieving the Paris target. More efficient use of energy and material resources, as well as the minimisation of energy-related environmental impacts is an essential part of efforts towards a sustainable society.

1.2. Building energy use and climate impact Buildings can play a crucial role in the transition to a sustainable society as their construction, operation and disposal are associated with various energy- and material-related sustainability problems. GHG emissions from the building sector more than doubled in 2010 compared to 1970 levels, accounting for 19% of global GHG emissions [6]. Most building related GHG emissions are indirect CO2 emissions from electricity and heat generation (Figure 2) [6]. The building sector’s final energy use was about 32% of the global final energy use in 2010, corresponding to over 30% of related CO2 emissions [6]. Both in the European Union (EU-28) and in Sweden, about 38% of the total final energy use was attributable to the residential and service sectors in 2014 [11, 12]. Space heating currently dominates the final operation energy use of the residential building stock in most EU countries [13]. In Sweden, for example, buildings accounted for about 90% of the final energy use in the residential and service sectors in 2014 with about 55% of this being for space heating and hot water supply [14]. Climate change may influence energy demands in buildings, with greater needs for cooling especially in highly energy efficient buildings [6, 15]. Cooling demand is expected to increase by about 150% globally by 2050 [16].

2

Figure 1. Global primary energy supply (EJ) by fuel type between 1971 and 2014. (Adapted from [3]). 1Includes peat and oil shale. 2Includes geothermal, solar, wind, heat, etc.

Several studies have emphasised the need to stabilise the concentration of

GHGs in the atmosphere in order to avoid dangerous anthropogenic interference with the global climate system that may lead to potentially irreversible negative impacts [7, 8]. Negative impacts of climate change such as rising sea levels, heat waves and droughts, extreme weather patterns, food shortage and air pollution among others may pose significant threats to human life and ecosystems. Several scenario analyses suggest that the transition to a sustainable society requires radical shifts in the world’s energy supply systems through large scale substitution of fossil fuels with renewable energy supply, introduction of low carbon technologies and increased energy efficiency across different sectors [5, 6].

Changes in the global climate system have been unprecedented over recent decades [7] and have been attributed to different factors including increasing concentration of GHGs in the atmosphere, primarily due to anthropogenic activities. The Intergovernmental Panel on Climate Change (IPCC) asserts with high certainty, that unprecedented concentration of GHGs in the atmosphere is the main cause of global warming and other negative climate change impacts [9]. Global mean surface temperatures have increased between 0.65 - 1.06°C over the period 1880–2012 and are projected to further increase between 0.3 - 4.8°C by 2100 compared to 1986-2005 levels, depending on different climate scenarios [7]. Considerable efforts have been made over the past few decades to avert the potential negative consequences of climate

3

change. At the recently concluded Conference of Parties (COP21) in Paris, renewed commitments were reached to keep global warming below 2°C above pre-industrial levels while continued efforts are pursued to limit it to 1.5°C [8]. Rogelj et al. [10] assessed national plans submitted by countries to address the climate change challenge beyond 2020 in line with the Paris agreement. They suggest that the national plans collectively lower GHG emissions compared to current policies but still fall short of achieving the Paris target. More efficient use of energy and material resources, as well as the minimisation of energy-related environmental impacts is an essential part of efforts towards a sustainable society.

1.2. Building energy use and climate impact Buildings can play a crucial role in the transition to a sustainable society as their construction, operation and disposal are associated with various energy- and material-related sustainability problems. GHG emissions from the building sector more than doubled in 2010 compared to 1970 levels, accounting for 19% of global GHG emissions [6]. Most building related GHG emissions are indirect CO2 emissions from electricity and heat generation (Figure 2) [6]. The building sector’s final energy use was about 32% of the global final energy use in 2010, corresponding to over 30% of related CO2 emissions [6]. Both in the European Union (EU-28) and in Sweden, about 38% of the total final energy use was attributable to the residential and service sectors in 2014 [11, 12]. Space heating currently dominates the final operation energy use of the residential building stock in most EU countries [13]. In Sweden, for example, buildings accounted for about 90% of the final energy use in the residential and service sectors in 2014 with about 55% of this being for space heating and hot water supply [14]. Climate change may influence energy demands in buildings, with greater needs for cooling especially in highly energy efficient buildings [6, 15]. Cooling demand is expected to increase by about 150% globally by 2050 [16].

2

Figure 1. Global primary energy supply (EJ) by fuel type between 1971 and 2014. (Adapted from [3]). 1Includes peat and oil shale. 2Includes geothermal, solar, wind, heat, etc.

Several studies have emphasised the need to stabilise the concentration of

GHGs in the atmosphere in order to avoid dangerous anthropogenic interference with the global climate system that may lead to potentially irreversible negative impacts [7, 8]. Negative impacts of climate change such as rising sea levels, heat waves and droughts, extreme weather patterns, food shortage and air pollution among others may pose significant threats to human life and ecosystems. Several scenario analyses suggest that the transition to a sustainable society requires radical shifts in the world’s energy supply systems through large scale substitution of fossil fuels with renewable energy supply, introduction of low carbon technologies and increased energy efficiency across different sectors [5, 6].

Changes in the global climate system have been unprecedented over recent decades [7] and have been attributed to different factors including increasing concentration of GHGs in the atmosphere, primarily due to anthropogenic activities. The Intergovernmental Panel on Climate Change (IPCC) asserts with high certainty, that unprecedented concentration of GHGs in the atmosphere is the main cause of global warming and other negative climate change impacts [9]. Global mean surface temperatures have increased between 0.65 - 1.06°C over the period 1880–2012 and are projected to further increase between 0.3 - 4.8°C by 2100 compared to 1986-2005 levels, depending on different climate scenarios [7]. Considerable efforts have been made over the past few decades to avert the potential negative consequences of climate

5

Various studies have explored different aspects of the energetic and climatic implications of buildings in different contexts. Life cycle assessments of conventional buildings indicate that the operation phase contributes largely to the total life cycle primary energy use and GHG emissions [19-21]. Building envelopes serve as a boundary between conditioned internal spaces and the outdoor climate and affect the space heating and cooling demands as well as comfort levels in buildings. Depending on the climate, about 33-50% of the global final energy use in the building sector is used for space heating and cooling [16]. The energy performance of envelope elements, including external walls, floors, roofs, ceilings, windows and doors is essential in estimating the heating and cooling energy requirement of buildings. Thus, efforts have mainly been towards reducing building operation energy use through improved airtightness and thermal insulation levels of envelope elements and by ventilation heat recovery (VHR). Insulation materials play an important role in improving the energy efficiency of both new and old existing buildings requiring renovation. In this regard, new innovative insulation materials and systems are emerging. A comprehensive review of traditional, state-of-the-art and future thermal insulation materials and solutions for buildings is presented in [22]. Most research on insulation materials have focused on their thermal properties and performance [23-28]. Some studies have analysed the cost, energy and environmental impacts of insulation materials in different climates. Ucar and Balo [29] and Ekici et al. [30] calculated optimal thicknesses and energy cost savings of different external wall insulation materials in four climate zones of Turkey. They considered different fuel types to meet heating and cooling demands. Their results showed that the optimal thicknesses and energy cost savings varied depending on cost of fuel, insulation material and climate zone. The above studies have mainly focused on thermal and economic benefits of insulation materials in the operation phase of buildings. Anastaselos et al. [31] proposed an integrated decision support tool to assess thermal insulation solutions for buildings over their life cycle. Audenaert et al. [32] performed a life cycle assessment of a low-energy apartment building using the Eco-indicator’99 method. They considered different exterior cladding and insulation materials in the building envelope components. They found that insulation materials have significant impact on the eco-score of the building due to their varying production energy requirements.

4

Figure 2. Direct and indirect emissions (from electricity and heat generation) for the building sector between 1970-2010 [6].

Building envelopes influence the space heating and cooling demands, as

well as comfort levels in buildings. Therefore, optimising building envelope designs to take advantage of the building’s local climate is important in achieving reduced energy use in the building sector. Globally, the building sector is expected to play a significant role to mitigate climate change and supplement efforts towards a sustainable society. The EU has committed itself to 80-95% reduction in building related GHG emissions by 2050 compared to 1990 levels, while the Swedish government aims to decrease specific energy use in buildings by 20% and 50% by 2020 and 2050, respectively, compared to 1995 levels [17, 18]. In line with these, regulations and policies promoting energy efficiency and deployment of renewable energy technologies in the building sector are promoted in several national and international contexts. These need to be further complemented with policies for resource efficiency to minimise the environmental implications of different construction and building materials. Effective strategies to achieve these targets should also encompass the whole building life cycle, including the production, renovation, operation and end-of-life as well as the interactions between them under both current and future climates.

1.3. Literature review Buildings form an integral part of efforts towards a sustainable future. The construction, operation and end-of-life activities of buildings are associated with a wide range of energy- and material-related issues.

5

Various studies have explored different aspects of the energetic and climatic implications of buildings in different contexts. Life cycle assessments of conventional buildings indicate that the operation phase contributes largely to the total life cycle primary energy use and GHG emissions [19-21]. Building envelopes serve as a boundary between conditioned internal spaces and the outdoor climate and affect the space heating and cooling demands as well as comfort levels in buildings. Depending on the climate, about 33-50% of the global final energy use in the building sector is used for space heating and cooling [16]. The energy performance of envelope elements, including external walls, floors, roofs, ceilings, windows and doors is essential in estimating the heating and cooling energy requirement of buildings. Thus, efforts have mainly been towards reducing building operation energy use through improved airtightness and thermal insulation levels of envelope elements and by ventilation heat recovery (VHR). Insulation materials play an important role in improving the energy efficiency of both new and old existing buildings requiring renovation. In this regard, new innovative insulation materials and systems are emerging. A comprehensive review of traditional, state-of-the-art and future thermal insulation materials and solutions for buildings is presented in [22]. Most research on insulation materials have focused on their thermal properties and performance [23-28]. Some studies have analysed the cost, energy and environmental impacts of insulation materials in different climates. Ucar and Balo [29] and Ekici et al. [30] calculated optimal thicknesses and energy cost savings of different external wall insulation materials in four climate zones of Turkey. They considered different fuel types to meet heating and cooling demands. Their results showed that the optimal thicknesses and energy cost savings varied depending on cost of fuel, insulation material and climate zone. The above studies have mainly focused on thermal and economic benefits of insulation materials in the operation phase of buildings. Anastaselos et al. [31] proposed an integrated decision support tool to assess thermal insulation solutions for buildings over their life cycle. Audenaert et al. [32] performed a life cycle assessment of a low-energy apartment building using the Eco-indicator’99 method. They considered different exterior cladding and insulation materials in the building envelope components. They found that insulation materials have significant impact on the eco-score of the building due to their varying production energy requirements.

4

Figure 2. Direct and indirect emissions (from electricity and heat generation) for the building sector between 1970-2010 [6].

Building envelopes influence the space heating and cooling demands, as

well as comfort levels in buildings. Therefore, optimising building envelope designs to take advantage of the building’s local climate is important in achieving reduced energy use in the building sector. Globally, the building sector is expected to play a significant role to mitigate climate change and supplement efforts towards a sustainable society. The EU has committed itself to 80-95% reduction in building related GHG emissions by 2050 compared to 1990 levels, while the Swedish government aims to decrease specific energy use in buildings by 20% and 50% by 2020 and 2050, respectively, compared to 1995 levels [17, 18]. In line with these, regulations and policies promoting energy efficiency and deployment of renewable energy technologies in the building sector are promoted in several national and international contexts. These need to be further complemented with policies for resource efficiency to minimise the environmental implications of different construction and building materials. Effective strategies to achieve these targets should also encompass the whole building life cycle, including the production, renovation, operation and end-of-life as well as the interactions between them under both current and future climates.

1.3. Literature review Buildings form an integral part of efforts towards a sustainable future. The construction, operation and end-of-life activities of buildings are associated with a wide range of energy- and material-related issues.

7

of office buildings in Sweden. They found that highly glazed office buildings could result in higher space heating and cooling demands than those with conventional façade elements. Grynning et al. [49] proposed and applied three rating methods to assess the energy performance of different configurations of window u-values and solar heat gain coefficients in a Norwegian office building. Few studies have analysed the influence of window sizes and orientations on the final and primary energy use for space heating and cooling of buildings with varying energy efficiency levels. Leskovar and Premrov [50, 51] studied the influence of glazing size on the architectural design and energy efficiency of timber-framed buildings with different external wall configurations and varying thermal transmittances. The focus of their studies was to analyse the effect of glazing size on the space heating and cooling demands of the studied buildings and to determine optimum glazing size on the south façade. However, they did not consider the primary energy implications and possible effects on the production energy of the different external wall configurations of the studied buildings.

Various post occupancy performance studies have emphasised increasing risks of overheating and high cooling demands for low energy buildings in different climate contexts [15, 52-56]. Other studies have reported the effect of climate change on the energy performance of different building configurations and have assessed overheating intervention measures for both current and future climates. Wang and Chen [57] investigated the impact of climate change on the energy use of residential and commercial buildings in all seven climate zones in the United States. They found that by 2080 there would be a net increase in primary energy use for heating and cooling in most climate zones and that the effectiveness of natural ventilation for buildings in some cities would be significantly reduced. Dodoo and Gustavsson [58] studied the energy use profile, overheating risks and effectiveness of various overheating control measures for multi-storey residential buildings in Sweden under different climate scenarios. They found that heating demand decreased significantly, while cooling demand increased considerably for the studied buildings. Holmes and Hacker [59] studied the thermal comfort and energy use of buildings in the United Kingdom (UK) in the context of low-energy design strategies under climate change. They considered different ventilation design strategies and building operation schedules to achieve comfortable indoor environment. Wong et al. [60] investigated the impact of climate

6

The EU’s energy performance of buildings directive (EPBD) provides a framework methodology for calculating energy use of buildings and suggests that this should at least account for factors related to building thermal envelope, orientation, outdoor and indoor climates, lighting, heating, ventilation, air handling units, and passive solar systems and solar protection [33]. Simulation tools that can account for the dynamics of these factors are increasingly available and used for building energy balance calculations [34-37]. However, the accuracy and reliability of results obtained from such tools partly depend on the quality of input data and assumptions. In an Australian study, Daly et al. [38] found that simulated final energy demand of prototype buildings varied by more than 50% from baselines when using plausible high and low simulation assumptions. Zhao et al. [39] simulated heating and cooling demands of buildings in different climate zones of China and explored the effects of key parameters influencing the buildings’ thermal performance including air infiltration rate, thickness of building envelope insulation and window u-values, external solar protection including shading co-efficient of windows, and window to wall ratios. Wall [40] simulated the energy performance of Swedish terrace houses and explored the implications of different assumptions and input data related to indoor temperature set-points, solar gains and occupant behaviour. They found large variations in space heating demand and attributed this mainly to underestimation of indoor temperature, household electricity and solar fraction for solar collectors in the building model. Molin et al. [41] studied the effect of different parameters on the energy use of low-energy buildings in Sweden. They found that among the studied parameters, internal heat gains had the most significant effect on the space heating energy use of the buildings. Danielski [42] compared simulated and monitored energy use of apartment buildings in Sweden and found large variations, despite similar construction and energy systems. This was attributed to uncertainties in input data for the building energy models, time difference between completion of the construction of the buildings and actual measurements, shape factor and relative size of common areas in the buildings.

Several studies have shown the significance of the influence of window types, sizes and orientation on the energy balance of buildings in different climates [43-47]. Poirazis [48] analysed the impacts of varying the ratio of window area, glazing type and size among others on the operation energy use

7

of office buildings in Sweden. They found that highly glazed office buildings could result in higher space heating and cooling demands than those with conventional façade elements. Grynning et al. [49] proposed and applied three rating methods to assess the energy performance of different configurations of window u-values and solar heat gain coefficients in a Norwegian office building. Few studies have analysed the influence of window sizes and orientations on the final and primary energy use for space heating and cooling of buildings with varying energy efficiency levels. Leskovar and Premrov [50, 51] studied the influence of glazing size on the architectural design and energy efficiency of timber-framed buildings with different external wall configurations and varying thermal transmittances. The focus of their studies was to analyse the effect of glazing size on the space heating and cooling demands of the studied buildings and to determine optimum glazing size on the south façade. However, they did not consider the primary energy implications and possible effects on the production energy of the different external wall configurations of the studied buildings.

Various post occupancy performance studies have emphasised increasing risks of overheating and high cooling demands for low energy buildings in different climate contexts [15, 52-56]. Other studies have reported the effect of climate change on the energy performance of different building configurations and have assessed overheating intervention measures for both current and future climates. Wang and Chen [57] investigated the impact of climate change on the energy use of residential and commercial buildings in all seven climate zones in the United States. They found that by 2080 there would be a net increase in primary energy use for heating and cooling in most climate zones and that the effectiveness of natural ventilation for buildings in some cities would be significantly reduced. Dodoo and Gustavsson [58] studied the energy use profile, overheating risks and effectiveness of various overheating control measures for multi-storey residential buildings in Sweden under different climate scenarios. They found that heating demand decreased significantly, while cooling demand increased considerably for the studied buildings. Holmes and Hacker [59] studied the thermal comfort and energy use of buildings in the United Kingdom (UK) in the context of low-energy design strategies under climate change. They considered different ventilation design strategies and building operation schedules to achieve comfortable indoor environment. Wong et al. [60] investigated the impact of climate

6

The EU’s energy performance of buildings directive (EPBD) provides a framework methodology for calculating energy use of buildings and suggests that this should at least account for factors related to building thermal envelope, orientation, outdoor and indoor climates, lighting, heating, ventilation, air handling units, and passive solar systems and solar protection [33]. Simulation tools that can account for the dynamics of these factors are increasingly available and used for building energy balance calculations [34-37]. However, the accuracy and reliability of results obtained from such tools partly depend on the quality of input data and assumptions. In an Australian study, Daly et al. [38] found that simulated final energy demand of prototype buildings varied by more than 50% from baselines when using plausible high and low simulation assumptions. Zhao et al. [39] simulated heating and cooling demands of buildings in different climate zones of China and explored the effects of key parameters influencing the buildings’ thermal performance including air infiltration rate, thickness of building envelope insulation and window u-values, external solar protection including shading co-efficient of windows, and window to wall ratios. Wall [40] simulated the energy performance of Swedish terrace houses and explored the implications of different assumptions and input data related to indoor temperature set-points, solar gains and occupant behaviour. They found large variations in space heating demand and attributed this mainly to underestimation of indoor temperature, household electricity and solar fraction for solar collectors in the building model. Molin et al. [41] studied the effect of different parameters on the energy use of low-energy buildings in Sweden. They found that among the studied parameters, internal heat gains had the most significant effect on the space heating energy use of the buildings. Danielski [42] compared simulated and monitored energy use of apartment buildings in Sweden and found large variations, despite similar construction and energy systems. This was attributed to uncertainties in input data for the building energy models, time difference between completion of the construction of the buildings and actual measurements, shape factor and relative size of common areas in the buildings.

Several studies have shown the significance of the influence of window types, sizes and orientation on the energy balance of buildings in different climates [43-47]. Poirazis [48] analysed the impacts of varying the ratio of window area, glazing type and size among others on the operation energy use

9

both space heating and cooling demands, contrary to present strategies in cold climates with a main focus on reducing space heating demand.

1.5. Aim and objective The aim of this thesis is to deepen the understanding of different strategies to minimise primary energy use and CO2 emissions of residential buildings from a life cycle and system perspective. The following specific research questions are addressed: How does the production of different insulation materials for residential

buildings affect the primary energy use and CO2 emission? How do key input parameters, methods and assumptions as well as their

interactions influence the energy balance calculations of residential buildings and energy savings of different energy efficiency measures?

What implications have different design strategies and their interaction with different heat supply options on production and operation primary energy use of residential buildings with different energy performance?

To what extent do different climate change scenarios influence the energy use of residential buildings with different energy performance and how can different design strategies and measures be used to minimise primary energy use?

8

change on the cooling demand of a residential building in Hong Kong under different GHG emission scenarios and assessed the effectiveness of increased indoor temperature, external wall insulation, double glazing and tinted glass. They found that increased indoor temperature was the most effective mitigation measure with occupants expected to adapt for example by changing clothes. Karimpour et al. [61] studied the impact of climate change on design variables to achieve energy efficient building envelopes in Australia under current and future climates. They considered different window glazing, floor covering, wall and roof insulation, reflective roofs and foil. They observed that measures to reduce cooling demand are more critical for better insulated buildings.

1.4. Knowledge gaps Thermal properties and performance of building insulation materials have significantly improved [62-65]. Several studies on building insulation materials have focused on the economic and final energy savings in individual building components. However, the potential primary energy and CO2 emission benefits of insulation materials linked to the production of functionally equivalent buildings have not been clearly quantified or demonstrated, when this research began in 2013.

There are several uncertainties linked to energy balance analyses of buildings. Various studies [39, 66, 67] have also investigated implications of different input data and assumptions for such analysis but focused on a few selected parameters and individual parameter variations. Comprehensive assessment of simulation input parameters and assumptions, encompassing microclimate, building envelope, occupancy behaviour, ventilation, electric and persons’ heat gains as well as their interactions appears to be lacking.

Different building design strategies may help to improve energy performance of buildings. The current design strategies for low-energy buildings are mainly geared towards improved building envelope performance. However, studies that analyse the energy implications, especially primary energy implications of incorporating different strategies in optimising building envelope design from a life cycle perspective seem to be lacking. Furthermore, design strategies for low-energy buildings need to be analysed under both current and future climates and optimised to minimise

9

both space heating and cooling demands, contrary to present strategies in cold climates with a main focus on reducing space heating demand.

1.5. Aim and objective The aim of this thesis is to deepen the understanding of different strategies to minimise primary energy use and CO2 emissions of residential buildings from a life cycle and system perspective. The following specific research questions are addressed: How does the production of different insulation materials for residential

buildings affect the primary energy use and CO2 emission? How do key input parameters, methods and assumptions as well as their

interactions influence the energy balance calculations of residential buildings and energy savings of different energy efficiency measures?

What implications have different design strategies and their interaction with different heat supply options on production and operation primary energy use of residential buildings with different energy performance?

To what extent do different climate change scenarios influence the energy use of residential buildings with different energy performance and how can different design strategies and measures be used to minimise primary energy use?

8

change on the cooling demand of a residential building in Hong Kong under different GHG emission scenarios and assessed the effectiveness of increased indoor temperature, external wall insulation, double glazing and tinted glass. They found that increased indoor temperature was the most effective mitigation measure with occupants expected to adapt for example by changing clothes. Karimpour et al. [61] studied the impact of climate change on design variables to achieve energy efficient building envelopes in Australia under current and future climates. They considered different window glazing, floor covering, wall and roof insulation, reflective roofs and foil. They observed that measures to reduce cooling demand are more critical for better insulated buildings.

1.4. Knowledge gaps Thermal properties and performance of building insulation materials have significantly improved [62-65]. Several studies on building insulation materials have focused on the economic and final energy savings in individual building components. However, the potential primary energy and CO2 emission benefits of insulation materials linked to the production of functionally equivalent buildings have not been clearly quantified or demonstrated, when this research began in 2013.

There are several uncertainties linked to energy balance analyses of buildings. Various studies [39, 66, 67] have also investigated implications of different input data and assumptions for such analysis but focused on a few selected parameters and individual parameter variations. Comprehensive assessment of simulation input parameters and assumptions, encompassing microclimate, building envelope, occupancy behaviour, ventilation, electric and persons’ heat gains as well as their interactions appears to be lacking.

Different building design strategies may help to improve energy performance of buildings. The current design strategies for low-energy buildings are mainly geared towards improved building envelope performance. However, studies that analyse the energy implications, especially primary energy implications of incorporating different strategies in optimising building envelope design from a life cycle perspective seem to be lacking. Furthermore, design strategies for low-energy buildings need to be analysed under both current and future climates and optimised to minimise

11

2. Methodological framework and approaches

In this thesis, the research aim and objectives are addressed by employing modelling and analytical tools to analyse the final and primary energy use as well as the associated CO2 emissions of buildings in a life cycle and system perspective.

2.1. Life cycle perspective Life cycle assessment (LCA) is one of the most widely used bottom-up analytical tools for assessing the environmental impacts of products and services. The general framework and guidelines for conducting LCA of goods and services are described in the ISO 14040:2006 and 14044:2006 standards, respectively [68, 69]. LCA involves the compilation and evaluation of the inputs and outputs as well as the potential environmental impacts of a product system throughout its life cycle [68, 69]. Conventional LCA comprises four phases, namely: goal and scope definition, inventory assessment, impact assessment, and results interpretation. Typically, two approaches of LCA analyses – attributional and consequential LCA are distinguished [70, 71]. While attributional LCA focuses on describing the environmentally relevant physical flows to and from a product life cycle and its subsystems, consequential LCA focuses on describing how the environmentally relevant flows will be affected in response to possible changes [72]. Plevin et al. [71] suggested that LCA practitioners and researchers should recognise the limitations and understand the appropriate uses of different LCA tools to achieve effective environmental policies and decisions. The main life cycle phases of buildings include production, operation and end-of-life management of demolished materials. LCA of buildings should cover all activities

11

2. Methodological framework and approaches

In this thesis, the research aim and objectives are addressed by employing modelling and analytical tools to analyse the final and primary energy use as well as the associated CO2 emissions of buildings in a life cycle and system perspective.

2.1. Life cycle perspective Life cycle assessment (LCA) is one of the most widely used bottom-up analytical tools for assessing the environmental impacts of products and services. The general framework and guidelines for conducting LCA of goods and services are described in the ISO 14040:2006 and 14044:2006 standards, respectively [68, 69]. LCA involves the compilation and evaluation of the inputs and outputs as well as the potential environmental impacts of a product system throughout its life cycle [68, 69]. Conventional LCA comprises four phases, namely: goal and scope definition, inventory assessment, impact assessment, and results interpretation. Typically, two approaches of LCA analyses – attributional and consequential LCA are distinguished [70, 71]. While attributional LCA focuses on describing the environmentally relevant physical flows to and from a product life cycle and its subsystems, consequential LCA focuses on describing how the environmentally relevant flows will be affected in response to possible changes [72]. Plevin et al. [71] suggested that LCA practitioners and researchers should recognise the limitations and understand the appropriate uses of different LCA tools to achieve effective environmental policies and decisions. The main life cycle phases of buildings include production, operation and end-of-life management of demolished materials. LCA of buildings should cover all activities

13

Energy system analysis can be performed by bottom‐up and top‐down methods. A bottom‐up approach is based on highly detailed representation of the fundamental components and processes of a system to generate aggregate system behavior by modelling the interactions between the individual components of the system [77]. While this approach gives detailed information on specific processes and enables detailed comparison of different alternatives, truncation error may occur outside the system boundaries as the analysis is expanded further upstream. In contrast, the top‐down approach begins with an overall aggregate description of a system and then proceeds to break this down to characterise the individual components of the system [77]. Though truncation errors are avoided in the top-down approach, it has limited detail of specific processes and may not enable complete understanding of the interactions between individual components in the system.

In this thesis, residential buildings and their energy supply chains are analysed in a systems perspective, using bottom-up models of mass and energy flows. This enabled detailed consideration of the processes in the energy supply chains and facilitated the comparison of different alternatives of the studied systems. In such comparative studies, the effect of truncation errors is marginal, as such errors are similar for the different alternative systems.

2.3. Energy supply systems The choice of energy supply system depends on various factors, including availability of local resources and expected life time performance of a technology [78]. Activities over the production phase of a building include extraction of raw materials, processing of raw materials and assembly of different materials into a building. Energy may be supplied in different ways for these purposes with varying primary energy use and CO2 emission. The largest use of fossil energy is for electricity production, both globally and in the EU. Electricity production is dominated by fossil fuel-based stand-alone power plants. Policy measures, however, are being implemented to increase the use of combined heat and power (CHP) plants. Here, end-use electricity for the production of building materials from a coal-based (Paper I) and biomass-based (Paper IV) steam turbine plants has been considered.

12

associated with these phases. LCA has been applied to assess the energetic and environmental impacts of buildings and building products in different contexts [1, 73, 74]. Still, studies have highlighted challenges associated with the application of LCA methods for whole building analysis. Such challenges relate to the complex interactions of activities over the long life span of buildings compared to many other products. Conventional LCA methodology may not adequately capture the interactions between the activities over the life cycle of a complete building and its energy supply systems. Such interactions may be explored using a system analysis approach, which accounts for the synergies between individual components within the system as a whole [75]. Basic considerations of a systems analysis approach include the objectives, environment, resources, components and management of the system [76].

In this thesis, a system analysis approach based on a life cycle perspective is employed to evaluate the studied buildings and their energy supply systems. The life cycle perspective considered here is similar to the inventory assessment phase of the LCA methodology and accounts for material and energy flows associated with the processes and activities during the life cycle. This approach is used in Papers I, IV and V to analyse the consequences of various changes on the modelled buildings and energy supply systems as it enables detailed assessment of specific processes and activities relevant to the modelled changes. In Papers II and III, key parameter values, methods and assumptions influencing energy flows related to the operation phase of the studied buildings as well as their interactions are modelled through detailed computer simulation.

2.2. Energy system analysis The final energy demand during the operation phase of a building can be provided by different technologies and energy resources. Depending on the energy supply system and energy resources, different amounts of primary energy may be required to meet the required final energy demand. Primary energy use determines the natural resource use and the environmental impact of the final energy demand by taking into account all inputs and losses along the entire energy supply chains. Therefore, analyses of the environmental impacts of energy supply systems need to be conducted with a system perspective approach.

13

Energy system analysis can be performed by bottom‐up and top‐down methods. A bottom‐up approach is based on highly detailed representation of the fundamental components and processes of a system to generate aggregate system behavior by modelling the interactions between the individual components of the system [77]. While this approach gives detailed information on specific processes and enables detailed comparison of different alternatives, truncation error may occur outside the system boundaries as the analysis is expanded further upstream. In contrast, the top‐down approach begins with an overall aggregate description of a system and then proceeds to break this down to characterise the individual components of the system [77]. Though truncation errors are avoided in the top-down approach, it has limited detail of specific processes and may not enable complete understanding of the interactions between individual components in the system.

In this thesis, residential buildings and their energy supply chains are analysed in a systems perspective, using bottom-up models of mass and energy flows. This enabled detailed consideration of the processes in the energy supply chains and facilitated the comparison of different alternatives of the studied systems. In such comparative studies, the effect of truncation errors is marginal, as such errors are similar for the different alternative systems.

2.3. Energy supply systems The choice of energy supply system depends on various factors, including availability of local resources and expected life time performance of a technology [78]. Activities over the production phase of a building include extraction of raw materials, processing of raw materials and assembly of different materials into a building. Energy may be supplied in different ways for these purposes with varying primary energy use and CO2 emission. The largest use of fossil energy is for electricity production, both globally and in the EU. Electricity production is dominated by fossil fuel-based stand-alone power plants. Policy measures, however, are being implemented to increase the use of combined heat and power (CHP) plants. Here, end-use electricity for the production of building materials from a coal-based (Paper I) and biomass-based (Paper IV) steam turbine plants has been considered.

12

associated with these phases. LCA has been applied to assess the energetic and environmental impacts of buildings and building products in different contexts [1, 73, 74]. Still, studies have highlighted challenges associated with the application of LCA methods for whole building analysis. Such challenges relate to the complex interactions of activities over the long life span of buildings compared to many other products. Conventional LCA methodology may not adequately capture the interactions between the activities over the life cycle of a complete building and its energy supply systems. Such interactions may be explored using a system analysis approach, which accounts for the synergies between individual components within the system as a whole [75]. Basic considerations of a systems analysis approach include the objectives, environment, resources, components and management of the system [76].

In this thesis, a system analysis approach based on a life cycle perspective is employed to evaluate the studied buildings and their energy supply systems. The life cycle perspective considered here is similar to the inventory assessment phase of the LCA methodology and accounts for material and energy flows associated with the processes and activities during the life cycle. This approach is used in Papers I, IV and V to analyse the consequences of various changes on the modelled buildings and energy supply systems as it enables detailed assessment of specific processes and activities relevant to the modelled changes. In Papers II and III, key parameter values, methods and assumptions influencing energy flows related to the operation phase of the studied buildings as well as their interactions are modelled through detailed computer simulation.

2.2. Energy system analysis The final energy demand during the operation phase of a building can be provided by different technologies and energy resources. Depending on the energy supply system and energy resources, different amounts of primary energy may be required to meet the required final energy demand. Primary energy use determines the natural resource use and the environmental impact of the final energy demand by taking into account all inputs and losses along the entire energy supply chains. Therefore, analyses of the environmental impacts of energy supply systems need to be conducted with a system perspective approach.

15

replace electricity that would have been otherwise produced in a stand‐alone plant with similar fuel and technology as the CHP plant [81]. The primary energy that would have been used to produce the replaced electricity in the stand‐alone plant is subtracted from that for the CHP plant to obtain the primary energy for the system.

2.5. System boundaries and functional unit Establishing effective system boundaries and defining an appropriate functional unit is an important aspect in comparative analyses [82]. System boundaries describe the activities included in the modelled system and should be established broadly enough to capture the significant impacts of interest, but not so broad as to make the analysis too unwieldy [82]. In this work, boundaries are defined depending on the goals of the analyses. In Papers I and IV, the focus was on materials production and operation of the studied buildings. The system boundaries covered the complete materials and energy chains, including material losses, conversion and fuel cycle losses along the entire material production and energy supply systems processes. In Papers II and III, the system boundaries were defined around the building envelope and included all the energy flows through them. In Paper V, the system boundaries are extended to cover the entire energy supply chains from extraction of natural resources to the supplied heat and electricity in the building.

A functional unit is a measure of the required properties of the studied system, providing a reference to which input and output flows can be related [82]. The functional unit can be defined at the level of building component, complete building, or services provided by the built environment [77]. In this thesis, the functional unit is defined at the level of an entire building and the results are expressed per usable floor area to readily facilitate comparison.

2.6. Analysed parameters Different parameters can be used to express the energetic and climate impacts of buildings over their life cycle. Final energy expresses the energy supplied to the building excluding losses in end-use conversion as well as internal heat losses. While minimising final energy use is an important aspect of achieving low-energy buildings, this strategy does not fully reflect the environmental impacts and natural resource use of energy supply. Primary energy use, on the

14

During the operation phase of a building, energy is required for space heating and cooling, tap water heating, household appliances, lighting as well as fans and pumps. Space heating dominates the final operation energy use of the residential building stock in almost all EU countries [13]. In 2013, district heating accounted for about 58% of the total heat supply in the residential and service sectors in Sweden [79]. District heating is mostly used in multi-storey residential buildings, which accounted for about half of the total heat supply in the residential and service sectors. In this thesis, multi-storey residential buildings connected to district heating based on CHP plants are analysed in Papers I, IV and V. The primary energy efficiency of heat supply systems may also be affected by the heat production technology and fuel types. In Paper IV, alternatives where the studied buildings are heated with heat only boilers (HOB) are also considered to show the interaction between different supply systems and design strategies. Electricity supply for household appliances, lighting and fans and pumps are based on stand-alone plants with similar technologies as for material production. Currently, cooling demands for residential buildings are generally low in Sweden and cooling is typically managed in summer by shading and ventilation strategies. However, the risk of overheating in buildings is expected to increase under projected climate change scenarios. Cooling demand was analysed for the buildings in Papers II, IV and V. In Papers IV and V, mechanical cooling systems with electricity supply from stand-alone plants were assumed to meet cooling demands. The detailed characteristics of the district heating and electricity supply systems are given in the respective papers.

2.4. Allocation in CHP production The district heating systems analysed in this thesis are based on CHP with cogeneration of heat and electricity. Allocation issues may arise in such multiple output systems. Allocation is the process of attributing impacts or benefits to a particular part of a process that results in multiple outputs and can be performed by different methods [80]. Allocation can be complex and subjective and hence could be avoided if possible e.g. through system expansion by including additional functions in the systems [81]. In this thesis, system expansion based on the subtraction method was used to avoid allocation in the CHP systems. The cogenerated electricity is assumed to

15

replace electricity that would have been otherwise produced in a stand‐alone plant with similar fuel and technology as the CHP plant [81]. The primary energy that would have been used to produce the replaced electricity in the stand‐alone plant is subtracted from that for the CHP plant to obtain the primary energy for the system.

2.5. System boundaries and functional unit Establishing effective system boundaries and defining an appropriate functional unit is an important aspect in comparative analyses [82]. System boundaries describe the activities included in the modelled system and should be established broadly enough to capture the significant impacts of interest, but not so broad as to make the analysis too unwieldy [82]. In this work, boundaries are defined depending on the goals of the analyses. In Papers I and IV, the focus was on materials production and operation of the studied buildings. The system boundaries covered the complete materials and energy chains, including material losses, conversion and fuel cycle losses along the entire material production and energy supply systems processes. In Papers II and III, the system boundaries were defined around the building envelope and included all the energy flows through them. In Paper V, the system boundaries are extended to cover the entire energy supply chains from extraction of natural resources to the supplied heat and electricity in the building.

A functional unit is a measure of the required properties of the studied system, providing a reference to which input and output flows can be related [82]. The functional unit can be defined at the level of building component, complete building, or services provided by the built environment [77]. In this thesis, the functional unit is defined at the level of an entire building and the results are expressed per usable floor area to readily facilitate comparison.

2.6. Analysed parameters Different parameters can be used to express the energetic and climate impacts of buildings over their life cycle. Final energy expresses the energy supplied to the building excluding losses in end-use conversion as well as internal heat losses. While minimising final energy use is an important aspect of achieving low-energy buildings, this strategy does not fully reflect the environmental impacts and natural resource use of energy supply. Primary energy use, on the

14

During the operation phase of a building, energy is required for space heating and cooling, tap water heating, household appliances, lighting as well as fans and pumps. Space heating dominates the final operation energy use of the residential building stock in almost all EU countries [13]. In 2013, district heating accounted for about 58% of the total heat supply in the residential and service sectors in Sweden [79]. District heating is mostly used in multi-storey residential buildings, which accounted for about half of the total heat supply in the residential and service sectors. In this thesis, multi-storey residential buildings connected to district heating based on CHP plants are analysed in Papers I, IV and V. The primary energy efficiency of heat supply systems may also be affected by the heat production technology and fuel types. In Paper IV, alternatives where the studied buildings are heated with heat only boilers (HOB) are also considered to show the interaction between different supply systems and design strategies. Electricity supply for household appliances, lighting and fans and pumps are based on stand-alone plants with similar technologies as for material production. Currently, cooling demands for residential buildings are generally low in Sweden and cooling is typically managed in summer by shading and ventilation strategies. However, the risk of overheating in buildings is expected to increase under projected climate change scenarios. Cooling demand was analysed for the buildings in Papers II, IV and V. In Papers IV and V, mechanical cooling systems with electricity supply from stand-alone plants were assumed to meet cooling demands. The detailed characteristics of the district heating and electricity supply systems are given in the respective papers.

2.4. Allocation in CHP production The district heating systems analysed in this thesis are based on CHP with cogeneration of heat and electricity. Allocation issues may arise in such multiple output systems. Allocation is the process of attributing impacts or benefits to a particular part of a process that results in multiple outputs and can be performed by different methods [80]. Allocation can be complex and subjective and hence could be avoided if possible e.g. through system expansion by including additional functions in the systems [81]. In this thesis, system expansion based on the subtraction method was used to avoid allocation in the CHP systems. The cogenerated electricity is assumed to

17

the Million Homes Programme [83]. The building is located in the Lindvägen area of Ronneby municipality (latitude 56.26, longitude 15.27), in southern Sweden and has 3 storeys of living areas made up of 27 apartments with heated floor area of 2000 m2 and a basement below ground level. The total ventilated volume is 5400 m3. The ground floor of the building is made up of 190 mm concrete slab on 150 mm crushed stones. The north and south external walls consist of layers of 20 mm air gap and 95 mm glass wool insulation, sandwiched between 85 mm brick façade and 120 mm concrete, with 15mm gypsum plaster. The east and west external walls are made of either brick or wooden claddings on the outside with layers of 20 mm air gap, 25 mm polystyrene insulation and 45 or 95 mm glass wool insulation with 15 mm gypsum plaster. The basement walls have layers of 15 mm cement plaster, 50 mm leca cement bond and 250 or 150 mm concrete on the north/south and east/west façades, respectively. The intermediate floors consist of 10 mm floor boarding over 190 mm concrete, while the attic floor has 350 mm mineral wool insulation placed over 160 mm concrete slab. The windows and doors have clear glass panels with wooden frames. Construction details and thermal properties of the building are given in Table 1.

2.7.3. Täppan building The Täppan building (Papers IV and V) is a 6-storey concrete frame structure with 24 apartments, comprising 1-3 rooms with a total heated floor area of 1686 m2 and was completed in 2014 in Växjö. The foundation of the building consists of layers of 200 mm crushed stone, 300 mm cellplast insulation and a 100 mm ground floor concrete slab. The external walls consist of 100 mm and 230 mm concrete on the outside and inside respectively, with a 100 mm layer of cellplast insulation material between them. The internal partitions are made of 200 mm concrete load bearing walls and non-load bearing walls of 30 mm thick gyproc plasterboard layers with steel studs spaced at 600 mm and air gaps of 95–145 mm between them. The intermediate floors are 250 mm concrete slabs whiles the ceiling floor is made up of 250 mm concrete slab and 500 mm loose fill rock wool insulation with wooden trusses and a roof covering over layers of asphalt-impregnated felt and plywood. The windows and external doors have clear glass double-glazed panels with wood frames, clad with aluminium profiles on the outside. The construction details and thermal properties of the building are given in Table 1.

16

other hand, accounts for natural resource use and all inputs and losses along the entire energy supply chains in order to deliver the required final energy demand. In this work, final energy demand is analysed in Papers II and III while primary energy use is considered in Papers I, IV and V. CO2 emission from building material production is also considered in Paper I.

2.7. Studied buildings Three different multi-storey buildings were analysed in this research and are briefly described below.

2.7.1. Wälludden building The Wälludden building (Paper I) is a 4-storey wood-frame multi-family residence located in Växjö (latitude 56°87′37″N; longitude 14°48′33″E). The building has 16 apartments and a total heated floor area of 1190 m2. The ground floor comprises 15 mm oak board flooring over a 160 mm concrete slab laid on 150 mm macadam and insulated with 70 mm expanded polystyrene (EPS). The external walls are made of three layers, namely 50 mm plaster-compatible mineral rock wool insulation, 120 mm thick timber studs, and a building services installation layer of 70 mm thick timber studs with mineral rock wool insulation. The windows and external doors are double-glazed panels with wood frames. The whole building façade is plastered with stucco except the stair well façade, which has wood panel finishes. The intermediate floors consist of timber floor joists with four layers of 13 mm plasterboards, 45 mm folded steel sheet and 300 mm mineral wool insulation with 15 mm oak board flooring. The internal walls separating the apartments are made of two layers of 30 mm thick plasterboards with mineral wool insulation between them while the other internal walls consist of layers of plasterboards with 120 mm air gap between them. The roof has two layers of asphalt-impregnated felt on wooden panels with 400 mm mineral rock wool insulation between wooden roof trusses, polythene foils and gypsum board. The construction details and thermal properties of the building are given in Table 1.

2.7.2. Lindvägen building The Lindvägen building (Papers II and III) is representative of a typical Swedish multi-storey residential building constructed in the 1970s as part of

17

the Million Homes Programme [83]. The building is located in the Lindvägen area of Ronneby municipality (latitude 56.26, longitude 15.27), in southern Sweden and has 3 storeys of living areas made up of 27 apartments with heated floor area of 2000 m2 and a basement below ground level. The total ventilated volume is 5400 m3. The ground floor of the building is made up of 190 mm concrete slab on 150 mm crushed stones. The north and south external walls consist of layers of 20 mm air gap and 95 mm glass wool insulation, sandwiched between 85 mm brick façade and 120 mm concrete, with 15mm gypsum plaster. The east and west external walls are made of either brick or wooden claddings on the outside with layers of 20 mm air gap, 25 mm polystyrene insulation and 45 or 95 mm glass wool insulation with 15 mm gypsum plaster. The basement walls have layers of 15 mm cement plaster, 50 mm leca cement bond and 250 or 150 mm concrete on the north/south and east/west façades, respectively. The intermediate floors consist of 10 mm floor boarding over 190 mm concrete, while the attic floor has 350 mm mineral wool insulation placed over 160 mm concrete slab. The windows and doors have clear glass panels with wooden frames. Construction details and thermal properties of the building are given in Table 1.

2.7.3. Täppan building The Täppan building (Papers IV and V) is a 6-storey concrete frame structure with 24 apartments, comprising 1-3 rooms with a total heated floor area of 1686 m2 and was completed in 2014 in Växjö. The foundation of the building consists of layers of 200 mm crushed stone, 300 mm cellplast insulation and a 100 mm ground floor concrete slab. The external walls consist of 100 mm and 230 mm concrete on the outside and inside respectively, with a 100 mm layer of cellplast insulation material between them. The internal partitions are made of 200 mm concrete load bearing walls and non-load bearing walls of 30 mm thick gyproc plasterboard layers with steel studs spaced at 600 mm and air gaps of 95–145 mm between them. The intermediate floors are 250 mm concrete slabs whiles the ceiling floor is made up of 250 mm concrete slab and 500 mm loose fill rock wool insulation with wooden trusses and a roof covering over layers of asphalt-impregnated felt and plywood. The windows and external doors have clear glass double-glazed panels with wood frames, clad with aluminium profiles on the outside. The construction details and thermal properties of the building are given in Table 1.

16

other hand, accounts for natural resource use and all inputs and losses along the entire energy supply chains in order to deliver the required final energy demand. In this work, final energy demand is analysed in Papers II and III while primary energy use is considered in Papers I, IV and V. CO2 emission from building material production is also considered in Paper I.

2.7. Studied buildings Three different multi-storey buildings were analysed in this research and are briefly described below.

2.7.1. Wälludden building The Wälludden building (Paper I) is a 4-storey wood-frame multi-family residence located in Växjö (latitude 56°87′37″N; longitude 14°48′33″E). The building has 16 apartments and a total heated floor area of 1190 m2. The ground floor comprises 15 mm oak board flooring over a 160 mm concrete slab laid on 150 mm macadam and insulated with 70 mm expanded polystyrene (EPS). The external walls are made of three layers, namely 50 mm plaster-compatible mineral rock wool insulation, 120 mm thick timber studs, and a building services installation layer of 70 mm thick timber studs with mineral rock wool insulation. The windows and external doors are double-glazed panels with wood frames. The whole building façade is plastered with stucco except the stair well façade, which has wood panel finishes. The intermediate floors consist of timber floor joists with four layers of 13 mm plasterboards, 45 mm folded steel sheet and 300 mm mineral wool insulation with 15 mm oak board flooring. The internal walls separating the apartments are made of two layers of 30 mm thick plasterboards with mineral wool insulation between them while the other internal walls consist of layers of plasterboards with 120 mm air gap between them. The roof has two layers of asphalt-impregnated felt on wooden panels with 400 mm mineral rock wool insulation between wooden roof trusses, polythene foils and gypsum board. The construction details and thermal properties of the building are given in Table 1.

2.7.2. Lindvägen building The Lindvägen building (Papers II and III) is representative of a typical Swedish multi-storey residential building constructed in the 1970s as part of

19

𝐸𝐸𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 = ∑ {∑[𝐹𝐹𝑝𝑝𝑖𝑖𝑖 × (1 + 𝛼𝛼𝑖𝑖)] + 𝐿𝐿𝑝𝑝𝜂𝜂

𝑖𝑖+ 𝐵𝐵𝑝𝑝}

𝑝𝑝

where Eproduction = total primary energy use for material production (kWh); i = individual material types in the building; F = end-use fossil fuel energy used to extract, process and transport the materials (kWh); k = fossil fuels - coal, oil, and natural gas; α = fuel cycle energy requirement of the fossil fuel; L = electricity to extract, process, and transport the materials including transmission and distribution losses (kWhe); η = conversion efficiency for electricity production; B = heat content (lower heating value) of the biofuels used in material processing (kWh).

Data for specific end-use energy for material production based on a study of building material industries in Sweden [85] and a similar Norwegian study [86] were used to calculate the end‐use fossil fuel and electricity used to extract, process and transport the materials. The specific end-use energy for production of selected materials based on these studies is given in Table 2. Though these represent a relatively old data source, they are well representative of the context for this study and show similar trends for selected materials compared to results with more recent data based on [87] as shown in paper I. A variety of factors can affect the energy and CO2 balances of building materials over their life cycle [88]. Several of such uncertainties and variabilities are discussed in detail by [77]. The efficiency and fuel input of production processes and technologies may improve with time. Uncertainties related to data for specific end-use energy for materials were explored in a sensitivity analysis in Paper I.

2.8.2 Building materials production CO2 emission Further, the CO2 emission from building material production as a result of fossil fuel use is calculated as:

𝐶𝐶𝑓𝑓𝑝𝑝𝑓𝑓𝑓𝑓𝑝𝑝𝑓𝑓 = ∑[𝐶𝐶𝑖𝑖 × 𝐹𝐹𝑖𝑖]𝑖𝑖

+ 𝐶𝐶𝐿𝐿 × 𝐿𝐿𝜂𝜂

where Cfossil = total CO2 emissions from material production (kg C);

18

Table 1. Construction details and thermal characteristics of the studied buildings Description Wälludden Lindvägen Täppan Construction frame Light timber Prefab concrete Prefab concrete Year of construction 1996 1972 2014 Number of floors 4 3 6 Number of apartments 16 27 24 Living area (m2) 1045 1878 1420 Common area (m2) 147 122 266 Basement area (m2) - 600 - Total heated air volume (m3) 2980 5400 4333 Exterior wall areaa (m2) 802 1051 1092 Windows area (m2) [S/W/E/N]b

26/90/58/26 9/117/130/9 39/161/75/39

Window to floor area ratio 0.17 0.13 0.19 Window to exterior wall ratio 0.25 0.25 0.29 U-values (W/m2K): Ground floor 0.23 0.26 0.11 Exterior walls 0.2 0.35/0.34/0.31c 0.32 Windows 1.9 2.9 1.2 Doors 1.19 3.0 1.2 Roof 0.13 0.11 0.08 Infiltration (l/s m2 @50 Pa) 0.8 0.8 0.6 Mechanical ventilation Exhaust air Exhaust air Balanced with VHRd a Excluding windows and door area b South/ West/ East and North c East & west brick façades/ South & north brick façades /East & west wooden façades d Ventilation heat recovery

2.8. Primary energy analysis and CO2 emission The primary energy analysis for building production phase activities is based on calculations of the overall primary energy use required to manufacture the materials necessary to construct the different building versions.

2.8.1 Building materials production primary energy The primary energy use for building materials production accounts for the total primary energy to extract, process and transport the materials, and is calculated based on [84] as:

19

𝐸𝐸𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 = ∑ {∑[𝐹𝐹𝑝𝑝𝑖𝑖𝑖 × (1 + 𝛼𝛼𝑖𝑖)] + 𝐿𝐿𝑝𝑝𝜂𝜂

𝑖𝑖+ 𝐵𝐵𝑝𝑝}

𝑝𝑝

where Eproduction = total primary energy use for material production (kWh); i = individual material types in the building; F = end-use fossil fuel energy used to extract, process and transport the materials (kWh); k = fossil fuels - coal, oil, and natural gas; α = fuel cycle energy requirement of the fossil fuel; L = electricity to extract, process, and transport the materials including transmission and distribution losses (kWhe); η = conversion efficiency for electricity production; B = heat content (lower heating value) of the biofuels used in material processing (kWh).

Data for specific end-use energy for material production based on a study of building material industries in Sweden [85] and a similar Norwegian study [86] were used to calculate the end‐use fossil fuel and electricity used to extract, process and transport the materials. The specific end-use energy for production of selected materials based on these studies is given in Table 2. Though these represent a relatively old data source, they are well representative of the context for this study and show similar trends for selected materials compared to results with more recent data based on [87] as shown in paper I. A variety of factors can affect the energy and CO2 balances of building materials over their life cycle [88]. Several of such uncertainties and variabilities are discussed in detail by [77]. The efficiency and fuel input of production processes and technologies may improve with time. Uncertainties related to data for specific end-use energy for materials were explored in a sensitivity analysis in Paper I.

2.8.2 Building materials production CO2 emission Further, the CO2 emission from building material production as a result of fossil fuel use is calculated as:

𝐶𝐶𝑓𝑓𝑝𝑝𝑓𝑓𝑓𝑓𝑝𝑝𝑓𝑓 = ∑[𝐶𝐶𝑖𝑖 × 𝐹𝐹𝑖𝑖]𝑖𝑖

+ 𝐶𝐶𝐿𝐿 × 𝐿𝐿𝜂𝜂

where Cfossil = total CO2 emissions from material production (kg C);

18

Table 1. Construction details and thermal characteristics of the studied buildings Description Wälludden Lindvägen Täppan Construction frame Light timber Prefab concrete Prefab concrete Year of construction 1996 1972 2014 Number of floors 4 3 6 Number of apartments 16 27 24 Living area (m2) 1045 1878 1420 Common area (m2) 147 122 266 Basement area (m2) - 600 - Total heated air volume (m3) 2980 5400 4333 Exterior wall areaa (m2) 802 1051 1092 Windows area (m2) [S/W/E/N]b

26/90/58/26 9/117/130/9 39/161/75/39

Window to floor area ratio 0.17 0.13 0.19 Window to exterior wall ratio 0.25 0.25 0.29 U-values (W/m2K): Ground floor 0.23 0.26 0.11 Exterior walls 0.2 0.35/0.34/0.31c 0.32 Windows 1.9 2.9 1.2 Doors 1.19 3.0 1.2 Roof 0.13 0.11 0.08 Infiltration (l/s m2 @50 Pa) 0.8 0.8 0.6 Mechanical ventilation Exhaust air Exhaust air Balanced with VHRd a Excluding windows and door area b South/ West/ East and North c East & west brick façades/ South & north brick façades /East & west wooden façades d Ventilation heat recovery

2.8. Primary energy analysis and CO2 emission The primary energy analysis for building production phase activities is based on calculations of the overall primary energy use required to manufacture the materials necessary to construct the different building versions.

2.8.1 Building materials production primary energy The primary energy use for building materials production accounts for the total primary energy to extract, process and transport the materials, and is calculated based on [84] as:

21

The final energy use during the operation phase of the buildings, including space heating, space cooling, tap water heating, electricity for household appliances, lighting, fans and pumps was estimated by computer modelling using the VIP-Energy simulation software [90]. VIP-Energy performs whole building and dynamic hourly energy balance calculations, considering interactions between building design, geometry, thermal characteristics of building envelope elements and climate conditions as well as heating, ventilation and air conditioning (HVAC) and other technical installation for different building occupancy and operational schedules. The software permits detailed multi-zone and multi-dimensional modelling of thermal bridges and heat storage capacity of building envelope components. VIP-Energy is a commercially available software, increasingly used by consultants and construction companies in Nordic countries [91, 92] and has been used in several scientific researches e.g. [58, 93, 94]. Validation reports of VIP-Energy from different standard testing methods, including the International Energy Agency’s BESTEST, ANSI/ ASHRAE Standard 140 and CEN 15265 suggest that it has reliable algorithms and calculation models. In an investigation on cost optimal building energy efficiency improvement, the Swedish National Board of Housing, Building and Planning [95] compared energy calculation results from predominant simulations software and note that VIP-Energy generally gives good and consistent results in comparison with the other software considered. Key input parameter values and assumptions for the energy balance simulation of the buildings are given in the appended papers.

ENSYST [96] was used to calculate the primary energy needed to provide the final energy use in the buildings. ENSYST calculates primary energy use considering the entire energy supply chain from extraction of natural resources to the delivered final energy-use.

20

k = fossil fuels - coal, oil, and fossil gas; C = fuel-cycle carbon intensity of the fossil fuel (kg C/kWh end-use fuel); F = end-use fossil fuel energy used to extract, process, and transport the materials (kWh); CL = fuel-cycle carbon intensity of the reference fossil fuel to produce electricity (kg C/ kWh fuel); L = electricity to extract, process, and transport the materials including transmission and distribution losses (kWhe); η = conversion efficiency for electricity production.

Specific fuel-cycle carbon emission values of 0.11, 0.08 and 0.06 kg C/kWh end-use fuel were assumed for coal, oil, and fossil gas, respectively based on [88].

Table 2. Specific end-use energy (kWhend-use/kg) to produce selected building materials Material Coal Oil Fossil gas Biofuel Electricity Rock wool 2.00 0.36 0.02 - 0.39 Glass wool 2.86 0.52 0.03 - 2.00 Cellulose fiber 0.51 0.09 0.01 - 0.14 EPS 0.28 3.89 3.72 - 0.63 Foam glass - 0.04 3.22 - 0.42 Concrete 0.09 0.10 - - 0.02 Plasterboard - 0.79 - - 0.16 Lumber - 0.15 - 0.69 0.14 Particleboard - 0.39 - 0.39 0.42 Steel (ore-based) 3.92 0.86 1.34 - 0.91

2.8.3 Final and primary energy use for building operation Several dynamic energy balance simulation tools that can adequately account for the complex interaction of different factors influencing buildings’ thermal performance are available. An extensive summary of key features and modelling capabilities of commonly used building energy simulation tools worldwide is presented in [89]. In the Nordic region, DEROB-LTH, DesignBuilder, Energyplus, ESP-r, IDA-ICE, TRNSYS and VIP-Energy are among the commonly used dynamic energy simulation software.

21

The final energy use during the operation phase of the buildings, including space heating, space cooling, tap water heating, electricity for household appliances, lighting, fans and pumps was estimated by computer modelling using the VIP-Energy simulation software [90]. VIP-Energy performs whole building and dynamic hourly energy balance calculations, considering interactions between building design, geometry, thermal characteristics of building envelope elements and climate conditions as well as heating, ventilation and air conditioning (HVAC) and other technical installation for different building occupancy and operational schedules. The software permits detailed multi-zone and multi-dimensional modelling of thermal bridges and heat storage capacity of building envelope components. VIP-Energy is a commercially available software, increasingly used by consultants and construction companies in Nordic countries [91, 92] and has been used in several scientific researches e.g. [58, 93, 94]. Validation reports of VIP-Energy from different standard testing methods, including the International Energy Agency’s BESTEST, ANSI/ ASHRAE Standard 140 and CEN 15265 suggest that it has reliable algorithms and calculation models. In an investigation on cost optimal building energy efficiency improvement, the Swedish National Board of Housing, Building and Planning [95] compared energy calculation results from predominant simulations software and note that VIP-Energy generally gives good and consistent results in comparison with the other software considered. Key input parameter values and assumptions for the energy balance simulation of the buildings are given in the appended papers.

ENSYST [96] was used to calculate the primary energy needed to provide the final energy use in the buildings. ENSYST calculates primary energy use considering the entire energy supply chain from extraction of natural resources to the delivered final energy-use.

20

k = fossil fuels - coal, oil, and fossil gas; C = fuel-cycle carbon intensity of the fossil fuel (kg C/kWh end-use fuel); F = end-use fossil fuel energy used to extract, process, and transport the materials (kWh); CL = fuel-cycle carbon intensity of the reference fossil fuel to produce electricity (kg C/ kWh fuel); L = electricity to extract, process, and transport the materials including transmission and distribution losses (kWhe); η = conversion efficiency for electricity production.

Specific fuel-cycle carbon emission values of 0.11, 0.08 and 0.06 kg C/kWh end-use fuel were assumed for coal, oil, and fossil gas, respectively based on [88].

Table 2. Specific end-use energy (kWhend-use/kg) to produce selected building materials Material Coal Oil Fossil gas Biofuel Electricity Rock wool 2.00 0.36 0.02 - 0.39 Glass wool 2.86 0.52 0.03 - 2.00 Cellulose fiber 0.51 0.09 0.01 - 0.14 EPS 0.28 3.89 3.72 - 0.63 Foam glass - 0.04 3.22 - 0.42 Concrete 0.09 0.10 - - 0.02 Plasterboard - 0.79 - - 0.16 Lumber - 0.15 - 0.69 0.14 Particleboard - 0.39 - 0.39 0.42 Steel (ore-based) 3.92 0.86 1.34 - 0.91

2.8.3 Final and primary energy use for building operation Several dynamic energy balance simulation tools that can adequately account for the complex interaction of different factors influencing buildings’ thermal performance are available. An extensive summary of key features and modelling capabilities of commonly used building energy simulation tools worldwide is presented in [89]. In the Nordic region, DEROB-LTH, DesignBuilder, Energyplus, ESP-r, IDA-ICE, TRNSYS and VIP-Energy are among the commonly used dynamic energy simulation software.

23

3. Results

3.1. Production primary energy use and CO2 emission of insulation materials

In Paper I, the effects of different insulation materials on the production primary energy use and CO2 emission of the Wälludden building designed in accordance to the Swedish building code (BBR 2012) [97] and passive house criteria (Passive 2012) [98] for 2012 are analysed. The insulation materials considered in the different parts of the building versions and their corresponding thicknesses as well as the overall thicknesses of the building parts are shown in Table 3. Type of insulation material in building components in the existing building is shown in bold in the table.

Table 3. Insulation materials with required thicknesses in the different building parts under each energy efficiency standard. (Adapted from Paper I). Bold shows type of insulation material in the existing building. Building part Insulation

materials Insulation material thickness (mm)

Building part overall thickness (mm)

BBR 2012 Passive

2012 BBR 2012 Passive

2012 Roof Rock wool 358 440 404 486

Glass wool 365 450 411 496 Cellulose fiber 350 430 394 476

External wall Rock wool 278 364 330 416 Glass wool 292 386 344 438 Cellulose fiber 292 386 344 438 EPS 262 346 314 398

Internal wall Rock wool 276 276 370 370 Glass wool 290 290 384 384 Cellulose fiber 290 290 384 384 EPS 262 262 356 356

Ground floor EPS 148 148 473 473 Foam glass 156 156 481 481

23

3. Results

3.1. Production primary energy use and CO2 emission of insulation materials

In Paper I, the effects of different insulation materials on the production primary energy use and CO2 emission of the Wälludden building designed in accordance to the Swedish building code (BBR 2012) [97] and passive house criteria (Passive 2012) [98] for 2012 are analysed. The insulation materials considered in the different parts of the building versions and their corresponding thicknesses as well as the overall thicknesses of the building parts are shown in Table 3. Type of insulation material in building components in the existing building is shown in bold in the table.

Table 3. Insulation materials with required thicknesses in the different building parts under each energy efficiency standard. (Adapted from Paper I). Bold shows type of insulation material in the existing building. Building part Insulation

materials Insulation material thickness (mm)

Building part overall thickness (mm)

BBR 2012 Passive

2012 BBR 2012 Passive

2012 Roof Rock wool 358 440 404 486

Glass wool 365 450 411 496 Cellulose fiber 350 430 394 476

External wall Rock wool 278 364 330 416 Glass wool 292 386 344 438 Cellulose fiber 292 386 344 438 EPS 262 346 314 398

Internal wall Rock wool 276 276 370 370 Glass wool 290 290 384 384 Cellulose fiber 290 290 384 384 EPS 262 262 356 356

Ground floor EPS 148 148 473 473 Foam glass 156 156 481 481

25

(a)Production primary energy (b) Production CO2 emission Figure 4. Primary energy use (a) and CO2 emission (b) for insulation materials production per square meter heated area for the initial and improved building versions under BBR 2012 and Passivhus 2012 standards. (Adapted from Paper I).

The marginal electricity for material production is varied from the

reference coal-fired condensing plant to a natural gas-fired plant to explore the effects of possible future marginal electricity generation technology. The results are presented in Figure 5 and show an average reduction of 7% and 20% in production primary energy use and CO2 emissions, respectively for the buildings when natural gas based electricity instead of coal is used.

(a)Production primary energy (b) Production CO2 emission Figure 5. Primary energy use (a) and CO2 emission (b) for production of all materials per square meter heated area for the initial and improved building versions under BBR 2012 and Passivhus 2012 standards based on either a coal- or natural gas-fired electricity production. (Paper I).

24

Figure 3 shows the production primary energy use for different types of insulation materials for the BBR 2012 and passive 2012 building versions. For the ground floor of the buildings, only foam glass and EPS insulations were compared. In the remaining building components, cellulose fiber insulation consistently resulted in the lowest primary energy use for production compared to the other insulation alternatives for both building versions, while glass wool gave the highest.

(a) BBR 2012 (b) Passive 2012 Figure 3. Production primary energy use per square meter heated area for BBR 2012 (a) and Passive 2012 (b) building versions with different insulation material types. (Paper I).

The production primary energy use and CO2 emissions are calculated for all insulation materials for different building versions. The first version (initial) has the same type of insulation materials as in the existing building. The second version (improved) has insulation materials that give the lowest production primary energy use for different building components. These two versions are modelled to the BBR 2012 and Passive 2012 energy performance. The improved versions have cellulose fiber insulations in all parts, except in the ground floor where EPS is used. The production primary energy use and fossil CO2 emissions for insulation materials for these four alternatives are shown in Figure 4. The total primary energy use for insulation materials production for the improved version of the BBR 2012 and Passivhus 2012 buildings is reduced by 39% and 40%, respectively, compared to the initial versions.

25

(a)Production primary energy (b) Production CO2 emission Figure 4. Primary energy use (a) and CO2 emission (b) for insulation materials production per square meter heated area for the initial and improved building versions under BBR 2012 and Passivhus 2012 standards. (Adapted from Paper I).

The marginal electricity for material production is varied from the

reference coal-fired condensing plant to a natural gas-fired plant to explore the effects of possible future marginal electricity generation technology. The results are presented in Figure 5 and show an average reduction of 7% and 20% in production primary energy use and CO2 emissions, respectively for the buildings when natural gas based electricity instead of coal is used.

(a)Production primary energy (b) Production CO2 emission Figure 5. Primary energy use (a) and CO2 emission (b) for production of all materials per square meter heated area for the initial and improved building versions under BBR 2012 and Passivhus 2012 standards based on either a coal- or natural gas-fired electricity production. (Paper I).

24

Figure 3 shows the production primary energy use for different types of insulation materials for the BBR 2012 and passive 2012 building versions. For the ground floor of the buildings, only foam glass and EPS insulations were compared. In the remaining building components, cellulose fiber insulation consistently resulted in the lowest primary energy use for production compared to the other insulation alternatives for both building versions, while glass wool gave the highest.

(a) BBR 2012 (b) Passive 2012 Figure 3. Production primary energy use per square meter heated area for BBR 2012 (a) and Passive 2012 (b) building versions with different insulation material types. (Paper I).

The production primary energy use and CO2 emissions are calculated for all insulation materials for different building versions. The first version (initial) has the same type of insulation materials as in the existing building. The second version (improved) has insulation materials that give the lowest production primary energy use for different building components. These two versions are modelled to the BBR 2012 and Passive 2012 energy performance. The improved versions have cellulose fiber insulations in all parts, except in the ground floor where EPS is used. The production primary energy use and fossil CO2 emissions for insulation materials for these four alternatives are shown in Figure 4. The total primary energy use for insulation materials production for the improved version of the BBR 2012 and Passivhus 2012 buildings is reduced by 39% and 40%, respectively, compared to the initial versions.

27

Table 5. Effects of single variations of different macro and micro-climate parameters on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Table 6. Effects of single variations of different heat gains parameters and assumptions on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Outdoor temperature (Reference is based on 2013 climate data for Ronneby): -1 oC 105 3 2 110 11 0 -33 +1 oC 86 3 4 93 -9 0 33 Horizontal angle of shading (Reference 20 degrees): 10 degrees 90 3 5 98 -5 0 67 30 degrees 100 3 1 104 5 0 -67 Ground solar reflection (Reference 0%): 25% 92 3 5 100 -3 0 67 50% 90 3 8 101 -5 0 167 Wind load against building (Reference 70%): 30% 95 3 3 101 0 0 0 100% 97 3 3 103 2 0 0 Air pressure outside (Reference 1000hPa): 990 hPa (-1% ) 95 3 3 101 0 0 0 1020 hPa (+2% ) 96 3 3 102 1 0 0

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Persons heat gains (Reference 1.0 W/m2): 1.68 W/m2 91 3 3 97 -4 0 0 2.16 W/m2 88 3 4 95 -7 0 33 3.19 W/m2 81 3 5 89 -15 0 67 4.30 W/m2 75 3 7 85 -21 0 133 Electrical heat gains (Reference 3.05 W/m2): 2.40 W/m2 100 3 2 105 5 0 -33 4.4 W/m2 87 3 4 94 -8 0 33 4.92 W/m2 83 3 5 91 -13 0 67

26

Overall, a reduction of about 6 – 7% in primary energy use and 6 – 8% in CO2 emission is achieved when the insulation material in the initial buildings is changed from rock wool to cellulose fiber in their improved versions.

3.2. Parameters and assumptions for energy balance calculations

Increasingly, inappropriate simulation input data and assumptions are cited as a key cause of discrepancy between simulated and monitored energy use of buildings [67, 99]. In paper II key simulation input parameter values, methods and assumptions used for energy balance calculations of residential buildings in Sweden and their effects on calculated energy balance of the Lindvägen building are explored. Their effects on calculated energy savings of different energy efficiency measures are also investigated. The studied parameters are related to microclimate, building envelope, occupancy behaviour, ventilation systems, electric and persons heat gains. Tables 4 - 8 show the effect of varying individual parameter values and assumptions on the simulated final energy demand, including space heating, space cooling and electricity for ventilation fans and pumps of the building. In the tables, negative change means that the simulated energy demand is lower, while positive change means that it is greater, relative to the reference case. Reference parameters and assumptions are indicated in brackets.

Table 4. Effects of single variations of different heating and cooling set-points on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Heating set-point (Reference 21 oC): 20 oC 88 3 3 94 -7 0 0 22 oC 104 3 3 110 9 0 0 23 oC 112 3 3 118 18 0 0 Cooling set point (Reference 26 oC): 27 oC 95 3 2 100 0 0 -33

27

Table 5. Effects of single variations of different macro and micro-climate parameters on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Table 6. Effects of single variations of different heat gains parameters and assumptions on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Outdoor temperature (Reference is based on 2013 climate data for Ronneby): -1 oC 105 3 2 110 11 0 -33 +1 oC 86 3 4 93 -9 0 33 Horizontal angle of shading (Reference 20 degrees): 10 degrees 90 3 5 98 -5 0 67 30 degrees 100 3 1 104 5 0 -67 Ground solar reflection (Reference 0%): 25% 92 3 5 100 -3 0 67 50% 90 3 8 101 -5 0 167 Wind load against building (Reference 70%): 30% 95 3 3 101 0 0 0 100% 97 3 3 103 2 0 0 Air pressure outside (Reference 1000hPa): 990 hPa (-1% ) 95 3 3 101 0 0 0 1020 hPa (+2% ) 96 3 3 102 1 0 0

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Persons heat gains (Reference 1.0 W/m2): 1.68 W/m2 91 3 3 97 -4 0 0 2.16 W/m2 88 3 4 95 -7 0 33 3.19 W/m2 81 3 5 89 -15 0 67 4.30 W/m2 75 3 7 85 -21 0 133 Electrical heat gains (Reference 3.05 W/m2): 2.40 W/m2 100 3 2 105 5 0 -33 4.4 W/m2 87 3 4 94 -8 0 33 4.92 W/m2 83 3 5 91 -13 0 67

26

Overall, a reduction of about 6 – 7% in primary energy use and 6 – 8% in CO2 emission is achieved when the insulation material in the initial buildings is changed from rock wool to cellulose fiber in their improved versions.

3.2. Parameters and assumptions for energy balance calculations

Increasingly, inappropriate simulation input data and assumptions are cited as a key cause of discrepancy between simulated and monitored energy use of buildings [67, 99]. In paper II key simulation input parameter values, methods and assumptions used for energy balance calculations of residential buildings in Sweden and their effects on calculated energy balance of the Lindvägen building are explored. Their effects on calculated energy savings of different energy efficiency measures are also investigated. The studied parameters are related to microclimate, building envelope, occupancy behaviour, ventilation systems, electric and persons heat gains. Tables 4 - 8 show the effect of varying individual parameter values and assumptions on the simulated final energy demand, including space heating, space cooling and electricity for ventilation fans and pumps of the building. In the tables, negative change means that the simulated energy demand is lower, while positive change means that it is greater, relative to the reference case. Reference parameters and assumptions are indicated in brackets.

Table 4. Effects of single variations of different heating and cooling set-points on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations Heating set-point (Reference 21 oC): 20 oC 88 3 3 94 -7 0 0 22 oC 104 3 3 110 9 0 0 23 oC 112 3 3 118 18 0 0 Cooling set point (Reference 26 oC): 27 oC 95 3 2 100 0 0 -33

29

calculations. The simulated demand for space cooling is significantly greater when the parameters giving the lowest heat demand are used. The calculated annual hourly peak loads and indoor air temperatures also vary significantly, depending on the datasets used for the simulation (Figure 7 and Figure 8).

Figure 6. Combined effects of the extremes of parameter values giving the highest and lowest space heating demand of the initial Lindvägen building. (Paper II).

Figure 7. Simulated annual hourly profiles for space heating of the initial Lindvägen building, arranged in descending order. (Paper II).

28

Table 7. Effects of single variations of different ventilation related parameters and assumptions on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Table 8. Effects of single variations of different u-values and airtightness of building envelope components on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Figure 6 shows the combined effects of the extremes of parameter values

and assumptions giving the highest and lowest simulated space heating demand for the building. For comparison, the reference value is also shown in Figure 6 as well as in Figures 7 and 8. The simulated final space heating demand is increased by 32% and decreased by 47% compared to the reference, when the extremes of parameter values are used to perform the energy balance

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations VHR efficiency (Reference no VHR): 76% 68 6 3 77 -28 100 0 80% 66 6 3 75 -31 100 0 85% 64 6 3 73 -33 100 0 Fan efficiency (Reference 50%): 33% 95 5 3 103 0 67 0 55% 95 3 3 101 0 0 0 Fan pressure (Reference 400 Pa): 200 Pa 95 2 3 100 0 -33 0 600 Pa 95 5 3 103 0 67 0 Airing (Reference no airing): VIP-energy approach 99 3 3 105 4 0 0 SVEBY approach 99 3 3 105 4 0 0

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations U-values of envelope (Reference is initial u-values of building envelope components): +20% 110 3 2 115 16 0 -33 Airtightness (Reference 0.8 l/sm2): 0.6 l/sm2 98 3 3 104 3 0 0 1 l/sm2 99 3 3 105 4 0 0

29

calculations. The simulated demand for space cooling is significantly greater when the parameters giving the lowest heat demand are used. The calculated annual hourly peak loads and indoor air temperatures also vary significantly, depending on the datasets used for the simulation (Figure 7 and Figure 8).

Figure 6. Combined effects of the extremes of parameter values giving the highest and lowest space heating demand of the initial Lindvägen building. (Paper II).

Figure 7. Simulated annual hourly profiles for space heating of the initial Lindvägen building, arranged in descending order. (Paper II).

28

Table 7. Effects of single variations of different ventilation related parameters and assumptions on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Table 8. Effects of single variations of different u-values and airtightness of building envelope components on simulated energy demand for the Lindvägen building. (Adapted from Paper II).

Figure 6 shows the combined effects of the extremes of parameter values

and assumptions giving the highest and lowest simulated space heating demand for the building. For comparison, the reference value is also shown in Figure 6 as well as in Figures 7 and 8. The simulated final space heating demand is increased by 32% and decreased by 47% compared to the reference, when the extremes of parameter values are used to perform the energy balance

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations VHR efficiency (Reference no VHR): 76% 68 6 3 77 -28 100 0 80% 66 6 3 75 -31 100 0 85% 64 6 3 73 -33 100 0 Fan efficiency (Reference 50%): 33% 95 5 3 103 0 67 0 55% 95 3 3 101 0 0 0 Fan pressure (Reference 400 Pa): 200 Pa 95 2 3 100 0 -33 0 600 Pa 95 5 3 103 0 67 0 Airing (Reference no airing): VIP-energy approach 99 3 3 105 4 0 0 SVEBY approach 99 3 3 105 4 0 0

Description Final energy demand (kWh/m2) Change from reference (%) Space heating

Ventilation electricity

Space cooling

Total Space heating

Ventilation electricity

Space cooling

Reference 95 3 3 101 - - - Parameter variations U-values of envelope (Reference is initial u-values of building envelope components): +20% 110 3 2 115 16 0 -33 Airtightness (Reference 0.8 l/sm2): 0.6 l/sm2 98 3 3 104 3 0 0 1 l/sm2 99 3 3 105 4 0 0

31

Figure 9. Saved final energy for space heating when the reference and extreme parameter values are used and different energy efficiency measures are applied singly or cumulatively in the shown order for the Lindvägen building. The main bars show the energy savings with the reference parameter values while the error bars show savings with combined effect of the extremes of parameter values giving either the lowest or highest simulated space heating demand. (Paper II).

Paper III builds on the analysis in Paper II with emphasis on the interactive influence of different simulation parameters and assumptions on the space heating demands of versions of the Lindvägen building in its existing state and with energy efficient improvements. Figure 10 shows a schematic illustration of the considered parameter groupings and the modelled interactions. Details of the input parameter values and assumptions variations for the energy balance simulation as well as thermal characteristics of the existing and energy efficient versions of the building are provided in the appended papers.

30

Figure 8. Simulated annual hourly profiles for indoor air temperature of the initial Lindvägen building, from January to December. (Paper II).

The implications of calculating the energy savings of energy efficiency

measures, implemented individually or cumulatively, with extremes of parameter values and assumptions giving the highest and lowest simulated space heating demand for the building are illustrated in Figure 9. The simulated energy savings are bigger when using the dataset giving the highest space heating demand, compared to the dataset giving the lowest space heating demand. Compared to the reference savings, the calculated savings for energy efficient new windows, extra insulation for exterior wall, VHR and improved airtight envelope changed significantly when the simulation is performed with the range of extreme datasets. On the other hand, the calculated energy savings for extra insulations for the attic and for the basement walls with the extremes of dataset vary marginally (in absolute terms).

31

Figure 9. Saved final energy for space heating when the reference and extreme parameter values are used and different energy efficiency measures are applied singly or cumulatively in the shown order for the Lindvägen building. The main bars show the energy savings with the reference parameter values while the error bars show savings with combined effect of the extremes of parameter values giving either the lowest or highest simulated space heating demand. (Paper II).

Paper III builds on the analysis in Paper II with emphasis on the interactive influence of different simulation parameters and assumptions on the space heating demands of versions of the Lindvägen building in its existing state and with energy efficient improvements. Figure 10 shows a schematic illustration of the considered parameter groupings and the modelled interactions. Details of the input parameter values and assumptions variations for the energy balance simulation as well as thermal characteristics of the existing and energy efficient versions of the building are provided in the appended papers.

30

Figure 8. Simulated annual hourly profiles for indoor air temperature of the initial Lindvägen building, from January to December. (Paper II).

The implications of calculating the energy savings of energy efficiency

measures, implemented individually or cumulatively, with extremes of parameter values and assumptions giving the highest and lowest simulated space heating demand for the building are illustrated in Figure 9. The simulated energy savings are bigger when using the dataset giving the highest space heating demand, compared to the dataset giving the lowest space heating demand. Compared to the reference savings, the calculated savings for energy efficient new windows, extra insulation for exterior wall, VHR and improved airtight envelope changed significantly when the simulation is performed with the range of extreme datasets. On the other hand, the calculated energy savings for extra insulations for the attic and for the basement walls with the extremes of dataset vary marginally (in absolute terms).

32

Figure 10. Schematic illustration of the parameter grouping and interactions modelled. (Paper III).

Tables 9a and 9b present the impacts of the different parameter values combinations and interactions on the calculated space heating of the Lindvägen building versions with household equipment and technical installations based on either standard technology (ST) or best available technology (BAT). The results from simulation of combination of parameter variations slightly differ from when the results of individual parameter variations are summed together, more so for the energy efficient building version. This suggests a somewhat interactive influence when several simulation parameter values are varied simultaneously.

33

Tabl

e 9a

. Si

mul

ated

fina

l ene

rgy

dem

ands

of t

he L

indv

ägen

bui

ldin

g ve

rsio

ns w

ith th

e pa

ram

eter

s var

iatio

ns a

nd in

tera

ctio

ns

with

the

hour

ly o

utdo

or te

mpe

ratu

re a

s in

the

2013

clim

ate

file

for t

he b

uild

ing

loca

tion.

(Pap

er II

I).

Para

met

er d

escr

iptio

n Ex

istin

g bu

ildin

g ve

rsio

n

Effi

cien

t bui

ldin

g ve

rsio

n

ST

BA

T

ST

B

AT

Spac

e he

atin

g (k

Wh/

m2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Initi

al (w

ith o

utdo

or te

mpe

ratu

re a

s in

refe

renc

e)

80.7

-

94

.1

-

18

-

28.1

-

+ m

ore

sunn

y 79

.5

-1.4

92.8

-1

.4

17

.7

-1.9

27.5

-2

.0

+ le

ss su

nny

81.8

1.

5

95.5

1.

5

18.4

2.

0

28.7

2.

1 +

mor

e w

indy

83

.4

3.4

96

.9

3.0

19

.6

8.7

29

.9

6.5

+ le

ss w

indy

78

.7

-2.4

92.1

-2

.2

16

.9

-6.0

26.8

-4

.6

+ m

ore

shad

ing

85.9

6.

6

100.

3 6.

6

19.7

9.

4

30.8

9.

8 +

less

shad

ing

74.7

-7

.4

87

.4

-7.1

16

-11.

5

25.1

-1

0.6

+ p

oor e

nvel

ope

101.

7 26

.0

11

5.6

22.8

25.1

39

.0

36

.0

28.4

+

mor

e su

nny

+ m

ore

win

dy

82.2

2.

0

95.6

1.

5

19.3

6.

8

29.3

4.

4 +

less

sunn

y +

less

win

dy

79.9

-1

.0

93

.5

-0.7

17.3

-4

.1

27

.4

-2.5

+

mor

e su

nny

+ m

ore

shad

ing

84.9

5.

2

99.0

5.

2

19.4

7.

6

30.3

7.

9 +

less

sunn

y +

less

shad

ing

75.9

-5

.9

88

.8

-5.7

16.3

-9

.6

25

.6

-8.8

+

mor

e su

nny

+ le

ss sh

adin

g 73

.5

-8.9

86.1

-8

.5

15

.6

-13.

4

24.6

-1

2.3

+ le

ss su

nny

+ m

ore

shad

ing

87.1

8.

0

101.

7 8.

1

20.1

11

.2

31

.4

11.8

+

mor

e w

indy

+ m

ore

shad

ing

88.8

10

.1

10

2.9

9.4

21

.4

18.6

32.7

16

.5

+ m

ore

win

dy +

less

shad

ing

77.4

-4

.1

90

.1

-4.2

17.5

-3

.2

26

.8

-4.6

32

Figure 10. Schematic illustration of the parameter grouping and interactions modelled. (Paper III).

Tables 9a and 9b present the impacts of the different parameter values combinations and interactions on the calculated space heating of the Lindvägen building versions with household equipment and technical installations based on either standard technology (ST) or best available technology (BAT). The results from simulation of combination of parameter variations slightly differ from when the results of individual parameter variations are summed together, more so for the energy efficient building version. This suggests a somewhat interactive influence when several simulation parameter values are varied simultaneously.

33

Table 9a. Simulated final energy demands of the Lindvägen building versions with the parameters variations and interactions with the hourly outdoor temperature as in the 2013 climate file for the building location. (Paper III). Parameter description Existing building version Efficient building version

ST BAT

ST

BAT

Space heating (kWh/m2)

Change from Initial (%)

Space heating (kWh/m2)

Change from Initial (%)

Space heating (kWh/m2)

Change from initial (%)

Space heating (kWh/m2)

Change from initial (%)

Initial (with outdoor temperature as in reference) 80.7 - 94.1 - 18 - 28.1 - + more sunny 79.5 -1.4 92.8 -1.4 17.7 -1.9 27.5 -2.0 + less sunny 81.8 1.5 95.5 1.5 18.4 2.0 28.7 2.1 + more windy 83.4 3.4 96.9 3.0 19.6 8.7 29.9 6.5 + less windy 78.7 -2.4 92.1 -2.2 16.9 -6.0 26.8 -4.6 + more shading 85.9 6.6 100.3 6.6 19.7 9.4 30.8 9.8 + less shading 74.7 -7.4 87.4 -7.1 16 -11.5 25.1 -10.6 + poor envelope 101.7 26.0 115.6 22.8 25.1 39.0 36.0 28.4 + more sunny + more windy 82.2 2.0 95.6 1.5 19.3 6.8 29.3 4.4 + less sunny + less windy 79.9 -1.0 93.5 -0.7 17.3 -4.1 27.4 -2.5 + more sunny + more shading 84.9 5.2 99.0 5.2 19.4 7.6 30.3 7.9 + less sunny + less shading 75.9 -5.9 88.8 -5.7 16.3 -9.6 25.6 -8.8 + more sunny + less shading 73.5 -8.9 86.1 -8.5 15.6 -13.4 24.6 -12.3 + less sunny + more shading 87.1 8.0 101.7 8.1 20.1 11.2 31.4 11.8 + more windy + more shading 88.8 10.1 102.9 9.4 21.4 18.6 32.7 16.5 + more windy + less shading 77.4 -4.1 90.1 -4.2 17.5 -3.2 26.8 -4.6

33

Tabl

e 9a

. Si

mul

ated

fina

l ene

rgy

dem

ands

of t

he L

indv

ägen

bui

ldin

g ve

rsio

ns w

ith th

e pa

ram

eter

s var

iatio

ns a

nd in

tera

ctio

ns

with

the

hour

ly o

utdo

or te

mpe

ratu

re a

s in

the

2013

clim

ate

file

for t

he b

uild

ing

loca

tion.

(Pap

er II

I).

Para

met

er d

escr

iptio

n Ex

istin

g bu

ildin

g ve

rsio

n

Effi

cien

t bui

ldin

g ve

rsio

n

ST

BA

T

ST

B

AT

Spac

e he

atin

g (k

Wh/

m2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Initi

al (w

ith o

utdo

or te

mpe

ratu

re a

s in

refe

renc

e)

80.7

-

94

.1

-

18

-

28.1

-

+ m

ore

sunn

y 79

.5

-1.4

92.8

-1

.4

17

.7

-1.9

27.5

-2

.0

+ le

ss su

nny

81.8

1.

5

95.5

1.

5

18.4

2.

0

28.7

2.

1 +

mor

e w

indy

83

.4

3.4

96

.9

3.0

19

.6

8.7

29

.9

6.5

+ le

ss w

indy

78

.7

-2.4

92.1

-2

.2

16

.9

-6.0

26.8

-4

.6

+ m

ore

shad

ing

85.9

6.

6

100.

3 6.

6

19.7

9.

4

30.8

9.

8 +

less

shad

ing

74.7

-7

.4

87

.4

-7.1

16

-11.

5

25.1

-1

0.6

+ p

oor e

nvel

ope

101.

7 26

.0

11

5.6

22.8

25.1

39

.0

36

.0

28.4

+

mor

e su

nny

+ m

ore

win

dy

82.2

2.

0

95.6

1.

5

19.3

6.

8

29.3

4.

4 +

less

sunn

y +

less

win

dy

79.9

-1

.0

93

.5

-0.7

17.3

-4

.1

27

.4

-2.5

+

mor

e su

nny

+ m

ore

shad

ing

84.9

5.

2

99.0

5.

2

19.4

7.

6

30.3

7.

9 +

less

sunn

y +

less

shad

ing

75.9

-5

.9

88

.8

-5.7

16.3

-9

.6

25

.6

-8.8

+

mor

e su

nny

+ le

ss sh

adin

g 73

.5

-8.9

86.1

-8

.5

15

.6

-13.

4

24.6

-1

2.3

+ le

ss su

nny

+ m

ore

shad

ing

87.1

8.

0

101.

7 8.

1

20.1

11

.2

31

.4

11.8

+

mor

e w

indy

+ m

ore

shad

ing

88.8

10

.1

10

2.9

9.4

21

.4

18.6

32.7

16

.5

+ m

ore

win

dy +

less

shad

ing

77.4

-4

.1

90

.1

-4.2

17.5

-3

.2

26

.8

-4.6

35

Figure 11 illustrates the effect of parameter combinations and assumptions giving the biggest change in space heating for the building versions. Of the considered interactions of parameters and assumptions, the combinations of “warmer outdoor temperature + ST + more sunny + less shading” and “colder outdoor temperature + BAT + less sunny + less windy + more shading + poor envelope” give the lowest and highest simulated space heating demands for the building versions, respectively. For these combinations, the simulated space heating demand decreased by 18% and increased by 64% for the existing building version compared to its reference space heating demand. The corresponding variations for the energy efficient building version are 53% and 51%, respectively.

Figure 11. Parameters combinations and assumptions giving the lowest and highest space heating demand for the existing and energy efficient Lindvägen building versions. (Paper III).

3.3. Space heating and cooling demand under different design strategies

In paper IV different design strategies, including varying proportions of glazed window areas, different façade orientations and different combinations of window thermal transmittances (u-values) and solar transmittances (g-values) to achieve optimised space heating and cooling demands for the Täppan building with different energy efficiency levels are analysed. The improved versions of the buildings are based on individual design strategies resulting in

34

Table 9b. Simulated final energy demands of the Lindvägen building versions with the parameters variations and interactions with the hourly outdoor temperature as in the 2013 climate file for the building location. (Paper III). Parameter description Existing building version Efficient building version

ST BAT

ST

BAT

Space heating (kWh/m2)

Change from Initial (%)

Space heating (kWh/m2)

Change from Initial (%)

Space heating (kWh/m2)

Change from initial (%)

Space heating (kWh/m2)

Change from initial (%)

Initial (with outdoor temperature as in reference) 80.7 - 94.1 - 28.1 - 18 - + more sunny + more windy + more shading 87.7 8.7 101.9 8.3 21.1 16.8 32.1 14.5 + more sunny + more windy + less shading 76.2 -5.5 88.8 -5.6 17.1 -5.1 26.3 -6.3 + less sunny + less windy + more shading 85.0 5.4 99.6 5.9 18.9 4.8 30.0 7.0 + less sunny + less windy + less shading 74.0 -8.3 86.8 -7.8 15.3 -15.3 24.4 -13.0 + more sunny + more windy + more shading + poor envelope 110.0 36.4 124.7 32.5 28.9 60.5 40.8 45.4

+ more sunny + more windy + less shading + poor envelope 96.9 20.1 109.9 16.8 24.2 34.0 34.1 23.8

+ less sunny + more windy + less shading + poor envelope 99.6 23.4 113.0 20.1 25.0 38.9 35.3 25.6

+ less sunny + less windy + more shading + poor envelope 106.5 32.1 121.5 29.2 26.1 44.7 38.1 35.6

+ less sunny + less windy + less shading + poor envelope 93.9 16.4 107.1 13.9 21.7 20.4 31.6 12.6

34

Tabl

e 9b

. Si

mul

ated

fina

l ene

rgy

dem

ands

of t

he L

indv

ägen

bui

ldin

g ve

rsio

ns w

ith th

e pa

ram

eter

s var

iatio

ns a

nd in

tera

ctio

ns

with

the

hour

ly o

utdo

or te

mpe

ratu

re a

s in

the

2013

clim

ate

file

for t

he b

uild

ing

loca

tion.

(Pap

er II

I).

Para

met

er d

escr

iptio

n Ex

istin

g bu

ildin

g ve

rsio

n

Effi

cien

t bui

ldin

g ve

rsio

n

ST

BA

T

ST

B

AT

Spac

e he

atin

g (k

Wh/

m2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

from

In

itial

(%

)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Sp

ace

heat

ing

(kW

h/m

2 )

Cha

nge

fro

m

initi

al

(%)

Initi

al (w

ith o

utdo

or te

mpe

ratu

re a

s in

refe

renc

e)

80.7

-

94

.1

-

28.1

-

18

-

+ m

ore

sunn

y +

mor

e w

indy

+ m

ore

shad

ing

87.7

8.

7

101.

9 8.

3

21.1

16

.8

32

.1

14.5

+

mor

e su

nny

+ m

ore

win

dy +

less

shad

ing

76.2

-5

.5

88

.8

-5.6

17.1

-5

.1

26

.3

-6.3

+

less

sunn

y +

less

win

dy +

mor

e sh

adin

g 85

.0

5.4

99

.6

5.9

18

.9

4.8

30

.0

7.0

+ le

ss su

nny

+ le

ss w

indy

+ le

ss sh

adin

g 74

.0

-8.3

86.8

-7

.8

15

.3

-15.

3

24.4

-1

3.0

+ m

ore

sunn

y +

mor

e w

indy

+ m

ore

shad

ing

+ po

or e

nvel

ope

110.

0 36

.4

12

4.7

32.5

28.9

60

.5

40

.8

45.4

+ m

ore

sunn

y +

mor

e w

indy

+ le

ss sh

adin

g +

poor

env

elop

e 96

.9

20.1

109.

9 16

.8

24

.2

34.0

34.1

23

.8

+ le

ss su

nny

+ m

ore

win

dy +

less

shad

ing

+ po

or

enve

lope

99

.6

23.4

113.

0 20

.1

25

.0

38.9

35.3

25

.6

+ le

ss su

nny

+ le

ss w

indy

+ m

ore

shad

ing

+ po

or

enve

lope

10

6.5

32.1

121.

5 29

.2

26

.1

44.7

38.1

35

.6

+ le

ss su

nny

+ le

ss w

indy

+ le

ss sh

adin

g +

poor

en

velo

pe

93.9

16

.4

10

7.1

13.9

21.7

20

.4

31

.6

12.6

35

Figure 11 illustrates the effect of parameter combinations and assumptions giving the biggest change in space heating for the building versions. Of the considered interactions of parameters and assumptions, the combinations of “warmer outdoor temperature + ST + more sunny + less shading” and “colder outdoor temperature + BAT + less sunny + less windy + more shading + poor envelope” give the lowest and highest simulated space heating demands for the building versions, respectively. For these combinations, the simulated space heating demand decreased by 18% and increased by 64% for the existing building version compared to its reference space heating demand. The corresponding variations for the energy efficient building version are 53% and 51%, respectively.

Figure 11. Parameters combinations and assumptions giving the lowest and highest space heating demand for the existing and energy efficient Lindvägen building versions. (Paper III).

3.3. Space heating and cooling demand under different design strategies

In paper IV different design strategies, including varying proportions of glazed window areas, different façade orientations and different combinations of window thermal transmittances (u-values) and solar transmittances (g-values) to achieve optimised space heating and cooling demands for the Täppan building with different energy efficiency levels are analysed. The improved versions of the buildings are based on individual design strategies resulting in

37

energy of the initial and improved (after implemented design strategies) building versions. The variations in the production primary energy use for the initial buildings are mainly due to the different insulation material thicknesses required in the external envelope components to achieve their respective energy efficiency levels. Steel and concrete contribute most to the production primary energy use, representing about 43% and 33% of the total primary energy for production of the initial building versions, respectively. The production primary energy use of the improved building versions after implemented design strategies to optimise their space heating and cooling demands increased by 4 kWh per m2 and year (14%) each for the BBR 2012 and “As built” and 3 kWh per m2 and year (10%) for the Passive 2012 buildings, compared to their respective initial versions. The assumed lifetime of the building versions is 50 years.

Figure 13. Annual primary energy use for production of the building versions before (Initial) and after (Improved) implemented design strategies to optimise their space heating and cooling demand. (Adapted from Paper IV).

3.4. Space heating and cooling demand under climate change

The effects of different climate scenarios on space heating and cooling demand are analysed for the Täppan building in Paper V. The future climate datasets are based on the Representative Concentration Pathway scenarios for

36

the lowest space heating and cooling demand for the building versions (Table 10). The variations in the annual space heating and cooling demands of the building versions are given in Figure 12, showing that the demands for the improved building versions are significantly reduced, especially for the Passive 2012 building version. Table 10. Individual design strategies giving the lowest space heating and cooling demand for the building versions. (Paper IV) Design strategies Building energy efficiency levels

BRR 2012 “As built” Passive 2012 Window areas (%) Minus 40% - All Minus 40% - All Minus 40% - All Orientation South South North u-value (W/m2K) 0.4 0.4 0.4 g-value 0.4 0.4 0.2

Figure 12. Annual final space heating and cooling demands for the initial and improved building versions. (Adapted from Paper IV).

Several design strategies may be employed to achieve lower operation energy use in buildings, including different proportions of glazed window areas and façade orientations as well as different combinations of window u-values and g-values. However, the choice of window types and sizes may also influence the quantities of building materials and hence their production primary energy use. Implications of such design strategies on the production primary energy use of the Täppan building with different energy efficiency levels are analysed in Paper IV. Figure 13 shows the production primary

37

energy of the initial and improved (after implemented design strategies) building versions. The variations in the production primary energy use for the initial buildings are mainly due to the different insulation material thicknesses required in the external envelope components to achieve their respective energy efficiency levels. Steel and concrete contribute most to the production primary energy use, representing about 43% and 33% of the total primary energy for production of the initial building versions, respectively. The production primary energy use of the improved building versions after implemented design strategies to optimise their space heating and cooling demands increased by 4 kWh per m2 and year (14%) each for the BBR 2012 and “As built” and 3 kWh per m2 and year (10%) for the Passive 2012 buildings, compared to their respective initial versions. The assumed lifetime of the building versions is 50 years.

Figure 13. Annual primary energy use for production of the building versions before (Initial) and after (Improved) implemented design strategies to optimise their space heating and cooling demand. (Adapted from Paper IV).

3.4. Space heating and cooling demand under climate change

The effects of different climate scenarios on space heating and cooling demand are analysed for the Täppan building in Paper V. The future climate datasets are based on the Representative Concentration Pathway scenarios for

36

the lowest space heating and cooling demand for the building versions (Table 10). The variations in the annual space heating and cooling demands of the building versions are given in Figure 12, showing that the demands for the improved building versions are significantly reduced, especially for the Passive 2012 building version. Table 10. Individual design strategies giving the lowest space heating and cooling demand for the building versions. (Paper IV) Design strategies Building energy efficiency levels

BRR 2012 “As built” Passive 2012 Window areas (%) Minus 40% - All Minus 40% - All Minus 40% - All Orientation South South North u-value (W/m2K) 0.4 0.4 0.4 g-value 0.4 0.4 0.2

Figure 12. Annual final space heating and cooling demands for the initial and improved building versions. (Adapted from Paper IV).

Several design strategies may be employed to achieve lower operation energy use in buildings, including different proportions of glazed window areas and façade orientations as well as different combinations of window u-values and g-values. However, the choice of window types and sizes may also influence the quantities of building materials and hence their production primary energy use. Implications of such design strategies on the production primary energy use of the Täppan building with different energy efficiency levels are analysed in Paper IV. Figure 13 shows the production primary

39

Figure 15. Annual final space heating and cooling demands of the building versions after implemented strategies and measures under different climate scenarios. (Adapted from Paper V).

The simulated annual hourly indoor temperature profiles of the Passive 2012 building version under the climate scenarios before and after the implemented strategies are shown in Figure 16. Indoor temperatures exceeded the cooling set point by 41-47% of the total operating hours for the initial building versions. Based on the overheating temperature threshold of 28 ºC for not more than 1% of annual occupied time suggested by [100], overheating occurs for the Passive 2012 building version under the considered climates with the proportion of overheating hours ranging between 39-44%. The proportion of overheating hours reduced significantly to 0.1-10% after the implemented strategies and overheating is avoided except under RCP4.5-2090s. The observed trend is similar for the BBR 2015 building version but with lesser magnitude (Paper V).

38

2050-2059 (2050s) and 2090-2099 (2090s). Figure 14 shows the variations in annual space heating and cooling demands of the initial building versions under the different climate scenarios. The initial building versions are assumed to have standard household equipment and technical installations. Space heating demand decreases, while space cooling demand increases for both building versions under the recent (1996-2005) and future climate scenarios, compared to the reference climate of 1961-1990. Cooling demand becomes more significant for the Passive 2012 building version under the recent and future climate scenarios. The effectiveness of different design strategies and measures to minimise space heating and cooling demands for the building versions under future climate scenarios are also investigated in Paper V. The considered strategies and measures include household equipment and technical installations based on best available technology (BAT), bypassing the VHR unit when cooling is required, solar shading of windows, combinations of window u- and g-values, different proportions of glazed window areas and façade orientations and mechanical cooling. Figure 15 shows the variations in annual final space heating and cooling demands for the building versions after implementing all the considered strategies. Overall, space cooling is significantly reduced while space heating increased slightly (mainly form household equipment based on BAT) for the building versions under the different climate scenarios.

Figure 14. Annual final space heating and cooling demands for initial building versions with standard technology under different climate scenarios. (Adapted from Paper V).

39

Figure 15. Annual final space heating and cooling demands of the building versions after implemented strategies and measures under different climate scenarios. (Adapted from Paper V).

The simulated annual hourly indoor temperature profiles of the Passive 2012 building version under the climate scenarios before and after the implemented strategies are shown in Figure 16. Indoor temperatures exceeded the cooling set point by 41-47% of the total operating hours for the initial building versions. Based on the overheating temperature threshold of 28 ºC for not more than 1% of annual occupied time suggested by [100], overheating occurs for the Passive 2012 building version under the considered climates with the proportion of overheating hours ranging between 39-44%. The proportion of overheating hours reduced significantly to 0.1-10% after the implemented strategies and overheating is avoided except under RCP4.5-2090s. The observed trend is similar for the BBR 2015 building version but with lesser magnitude (Paper V).

38

2050-2059 (2050s) and 2090-2099 (2090s). Figure 14 shows the variations in annual space heating and cooling demands of the initial building versions under the different climate scenarios. The initial building versions are assumed to have standard household equipment and technical installations. Space heating demand decreases, while space cooling demand increases for both building versions under the recent (1996-2005) and future climate scenarios, compared to the reference climate of 1961-1990. Cooling demand becomes more significant for the Passive 2012 building version under the recent and future climate scenarios. The effectiveness of different design strategies and measures to minimise space heating and cooling demands for the building versions under future climate scenarios are also investigated in Paper V. The considered strategies and measures include household equipment and technical installations based on best available technology (BAT), bypassing the VHR unit when cooling is required, solar shading of windows, combinations of window u- and g-values, different proportions of glazed window areas and façade orientations and mechanical cooling. Figure 15 shows the variations in annual final space heating and cooling demands for the building versions after implementing all the considered strategies. Overall, space cooling is significantly reduced while space heating increased slightly (mainly form household equipment based on BAT) for the building versions under the different climate scenarios.

Figure 14. Annual final space heating and cooling demands for initial building versions with standard technology under different climate scenarios. (Adapted from Paper V).

41

(a) Space heating (b) Space cooling Figure 17. Annual final space heating (a) and space cooling (b) demands for building versions with implemented strategies under different climate scenarios. Error bars show corresponding demands for RCP2.6 and RCP8.5 from top to down for space heating and from down to top for space cooling. (Paper V).

3.5. Operation primary energy use under different design strategies and heat supply options

The effect of different design strategies on the primary energy use for space heating and cooling of the building versions with heat supply based on CHP or HOB is investigated in Paper IV under current climate. Table 11 gives a summary of the individual design strategies, resulting in the lowest annual primary energy use for space heating and cooling for the building versions. Window orientations and g-values giving the lowest energy use vary depending on whether the approach is based on achieving the lowest space heating and cooling demand (Table 10) or the lowest primary energy use for space heating and cooling (Table 11).

40

(a) Before implemented strategies

(b) After implemented strategies Figure 16. Annual hourly indoor air temperature profile for the Passive 2012 building version before and after all implemented design strategies. (Adapted from Paper V).

Figure 17 presents the effects of the implemented design strategies on the annual space heating and cooling demands of the building versions for RCPs 2.6 and 8.5 (error bars) relative to RCP4.5 and compared to the reference and recent climates (main bars). Space heating demand for end of century increased slightly (about 1%) for both building versions compared to that for mid-century under RCP2.6. The variation in space heating is more significant for the same periods under RCP8.5.

41

(a) Space heating (b) Space cooling Figure 17. Annual final space heating (a) and space cooling (b) demands for building versions with implemented strategies under different climate scenarios. Error bars show corresponding demands for RCP2.6 and RCP8.5 from top to down for space heating and from down to top for space cooling. (Paper V).

3.5. Operation primary energy use under different design strategies and heat supply options

The effect of different design strategies on the primary energy use for space heating and cooling of the building versions with heat supply based on CHP or HOB is investigated in Paper IV under current climate. Table 11 gives a summary of the individual design strategies, resulting in the lowest annual primary energy use for space heating and cooling for the building versions. Window orientations and g-values giving the lowest energy use vary depending on whether the approach is based on achieving the lowest space heating and cooling demand (Table 10) or the lowest primary energy use for space heating and cooling (Table 11).

40

(a) Before implemented strategies

(b) After implemented strategies Figure 16. Annual hourly indoor air temperature profile for the Passive 2012 building version before and after all implemented design strategies. (Adapted from Paper V).

Figure 17 presents the effects of the implemented design strategies on the annual space heating and cooling demands of the building versions for RCPs 2.6 and 8.5 (error bars) relative to RCP4.5 and compared to the reference and recent climates (main bars). Space heating demand for end of century increased slightly (about 1%) for both building versions compared to that for mid-century under RCP2.6. The variation in space heating is more significant for the same periods under RCP8.5.

43

Figure 19. Annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving lowest primary energy with space heating based on HOB. (Adapted from Paper IV).

The shares of primary energy use for production and for space heating, space cooling and ventilation over an assumed 50 year lifespan are presented in Figure 20 for the initial and improved building versions with space heating based on CHP. The production primary energy use is proportionally more significant for the improved building versions and more so with higher energy efficiency levels. Still, total primary energy use decreased by 10-18% for the improved building versions.

Figure 20. Primary energy use for production and for space heating, space cooling and ventilation over 50 years for the initial and improved building versions with space heating based on CHP. (Paper IV).

42

Table 11. Individual design strategies giving the lowest primary energy use for space heating and cooling for the building versions based on different supply systems. (Paper IV) Design strategies Building energy efficiency levels

BBR 2012 ”As built” Passive 2012 CHP HOB CHP HOB CHP HOB

Windows areas (%) Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Orientation North North North North North North u-value (W/m2k) 0.4 0.4 0.4 0.4 0.4 0.4 g-value 0.2 0.4 0.2 0.2 0.2 0.2

Figure 18 and Figure 19 show the annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving the lowest primary energy use (Table 11) when space heating is based on CHP and HOB, respectively. The primary energy use for space heating is significantly lower when the heat supply is from CHP rather than HOB. The total annual primary energy use for space heating and cooling for the improved building versions decreased between 29-67% and 28-58% when the space heating is based on CHP and HOB, respectively compared to that of the initial versions.

Figure 18. Annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving lowest primary energy with space heating based on CHP. (Adapted from Paper IV).

43

Figure 19. Annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving lowest primary energy with space heating based on HOB. (Adapted from Paper IV).

The shares of primary energy use for production and for space heating, space cooling and ventilation over an assumed 50 year lifespan are presented in Figure 20 for the initial and improved building versions with space heating based on CHP. The production primary energy use is proportionally more significant for the improved building versions and more so with higher energy efficiency levels. Still, total primary energy use decreased by 10-18% for the improved building versions.

Figure 20. Primary energy use for production and for space heating, space cooling and ventilation over 50 years for the initial and improved building versions with space heating based on CHP. (Paper IV).

42

Table 11. Individual design strategies giving the lowest primary energy use for space heating and cooling for the building versions based on different supply systems. (Paper IV) Design strategies Building energy efficiency levels

BBR 2012 ”As built” Passive 2012 CHP HOB CHP HOB CHP HOB

Windows areas (%) Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Minus 40% - All

Orientation North North North North North North u-value (W/m2k) 0.4 0.4 0.4 0.4 0.4 0.4 g-value 0.2 0.4 0.2 0.2 0.2 0.2

Figure 18 and Figure 19 show the annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving the lowest primary energy use (Table 11) when space heating is based on CHP and HOB, respectively. The primary energy use for space heating is significantly lower when the heat supply is from CHP rather than HOB. The total annual primary energy use for space heating and cooling for the improved building versions decreased between 29-67% and 28-58% when the space heating is based on CHP and HOB, respectively compared to that of the initial versions.

Figure 18. Annual primary energy use for space heating and space cooling for the initial and improved building versions based on combination of strategies giving lowest primary energy with space heating based on CHP. (Adapted from Paper IV).

45

4. Discussion and Conclusions

4.1. Primary energy use and CO2 emission for materials production

The application of extra insulation materials to the studied buildings reduce the operating primary energy use but more primary energy is needed for the insulation material production, that also slightly increasing the CO2 emissions from the material production. The increases in primary energy use and CO2 emissions are mainly due to the differences in the quantities and manufacturing processes of the various materials required for the construction of the studied buildings. For example, rock wool insulation used in the initial building versions (Paper I) is produced from raw materials, which require more energy to be extracted and transported and the production process is more fossil fuel intensive, compared to cellulose fiber. The substitution of rock wool in the improved Passivhus 2012 building with cellulose fiber reduces the primary energy use for insulation material production by 40%. Additionally, the use of material production electricity input from a natural gas-fired plant instead of coal-fired plant further results in reduced primary energy use and CO2 emissions for the material production.

The use of insulation to improve envelope thermal performance of both new and existing old buildings is important, among others in achieving energy efficient buildings. Therefore, financial incentives exist in many countries to improve the insulation of existing buildings and their airtightness [101]. Such policies may also include incentives for renewable based materials, for example insulation and building frame materials, to reduce primary energy use and GHG emissions for building material production.

44

3.6. Operation primary energy use under different design strategies and climate scenarios

The effectiveness of cumulative implementation of different design strategies and measures in reducing the primary energy use for operating the Täppan building for BBR 2012 and passive 2012 versions under different climate scenarios is presented in Table 12. The operation primary energy use includes space heating, space cooling, tap water heating and electricity for household appliances, lighting, fans and pumps. Space heating and tap water heating is based on CHP plant. Mechanical cooling is assumed to meet the remaining cooling demands after implementing each strategy and measure. Household equipment and technical installations based on BAT gives the biggest decrease in primary energy use for both building versions, while the effectiveness of the other design strategies in reducing primary energy use varies depending on the energy performance of the building versions and the climate scenarios.

Table 12. Total annual primary energy use (kWh/m2) for operating the building versions before and after implementing different design strategies and measures cumulatively under different climate scenarios (Paper V). Heating is based on CHP plants. Description RCP4.5-

2050s RCP2.6-2050s

RCP8.5-2050s

RCP4.5-2090s

RCP2.6-2090s

RCP8.5-2090s

BBR 2015 Initial with standard

technology 149.2

150.4 148.5

152.2 150.4 149.5

+ BAT 95.5 97.4 94.2 97.6 97.4 93.7 + Bypass of VHR unit 94.7 96.8 93.2 96.6 96.8 92.7 + Shading 92.7 95.4 91.2 93.4 95.5 87.8 + U and g-values 91.9 94.9 90.3 93.4 95.1 86.1 + Orientation 91.8 93.9 90.2 93.4 94.1 85.8 + Window areas 91.4 93.8 89.7 92.1 94.0 84.6 Passive 2012

Initial with standard technology

135.7

135.0 135.7

137.9 134.7 139.5

+ BAT 77.8 77.4 77.6 79.8 77.2 79.9 + Bypass of VHR unit 75.3 74.9 75.3 77.6 74.8 78.1 + Shading 70.2 70.5 69.7 71.3 70.5 70.8 + U and g-values 67.9 69.1 67.3 68.3 69.2 66.3 + Orientation 67.8 69.1 67.2 68.1 69.2 65.9 + Window areas 66.5 67.7 66.0 66.6 67.9 64.6

45

4. Discussion and Conclusions

4.1. Primary energy use and CO2 emission for materials production

The application of extra insulation materials to the studied buildings reduce the operating primary energy use but more primary energy is needed for the insulation material production, that also slightly increasing the CO2 emissions from the material production. The increases in primary energy use and CO2 emissions are mainly due to the differences in the quantities and manufacturing processes of the various materials required for the construction of the studied buildings. For example, rock wool insulation used in the initial building versions (Paper I) is produced from raw materials, which require more energy to be extracted and transported and the production process is more fossil fuel intensive, compared to cellulose fiber. The substitution of rock wool in the improved Passivhus 2012 building with cellulose fiber reduces the primary energy use for insulation material production by 40%. Additionally, the use of material production electricity input from a natural gas-fired plant instead of coal-fired plant further results in reduced primary energy use and CO2 emissions for the material production.

The use of insulation to improve envelope thermal performance of both new and existing old buildings is important, among others in achieving energy efficient buildings. Therefore, financial incentives exist in many countries to improve the insulation of existing buildings and their airtightness [101]. Such policies may also include incentives for renewable based materials, for example insulation and building frame materials, to reduce primary energy use and GHG emissions for building material production.

44

3.6. Operation primary energy use under different design strategies and climate scenarios

The effectiveness of cumulative implementation of different design strategies and measures in reducing the primary energy use for operating the Täppan building for BBR 2012 and passive 2012 versions under different climate scenarios is presented in Table 12. The operation primary energy use includes space heating, space cooling, tap water heating and electricity for household appliances, lighting, fans and pumps. Space heating and tap water heating is based on CHP plant. Mechanical cooling is assumed to meet the remaining cooling demands after implementing each strategy and measure. Household equipment and technical installations based on BAT gives the biggest decrease in primary energy use for both building versions, while the effectiveness of the other design strategies in reducing primary energy use varies depending on the energy performance of the building versions and the climate scenarios.

Table 12. Total annual primary energy use (kWh/m2) for operating the building versions before and after implementing different design strategies and measures cumulatively under different climate scenarios (Paper V). Heating is based on CHP plants. Description RCP4.5-

2050s RCP2.6-2050s

RCP8.5-2050s

RCP4.5-2090s

RCP2.6-2090s

RCP8.5-2090s

BBR 2015 Initial with standard

technology 149.2

150.4 148.5

152.2 150.4 149.5

+ BAT 95.5 97.4 94.2 97.6 97.4 93.7 + Bypass of VHR unit 94.7 96.8 93.2 96.6 96.8 92.7 + Shading 92.7 95.4 91.2 93.4 95.5 87.8 + U and g-values 91.9 94.9 90.3 93.4 95.1 86.1 + Orientation 91.8 93.9 90.2 93.4 94.1 85.8 + Window areas 91.4 93.8 89.7 92.1 94.0 84.6 Passive 2012

Initial with standard technology

135.7

135.0 135.7

137.9 134.7 139.5

+ BAT 77.8 77.4 77.6 79.8 77.2 79.9 + Bypass of VHR unit 75.3 74.9 75.3 77.6 74.8 78.1 + Shading 70.2 70.5 69.7 71.3 70.5 70.8 + U and g-values 67.9 69.1 67.3 68.3 69.2 66.3 + Orientation 67.8 69.1 67.2 68.1 69.2 65.9 + Window areas 66.5 67.7 66.0 66.6 67.9 64.6

47

in a building is essential to accurately calculate space heating demand of buildings, particularly for a low energy building. Currently, the building energy regulation approach in several European countries as in Sweden and Denmark, focuses on energy demand for space heating, tap water heating and electricity used for fans and pumps and exclude electricity for household appliances and lighting. However, household electricity use interacts strongly with and has significant impact on space heating and cooling demands of buildings (Papers II, III and V). For accurate estimation of buildings’ space heating demand, analyses need to address all electricity use within buildings, including electricity for household appliances and lighting.

Accurate analyses of energy performance of buildings require that sensitive key input parameters and assumptions are established based on expected building thermal performance, electricity consumption, energy efficiency levels of lighting and electrical appliances, and number of building occupants. Assumptions regarding sensitive climate related parameters such as outdoor temperature, ground solar reflection and window shading factor should consider site specific conditions of the building location.

4.3. Climate scenarios and design strategies The space heating and cooling demands of the analysed building versions vary significantly with energy performance of the buildings and climate scenarios (Papers IV and V). Space heating demand decreases while space cooling demand as well as the risk of overheating increases considerably with warmer climate. The space cooling demand for the Passive 2012 building version becomes more significant than space heating under current and future climates.

The combination of design strategies resulting in the improved building versions in Paper IV varies depending on if the lowest space heating and cooling demand or the lowest primary energy use is given priority. Orientation of the largest window areas and g-values seem to be sensitive to the choice of approach, while the share of window areas and the window u-values are not.

Overall, significant reductions are achieved in the operation final energy demands of the building versions and overheating is avoided or greatly reduced when different design strategies and measures are implemented cumulatively under different climate change scenarios. As the number of low

46

Buildings are constructed with combinations of materials in different quantities with varying energetic and GHG emission implications. In Paper IV, the improved building versions are mainly due to increased material use in the building envelope elements such as triple and quadruple glazed windows, more concrete, steel and insulation materials in the external walls when the window areas are decreased, among others. That increased production primary energy use for the improved building versions and imply that such strategies should be considered in a system wide perspective considering both the production and operation phases.

The results of the analyses suggest that choice of building materials based on renewable raw materials with low production energy use could be important in an overall strategy to reduce primary energy use and GHG emissions in the building sector.

4.2. Input parameter values and assumptions Input data and assumptions used for energy balance simulations of buildings vary widely in the Swedish context and result in significant differences in space heating and cooling demands. The calculated final space heating demand varied by 75 kWh/m2 when the studied building is simulated with extremes of datasets screened from various Swedish studies and reports. The calculated energy savings for efficient new windows ranged from 18 to 31 kWh/m2. The corresponding values are 19 to 29 kWh/m2 for VHR, and 6 to 23 kWh/m2 for extra insulation to exterior walls.

Of the parameters explored, the assumed indoor air temperature, internal heat gains and efficiency of VHR had significant influence on the simulated energy performance of the studied building as on the energy efficiency measures. The assumptions regarding outdoor temperature, ground solar reflection and window shading factor have relatively higher impact on the simulated space heating and cooling demands than other climate related parameters. Air pressure outside and the percentage of wind load that hits the building had a minor impact on the simulated energy performances.

The impact of parameter interactions on calculated space heating of buildings is rather small but increase with more parameter combinations and more energy efficient buildings (Papers III). Detailed energy characterisation of household appliances and lighting as well as the technical installations used

47

in a building is essential to accurately calculate space heating demand of buildings, particularly for a low energy building. Currently, the building energy regulation approach in several European countries as in Sweden and Denmark, focuses on energy demand for space heating, tap water heating and electricity used for fans and pumps and exclude electricity for household appliances and lighting. However, household electricity use interacts strongly with and has significant impact on space heating and cooling demands of buildings (Papers II, III and V). For accurate estimation of buildings’ space heating demand, analyses need to address all electricity use within buildings, including electricity for household appliances and lighting.

Accurate analyses of energy performance of buildings require that sensitive key input parameters and assumptions are established based on expected building thermal performance, electricity consumption, energy efficiency levels of lighting and electrical appliances, and number of building occupants. Assumptions regarding sensitive climate related parameters such as outdoor temperature, ground solar reflection and window shading factor should consider site specific conditions of the building location.

4.3. Climate scenarios and design strategies The space heating and cooling demands of the analysed building versions vary significantly with energy performance of the buildings and climate scenarios (Papers IV and V). Space heating demand decreases while space cooling demand as well as the risk of overheating increases considerably with warmer climate. The space cooling demand for the Passive 2012 building version becomes more significant than space heating under current and future climates.

The combination of design strategies resulting in the improved building versions in Paper IV varies depending on if the lowest space heating and cooling demand or the lowest primary energy use is given priority. Orientation of the largest window areas and g-values seem to be sensitive to the choice of approach, while the share of window areas and the window u-values are not.

Overall, significant reductions are achieved in the operation final energy demands of the building versions and overheating is avoided or greatly reduced when different design strategies and measures are implemented cumulatively under different climate change scenarios. As the number of low

46

Buildings are constructed with combinations of materials in different quantities with varying energetic and GHG emission implications. In Paper IV, the improved building versions are mainly due to increased material use in the building envelope elements such as triple and quadruple glazed windows, more concrete, steel and insulation materials in the external walls when the window areas are decreased, among others. That increased production primary energy use for the improved building versions and imply that such strategies should be considered in a system wide perspective considering both the production and operation phases.

The results of the analyses suggest that choice of building materials based on renewable raw materials with low production energy use could be important in an overall strategy to reduce primary energy use and GHG emissions in the building sector.

4.2. Input parameter values and assumptions Input data and assumptions used for energy balance simulations of buildings vary widely in the Swedish context and result in significant differences in space heating and cooling demands. The calculated final space heating demand varied by 75 kWh/m2 when the studied building is simulated with extremes of datasets screened from various Swedish studies and reports. The calculated energy savings for efficient new windows ranged from 18 to 31 kWh/m2. The corresponding values are 19 to 29 kWh/m2 for VHR, and 6 to 23 kWh/m2 for extra insulation to exterior walls.

Of the parameters explored, the assumed indoor air temperature, internal heat gains and efficiency of VHR had significant influence on the simulated energy performance of the studied building as on the energy efficiency measures. The assumptions regarding outdoor temperature, ground solar reflection and window shading factor have relatively higher impact on the simulated space heating and cooling demands than other climate related parameters. Air pressure outside and the percentage of wind load that hits the building had a minor impact on the simulated energy performances.

The impact of parameter interactions on calculated space heating of buildings is rather small but increase with more parameter combinations and more energy efficient buildings (Papers III). Detailed energy characterisation of household appliances and lighting as well as the technical installations used

49

primary energy use for space heating and cooling, tap water heating, electricity for household appliances, lighting as well as fans and pumps is reduced by 37-43% and 48-54% for the BBR 2015 and Passive 2012 building versions, respectively when all the design strategies and measures are implemented under the different climate scenarios (Paper V). BAT gives the biggest decrease in total primary energy use for the building versions under all the considered climate scenarios. This is followed by window u- and g-values for the BBR 2015 building version under the reference and recent climates. Shading consistently gives the second biggest decrease in primary energy use for the Passive 2012 building version under all climate scenarios as well as for the BBR 2015 building version under future climate scenarios. Varying the share of window areas and orientations has a minor impact on primary energy use when implemented after all other strategies. This implies that other design strategies and measures should be prioritised instead of changing shares of window areas and orientations to reduce primary energy use under climate change. Considering a 50 year life time for windows, the choice of windows especially for new buildings may be based on optimised options taking into account the impacts of climate change e.g. for the coming 50 years.

Overall, these analyses suggest that significant primary energy reductions are achievable under climate change, if new buildings are designed with appropriate strategies.

4.5. Uncertainties The specific energy use for material production may vary due to geographical location, production technologies and availability of natural resources. The efficiency and fuel input of production processes may also improve depending on technological advancement and relevant policies. Data for specific end-use energy for materials production in this study is mainly from [85, 102]. Though this represents a relatively old data source, it is well representative of the building material production industry in Sweden, where the analysed buildings are located. Nevertheless, sensitivity analyses were conducted with data from a more recent study for selected materials to assess the impacts of improved efficiency and technology in material production (Paper I). The results show lower primary energy use and CO2 emissions with the relatively more recent data. Still, the production primary energy of the insulation materials based on

48

energy buildings is expected to increase across the EU in line with stringent regulations, these findings suggest that strategies to minimise both space heating and cooling demands need to be incorporated in the design of such buildings considering potential climate change.

4.4. Primary energy use for building production and operation

The individual strategies giving the lowest primary energy use for space heating and cooling for the building versions do not vary depending on whether the space heating is from CHP or HOB except for the g-values of the BBR 2012 building version. For the improved building versions based on combination of strategies giving the lowest primary energy use, the total primary energy for operation varies between heat supply from CHP and HOB. Aiming at the lowest space heating and cooling demand, the primary energy use for space heating of the improved building versions is significantly reduced compared to that for space cooling. Aiming at the lowest primary energy use, the space cooling demand is much more reduced than the space heating demand, in particular when the heat supply is from CHP. The primary energy efficiency of heat supply systems depends on the heat production technology and type of fuel use. When the heat supply of the building versions is from CHP, the primary energy use for space heating is significantly lower than when the heat supply is from HOB.

Over an assumed 50 year lifespan, the share of building production primary energy use of the initial building versions represents 31-42% of the total primary energy use for production, space heating, space cooling and ventilation, while that of the improved versions represents 39-54% when heat supply is from CHP. The corresponding numbers are 23-37% and 30-50% when heat supply is from HOB. The share of production primary energy use is proportionally more significant for the building versions with higher energy efficiency. Overall, the total primary energy use for production and for space heating, space cooling and ventilation is decreased by 10-18% for the improved building versions.

The primary energy use for space heating, space cooling and ventilation for the buildings with implemented design strategies and measures in Paper IV was in average reduced by 27%, compared to their initial versions. The annual

49

primary energy use for space heating and cooling, tap water heating, electricity for household appliances, lighting as well as fans and pumps is reduced by 37-43% and 48-54% for the BBR 2015 and Passive 2012 building versions, respectively when all the design strategies and measures are implemented under the different climate scenarios (Paper V). BAT gives the biggest decrease in total primary energy use for the building versions under all the considered climate scenarios. This is followed by window u- and g-values for the BBR 2015 building version under the reference and recent climates. Shading consistently gives the second biggest decrease in primary energy use for the Passive 2012 building version under all climate scenarios as well as for the BBR 2015 building version under future climate scenarios. Varying the share of window areas and orientations has a minor impact on primary energy use when implemented after all other strategies. This implies that other design strategies and measures should be prioritised instead of changing shares of window areas and orientations to reduce primary energy use under climate change. Considering a 50 year life time for windows, the choice of windows especially for new buildings may be based on optimised options taking into account the impacts of climate change e.g. for the coming 50 years.

Overall, these analyses suggest that significant primary energy reductions are achievable under climate change, if new buildings are designed with appropriate strategies.

4.5. Uncertainties The specific energy use for material production may vary due to geographical location, production technologies and availability of natural resources. The efficiency and fuel input of production processes may also improve depending on technological advancement and relevant policies. Data for specific end-use energy for materials production in this study is mainly from [85, 102]. Though this represents a relatively old data source, it is well representative of the building material production industry in Sweden, where the analysed buildings are located. Nevertheless, sensitivity analyses were conducted with data from a more recent study for selected materials to assess the impacts of improved efficiency and technology in material production (Paper I). The results show lower primary energy use and CO2 emissions with the relatively more recent data. Still, the production primary energy of the insulation materials based on

48

energy buildings is expected to increase across the EU in line with stringent regulations, these findings suggest that strategies to minimise both space heating and cooling demands need to be incorporated in the design of such buildings considering potential climate change.

4.4. Primary energy use for building production and operation

The individual strategies giving the lowest primary energy use for space heating and cooling for the building versions do not vary depending on whether the space heating is from CHP or HOB except for the g-values of the BBR 2012 building version. For the improved building versions based on combination of strategies giving the lowest primary energy use, the total primary energy for operation varies between heat supply from CHP and HOB. Aiming at the lowest space heating and cooling demand, the primary energy use for space heating of the improved building versions is significantly reduced compared to that for space cooling. Aiming at the lowest primary energy use, the space cooling demand is much more reduced than the space heating demand, in particular when the heat supply is from CHP. The primary energy efficiency of heat supply systems depends on the heat production technology and type of fuel use. When the heat supply of the building versions is from CHP, the primary energy use for space heating is significantly lower than when the heat supply is from HOB.

Over an assumed 50 year lifespan, the share of building production primary energy use of the initial building versions represents 31-42% of the total primary energy use for production, space heating, space cooling and ventilation, while that of the improved versions represents 39-54% when heat supply is from CHP. The corresponding numbers are 23-37% and 30-50% when heat supply is from HOB. The share of production primary energy use is proportionally more significant for the building versions with higher energy efficiency. Overall, the total primary energy use for production and for space heating, space cooling and ventilation is decreased by 10-18% for the improved building versions.

The primary energy use for space heating, space cooling and ventilation for the buildings with implemented design strategies and measures in Paper IV was in average reduced by 27%, compared to their initial versions. The annual

51

5. Future work

Innovative insulation materials and systems, e.g. vacuum insulation panels, aerogel, gas filled panel insulation are reported to have significantly higher thermal performance compared to conventional insulation materials. Therefore, building envelopes with such systems can have higher energy efficiency than with conventional insulation materials. The analysis in Paper I could be expanded to explore the implications of such innovative materials over the complete building life cycle. Such analyses could seek to minimise the primary energy use of operation and production phases as well as the economic performance of such materials in comparison with conventional materials.

The influence of different types of frame materials on building production energy use has been emphasised in several studies [19, 105, 106], especially for low energy buildings. Wood framed buildings are increasingly associated with lower life cycle primary energy use and CO2 emissions due to the lower production energy and higher end-of-life benefits compared to similar concrete-framed buildings and higher net processing CO2 emissions for concrete buildings. The thermal mass of frame material may influence building operation energy use but the benefit of thermal mass is suggested to be minor for buildings in cold climates [107-109]. As the energy use profile of buildings may change under future climates, further studies may analyse how different design strategies could be used for wooden and concrete building systems, considering their interactions with different energy supply options to minimise life cycle primary energy use and GHG emissions.

Climate change may also influence energy supply for buildings. Demand for electricity is generally expected to increase due to greater needs for space cooling [6]. In this research, analysis of space cooling is assumed to be based

50

the two datasets follow similar trends, with cellulose fiber giving the lowest primary energy followed by rock wool and glass wool.

Uncertainties related to climate models and projection of future climate data may affect simulation results. Nik and Kalagasidis [103] assessed the effect of several climate uncertainties on the energy performance of residential buildings in Stockholm, Sweden. They observed similar trends of heating demand reductions and cooling demand increases as in Paper V but to various extents depending on the climate model used. Global Climate models (GCMs) are reported as the most advanced tools currently available for simulating the response of the global climate system to increased GHG concentrations [104]. Future climate projections are based on advanced and high resolution GCMs, which continue to improve over time. Our analyses in Paper V are based on the recent climate scenarios released by the IPCC to minimise these uncertainties.

Uncertainties linked to simulation input parameters and assumptions for building energy balance calculations were the main focus in Papers II and III.

51

5. Future work

Innovative insulation materials and systems, e.g. vacuum insulation panels, aerogel, gas filled panel insulation are reported to have significantly higher thermal performance compared to conventional insulation materials. Therefore, building envelopes with such systems can have higher energy efficiency than with conventional insulation materials. The analysis in Paper I could be expanded to explore the implications of such innovative materials over the complete building life cycle. Such analyses could seek to minimise the primary energy use of operation and production phases as well as the economic performance of such materials in comparison with conventional materials.

The influence of different types of frame materials on building production energy use has been emphasised in several studies [19, 105, 106], especially for low energy buildings. Wood framed buildings are increasingly associated with lower life cycle primary energy use and CO2 emissions due to the lower production energy and higher end-of-life benefits compared to similar concrete-framed buildings and higher net processing CO2 emissions for concrete buildings. The thermal mass of frame material may influence building operation energy use but the benefit of thermal mass is suggested to be minor for buildings in cold climates [107-109]. As the energy use profile of buildings may change under future climates, further studies may analyse how different design strategies could be used for wooden and concrete building systems, considering their interactions with different energy supply options to minimise life cycle primary energy use and GHG emissions.

Climate change may also influence energy supply for buildings. Demand for electricity is generally expected to increase due to greater needs for space cooling [6]. In this research, analysis of space cooling is assumed to be based

50

the two datasets follow similar trends, with cellulose fiber giving the lowest primary energy followed by rock wool and glass wool.

Uncertainties related to climate models and projection of future climate data may affect simulation results. Nik and Kalagasidis [103] assessed the effect of several climate uncertainties on the energy performance of residential buildings in Stockholm, Sweden. They observed similar trends of heating demand reductions and cooling demand increases as in Paper V but to various extents depending on the climate model used. Global Climate models (GCMs) are reported as the most advanced tools currently available for simulating the response of the global climate system to increased GHG concentrations [104]. Future climate projections are based on advanced and high resolution GCMs, which continue to improve over time. Our analyses in Paper V are based on the recent climate scenarios released by the IPCC to minimise these uncertainties.

Uncertainties linked to simulation input parameters and assumptions for building energy balance calculations were the main focus in Papers II and III.

53

References 1. Zabalza Bribián, I., A. Valero Capilla, and A. Aranda Usón, Life cycle

assessment of building materials: Comparative analysis of energy and environmental impacts and evaluation of the eco-efficiency improvement potential. Building and Environment, 2011. 46(5): p. 1133-1140.

2. UNEP United Nations Environment Programme, Global Environment Outlook – environment for development (GEO-4). Available from: http://www.unep.org (accessed November 2016). 2007.

3. IEA International Energy Agency, Key World Energy Statistics, available at http://www.iea.org 2016.

4. IEA International Energy Agency, World Energy outlook 2016. 2016. 5. IEA International Energy Agency, Energy and climate change, in: World

Energy Outlook Special Report available at http://www.worldenergyoutlook.org/energyclimate/. 2015.

6. IPCC Intergovernmental Panel on Climate Change, Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 2014.

7. IPCC Intergovermental Panel on Climate Change, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. 2013.

8. UNFCCC United Nations Framework Convention on Climate Change, Adoption of the Paris Agreement, Conference of the Parties on its twenty-first session. 2015.

9. IPCC Intergovernmental Panel on Climate Change, Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp. 2014.

10. Rogelj, J., et al., Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature, 2016. 534(7609): p. 631-639.

11. Eurostat, Energy, transport and environment indicators. Eurostat; 2016. Available at: http://epp.eurostat.ec.europa.eu. 2016.

12. Swedish Energy Agency, Energy in Sweden - Facts and Figures 2016. Available at: http://www.energimyndigheten.se/en/news/2016/energy-in-sweden---facts-and-figures-2016-available-now/. 2016.

52

on electricity from stand-alone plants with biomass fuels. It is of interest to explore other renewable based electricity sources in this context.

Newly planned areas may constitute different building types and configurations to meet various accommodation needs in society. In addition to climate change, this may also have implications for resource use and energy supply needs. The integration of different aspects of site specific conditions, including design of buildings and layout of the surroundings, construction systems and energy supply systems among others could be valuable in the planning and development of new urban areas.

53

References 1. Zabalza Bribián, I., A. Valero Capilla, and A. Aranda Usón, Life cycle

assessment of building materials: Comparative analysis of energy and environmental impacts and evaluation of the eco-efficiency improvement potential. Building and Environment, 2011. 46(5): p. 1133-1140.

2. UNEP United Nations Environment Programme, Global Environment Outlook – environment for development (GEO-4). Available from: http://www.unep.org (accessed November 2016). 2007.

3. IEA International Energy Agency, Key World Energy Statistics, available at http://www.iea.org 2016.

4. IEA International Energy Agency, World Energy outlook 2016. 2016. 5. IEA International Energy Agency, Energy and climate change, in: World

Energy Outlook Special Report available at http://www.worldenergyoutlook.org/energyclimate/. 2015.

6. IPCC Intergovernmental Panel on Climate Change, Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 2014.

7. IPCC Intergovermental Panel on Climate Change, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. 2013.

8. UNFCCC United Nations Framework Convention on Climate Change, Adoption of the Paris Agreement, Conference of the Parties on its twenty-first session. 2015.

9. IPCC Intergovernmental Panel on Climate Change, Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp. 2014.

10. Rogelj, J., et al., Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature, 2016. 534(7609): p. 631-639.

11. Eurostat, Energy, transport and environment indicators. Eurostat; 2016. Available at: http://epp.eurostat.ec.europa.eu. 2016.

12. Swedish Energy Agency, Energy in Sweden - Facts and Figures 2016. Available at: http://www.energimyndigheten.se/en/news/2016/energy-in-sweden---facts-and-figures-2016-available-now/. 2016.

52

on electricity from stand-alone plants with biomass fuels. It is of interest to explore other renewable based electricity sources in this context.

Newly planned areas may constitute different building types and configurations to meet various accommodation needs in society. In addition to climate change, this may also have implications for resource use and energy supply needs. The integration of different aspects of site specific conditions, including design of buildings and layout of the surroundings, construction systems and energy supply systems among others could be valuable in the planning and development of new urban areas.

55

28. Ozel, M., Effect of insulation location on dynamic heat-transfer characteristics of building external walls and optimization of insulation thickness. Energy and Buildings, 2014. 72: p. 288-295.

29. Ucar, A. and F. Balo, Determination of the energy savings and the optimum insulation thickness in the four different insulated exterior walls. Renewable Energy, 2010. 35(1): p. 88-94.

30. Bektas Ekici, B., A. Aytac Gulten, and U.T. Aksoy, A study on the optimum insulation thicknesses of various types of external walls with respect to different materials, fuels and climate zones in Turkey. Applied Energy, 2012. 92: p. 211-217.

31. Anastaselos, D., S. Oxizidis, and A.M. Papadopoulos, Energy, environmental and economic optimization of thermal insulation solutions by means of an integrated decision support system. Energy and Buildings, 2011. 43(2–3): p. 686-694.

32. Audenaert, A., S.H. De Cleyn, and M. Buyle, LCA of low-energy flats using the Eco-indicator 99 method: Impact of insulation materials. Energy and Buildings, 2012. 47: p. 68-73.

33. Directive 2010/31/EU, of the European Parliament and of the Council of 19 May2010 on the energy performance of buildings (Recast). Official Journal of the European Union.

34. Crawley, D.B., et al., EnergyPlus: creating a new-generation building energy simulation program. Energy and Buildings, 2001. 33(4): p. 319-331.

35. Salamanca, F., et al., A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. formulation, verification, and sensitivity analysis of the model. Theoretical and Applied Climatology, 2009. 99(3): p. 331.

36. Boyano, A., P. Hernandez, and O. Wolf, Energy demands and potential savings in European office buildings: Case studies based on EnergyPlus simulations. Energy and Buildings, 2013. 65: p. 19-28.

37. De Rosa, M., et al., Impact of wall discretization on the modeling of heating/cooling energy consumption of residential buildings. Energy Efficiency, 2016. 9(1): p. 95-108.

38. Daly, D., P. Cooper, and Z. Ma, Understanding the risks and uncertainties introduced by common assumptions in energy simulations for Australian commercial buildings. Energy and Buildings, 2014. 75(0): p. 382-393.

39. Zhao, M., H.M. Künzel, and F. Antretter, Parameters influencing the energy performance of residential buildings in different Chinese climate zones. Energy and Buildings, 2015. 96: p. 64-75.

40. Wall, M., Energy-efficient terrace houses in Sweden: Simulations and measurements. Energy and Buildings, 2006. 38(6): p. 627-634.

41. Molin, A., P. Rohdin, and B. Moshfegh, Investigation of energy performance of newly built low-energy buildings in Sweden. Energy and Buildings, 2011. 43(10): p. 2822-2831.

54

13. Saheb, Y., et al., Energy Renovation: The Trump Card for the New Start for Europe. 2015: JRC Science and policy reports. Web accessed at http://iet.jrc.ec.europa.eu/energyefficiency/system/tdf/eur26888_buildingreport_online.pdf?file=1&type=node&id=9069 on October 3, 2015.

14. Swedish Energy Agency, Energy in Sweden 2015. Available at www.energimyndigheten.se, Swedish Energy Agency. 2015.

15. Janson, U., Passive houses in Sweden - From design to evaluation of four demonstration projects, in Division of Energy and Building Design, Department of Architecture and Built Environment. 2010, Lund University: Lund, Sweden.

16. IEA International Energy Agency, Technology Roadmap: Energy efficient building envelopes. Available at https://www.iea.org/publications/freepublications/publication/technology-roadmap-energy-efficient-building-envelopes.html. 2013.

17. European Commission, Energy roadmap 2050. 2012. 18. Swedish Government Bill 2005/06:145, National Programme for Energy

Efficiency and Energy-smart Construction. Available at http://www.government.se/information-material/2006/05/national-programme-for-energy-efficiency-and-energy-smart-construction/.

19. Sartori, I. and A.G. Hestnes, Energy use in the life cycle of conventional and low-energy buildings: A review article. Energy and Buildings, 2007. 39(3): p. 249-257.

20. Rossi, B., et al., Life-cycle assessment of residential buildings in three different European locations, basic tool. Building and Environment, 2012. 51: p. 395-401.

21. Asdrubali, F., C. Baldassarri, and V. Fthenakis, Life cycle analysis in the construction sector: Guiding the optimization of conventional Italian buildings. Energy and Buildings, 2013. 64(0): p. 73-89.

22. Jelle, B.P., Traditional, state-of-the-art and future thermal building insulation materials and solutions – Properties, requirements and possibilities. Energy and Buildings, 2011. 43(10): p. 2549-2563.

23. Al-Homoud, D.M.S., Performance characteristics and practical applications of common building thermal insulation materials. Building and Environment, 2005. 40(3): p. 353-366.

24. Pavlík, Z. and R. Černý, Hygrothermal performance study of an innovative interior thermal insulation system. Applied Thermal Engineering, 2009. 29(10): p. 1941-1946.

25. Pilkington, B. and S. Grove, Thermal conductivity probe length to radius ratio problem when measuring building insulation materials. Construction and Building Materials, 2012. 35: p. 531-546.

26. Stazi, F., et al., Experimental comparison between 3 different traditional wall constructions and dynamic simulations to identify optimal thermal insulation strategies. Energy and Buildings, 2013. 60: p. 429-441.

27. Kolaitis, D.I., et al., Comparative assessment of internal and external thermal insulation systems for energy efficient retrofitting of residential buildings. Energy and Buildings, 2013. 64: p. 123-131.

55

28. Ozel, M., Effect of insulation location on dynamic heat-transfer characteristics of building external walls and optimization of insulation thickness. Energy and Buildings, 2014. 72: p. 288-295.

29. Ucar, A. and F. Balo, Determination of the energy savings and the optimum insulation thickness in the four different insulated exterior walls. Renewable Energy, 2010. 35(1): p. 88-94.

30. Bektas Ekici, B., A. Aytac Gulten, and U.T. Aksoy, A study on the optimum insulation thicknesses of various types of external walls with respect to different materials, fuels and climate zones in Turkey. Applied Energy, 2012. 92: p. 211-217.

31. Anastaselos, D., S. Oxizidis, and A.M. Papadopoulos, Energy, environmental and economic optimization of thermal insulation solutions by means of an integrated decision support system. Energy and Buildings, 2011. 43(2–3): p. 686-694.

32. Audenaert, A., S.H. De Cleyn, and M. Buyle, LCA of low-energy flats using the Eco-indicator 99 method: Impact of insulation materials. Energy and Buildings, 2012. 47: p. 68-73.

33. Directive 2010/31/EU, of the European Parliament and of the Council of 19 May2010 on the energy performance of buildings (Recast). Official Journal of the European Union.

34. Crawley, D.B., et al., EnergyPlus: creating a new-generation building energy simulation program. Energy and Buildings, 2001. 33(4): p. 319-331.

35. Salamanca, F., et al., A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. formulation, verification, and sensitivity analysis of the model. Theoretical and Applied Climatology, 2009. 99(3): p. 331.

36. Boyano, A., P. Hernandez, and O. Wolf, Energy demands and potential savings in European office buildings: Case studies based on EnergyPlus simulations. Energy and Buildings, 2013. 65: p. 19-28.

37. De Rosa, M., et al., Impact of wall discretization on the modeling of heating/cooling energy consumption of residential buildings. Energy Efficiency, 2016. 9(1): p. 95-108.

38. Daly, D., P. Cooper, and Z. Ma, Understanding the risks and uncertainties introduced by common assumptions in energy simulations for Australian commercial buildings. Energy and Buildings, 2014. 75(0): p. 382-393.

39. Zhao, M., H.M. Künzel, and F. Antretter, Parameters influencing the energy performance of residential buildings in different Chinese climate zones. Energy and Buildings, 2015. 96: p. 64-75.

40. Wall, M., Energy-efficient terrace houses in Sweden: Simulations and measurements. Energy and Buildings, 2006. 38(6): p. 627-634.

41. Molin, A., P. Rohdin, and B. Moshfegh, Investigation of energy performance of newly built low-energy buildings in Sweden. Energy and Buildings, 2011. 43(10): p. 2822-2831.

54

13. Saheb, Y., et al., Energy Renovation: The Trump Card for the New Start for Europe. 2015: JRC Science and policy reports. Web accessed at http://iet.jrc.ec.europa.eu/energyefficiency/system/tdf/eur26888_buildingreport_online.pdf?file=1&type=node&id=9069 on October 3, 2015.

14. Swedish Energy Agency, Energy in Sweden 2015. Available at www.energimyndigheten.se, Swedish Energy Agency. 2015.

15. Janson, U., Passive houses in Sweden - From design to evaluation of four demonstration projects, in Division of Energy and Building Design, Department of Architecture and Built Environment. 2010, Lund University: Lund, Sweden.

16. IEA International Energy Agency, Technology Roadmap: Energy efficient building envelopes. Available at https://www.iea.org/publications/freepublications/publication/technology-roadmap-energy-efficient-building-envelopes.html. 2013.

17. European Commission, Energy roadmap 2050. 2012. 18. Swedish Government Bill 2005/06:145, National Programme for Energy

Efficiency and Energy-smart Construction. Available at http://www.government.se/information-material/2006/05/national-programme-for-energy-efficiency-and-energy-smart-construction/.

19. Sartori, I. and A.G. Hestnes, Energy use in the life cycle of conventional and low-energy buildings: A review article. Energy and Buildings, 2007. 39(3): p. 249-257.

20. Rossi, B., et al., Life-cycle assessment of residential buildings in three different European locations, basic tool. Building and Environment, 2012. 51: p. 395-401.

21. Asdrubali, F., C. Baldassarri, and V. Fthenakis, Life cycle analysis in the construction sector: Guiding the optimization of conventional Italian buildings. Energy and Buildings, 2013. 64(0): p. 73-89.

22. Jelle, B.P., Traditional, state-of-the-art and future thermal building insulation materials and solutions – Properties, requirements and possibilities. Energy and Buildings, 2011. 43(10): p. 2549-2563.

23. Al-Homoud, D.M.S., Performance characteristics and practical applications of common building thermal insulation materials. Building and Environment, 2005. 40(3): p. 353-366.

24. Pavlík, Z. and R. Černý, Hygrothermal performance study of an innovative interior thermal insulation system. Applied Thermal Engineering, 2009. 29(10): p. 1941-1946.

25. Pilkington, B. and S. Grove, Thermal conductivity probe length to radius ratio problem when measuring building insulation materials. Construction and Building Materials, 2012. 35: p. 531-546.

26. Stazi, F., et al., Experimental comparison between 3 different traditional wall constructions and dynamic simulations to identify optimal thermal insulation strategies. Energy and Buildings, 2013. 60: p. 429-441.

27. Kolaitis, D.I., et al., Comparative assessment of internal and external thermal insulation systems for energy efficient retrofitting of residential buildings. Energy and Buildings, 2013. 64: p. 123-131.

57

57. Wang, H. and Q. Chen, Impact of climate change heating and cooling energy use in buildings in the United States. Energy and Buildings, 2014. 82: p. 428-436.

58. Dodoo, A. and L. Gustavsson, Energy use and overheating risk of Swedish multi-storey residential buildings under different climate scenarios. Energy, 2016. 97: p. 534-548.

59. Holmes, M.J. and J.N. Hacker, Climate change, thermal comfort and energy: Meeting the design challenges of the 21st century. Energy and Buildings, 2007. 39(7): p. 802-814.

60. Wong, S.L., et al., Impact of climate change on residential building envelope cooling loads in subtropical climates. Energy and Buildings, 2010. 42(11): p. 2098-2103.

61. Karimpour, M., et al., Impact of climate change on the design of energy efficient residential building envelopes. Energy and Buildings, 2015. 87: p. 142-154.

62. Al-Sanea, S.A. and M.F. Zedan, Improving thermal performance of building walls by optimizing insulation layer distribution and thickness for same thermal mass. Applied Energy, 2011. 88(9): p. 3113-3124.

63. Jerman, M. and R. Černý, Effect of moisture content on heat and moisture transport and storage properties of thermal insulation materials. Energy and Buildings, 2012. 53: p. 39-46.

64. Jiang, L., et al., Correlation study between flammability and the width of organic thermal insulation materials for building exterior walls. Energy and Buildings, 2014. 82: p. 243-249.

65. Baetens, R., 9 - High performance thermal insulation materials for buildings, in Nanotechnology in Eco-Efficient Construction. 2013, Woodhead Publishing. p. 188-206.

66. Karlsson, J.F. and B. Moshfegh, Energy demand and indoor climate in a low energy building—changed control strategies and boundary conditions. Energy and Buildings, 2006. 38(4): p. 315-326.

67. Karlsson, F., P. Rohdin, and M.-L. Persson, Measured and predicted energy demand of a low energy building: important aspects when using Building Energy Simulation. Building Services Engineering Research and Technology, 2007. 28(3): p. 223-235.

68. ISO (International Organization for Standardization), ISO 14040 International Standard. Environmental management - Life cycle assessment - Principles and framework. 2006: Geneva, Switzerland.

69. ISO (International Organization for Standardization), ISO 14044 International Standard. Environmental management - Life cycle assessment - Requirements and guidelines. 2006: Geneva, Switzerland.

70. Earles, J.M. and A. Halog, Consequential life cycle assessment: a review. The International Journal of Life Cycle Assessment, 2011. 16(5): p. 445-453.

71. Plevin, R.J., M.A. Delucchi, and F. Creutzig, Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation Benefits

56

42. Danielski, I., Large variations in specific final energy use in Swedish apartment buildings: Causes and solutions. Energy and Buildings, 2012. 49: p. 276-285.

43. Persson, M.-L., A. Roos, and M. Wall, Influence of window size on the energy balance of low energy houses. Energy and Buildings, 2006. 38(3): p. 181-188.

44. Gugliermetti, F. and F. Bisegna, Saving energy in residential buildings: The use of fully reversible windows. Energy, 2007. 32(7): p. 1235-1247.

45. Hassouneh, K., A. Alshboul, and A. Al-Salaymeh, Influence of windows on the energy balance of apartment buildings in Amman. Energy Conversion and Management, 2010. 51(8): p. 1583-1591.

46. Jaber, S. and S. Ajib, Thermal and economic windows design for different climate zones. Energy and Buildings, 2011. 43(11): p. 3208-3215.

47. Yaşar, Y. and S.M. Kalfa, The effects of window alternatives on energy efficiency and building economy in high-rise residential buildings in moderate to humid climates. Energy Conversion and Management, 2012. 64(0): p. 170-181.

48. Poirazis, H., Å. Blomsterberg, and M. Wall, Energy simulations for glazed office buildings in Sweden. Energy and Buildings, 2008. 40(7): p. 1161-1170.

49. Grynning, S., et al., Windows in the buildings of tomorrow: Energy losers or energy gainers? Energy and Buildings, 2013. 61(0): p. 185-192.

50. Leskovar, V.Ž. and M. Premrov, An approach in architectural design of energy-efficient timber buildings with a focus on the optimal glazing size in the south-oriented façade. Energy and Buildings, 2011. 43(12): p. 3410-3418.

51. Leskovar, V.Ž. and M. Premrov, Influence of glazing size on energy efficiency of timber-frame buildings. Construction and Building Materials, 2012. 30(0): p. 92-99.

52. Badescu, V., N. Laaser, and R. Crutescu, Warm season cooling requirements for passive buildings in Southeastern Europe (Romania). Energy, 2010. 35(8): p. 3284-3300.

53. Mlakar, J. and J. Štrancar, Overheating in residential passive house: Solution strategies revealed and confirmed through data analysis and simulations. Energy and Buildings, 2011. 43(6): p. 1443-1451.

54. Persson, J. and M. Westermark, Phase change material cool storage for a Swedish Passive House. Energy and Buildings, 2012. 54: p. 490-495.

55. McLeod, R.S., C.J. Hopfe, and A. Kwan, An investigation into future performance and overheating risks in Passivhaus dwellings. Building and Environment, 2013. 70: p. 189-209.

56. Rohdin, P., A. Molin, and B. Moshfegh, Experiences from nine passive houses in Sweden – Indoor thermal environment and energy use. Building and Environment, 2014. 71: p. 176-185.

57

57. Wang, H. and Q. Chen, Impact of climate change heating and cooling energy use in buildings in the United States. Energy and Buildings, 2014. 82: p. 428-436.

58. Dodoo, A. and L. Gustavsson, Energy use and overheating risk of Swedish multi-storey residential buildings under different climate scenarios. Energy, 2016. 97: p. 534-548.

59. Holmes, M.J. and J.N. Hacker, Climate change, thermal comfort and energy: Meeting the design challenges of the 21st century. Energy and Buildings, 2007. 39(7): p. 802-814.

60. Wong, S.L., et al., Impact of climate change on residential building envelope cooling loads in subtropical climates. Energy and Buildings, 2010. 42(11): p. 2098-2103.

61. Karimpour, M., et al., Impact of climate change on the design of energy efficient residential building envelopes. Energy and Buildings, 2015. 87: p. 142-154.

62. Al-Sanea, S.A. and M.F. Zedan, Improving thermal performance of building walls by optimizing insulation layer distribution and thickness for same thermal mass. Applied Energy, 2011. 88(9): p. 3113-3124.

63. Jerman, M. and R. Černý, Effect of moisture content on heat and moisture transport and storage properties of thermal insulation materials. Energy and Buildings, 2012. 53: p. 39-46.

64. Jiang, L., et al., Correlation study between flammability and the width of organic thermal insulation materials for building exterior walls. Energy and Buildings, 2014. 82: p. 243-249.

65. Baetens, R., 9 - High performance thermal insulation materials for buildings, in Nanotechnology in Eco-Efficient Construction. 2013, Woodhead Publishing. p. 188-206.

66. Karlsson, J.F. and B. Moshfegh, Energy demand and indoor climate in a low energy building—changed control strategies and boundary conditions. Energy and Buildings, 2006. 38(4): p. 315-326.

67. Karlsson, F., P. Rohdin, and M.-L. Persson, Measured and predicted energy demand of a low energy building: important aspects when using Building Energy Simulation. Building Services Engineering Research and Technology, 2007. 28(3): p. 223-235.

68. ISO (International Organization for Standardization), ISO 14040 International Standard. Environmental management - Life cycle assessment - Principles and framework. 2006: Geneva, Switzerland.

69. ISO (International Organization for Standardization), ISO 14044 International Standard. Environmental management - Life cycle assessment - Requirements and guidelines. 2006: Geneva, Switzerland.

70. Earles, J.M. and A. Halog, Consequential life cycle assessment: a review. The International Journal of Life Cycle Assessment, 2011. 16(5): p. 445-453.

71. Plevin, R.J., M.A. Delucchi, and F. Creutzig, Using Attributional Life Cycle Assessment to Estimate Climate-Change Mitigation Benefits

56

42. Danielski, I., Large variations in specific final energy use in Swedish apartment buildings: Causes and solutions. Energy and Buildings, 2012. 49: p. 276-285.

43. Persson, M.-L., A. Roos, and M. Wall, Influence of window size on the energy balance of low energy houses. Energy and Buildings, 2006. 38(3): p. 181-188.

44. Gugliermetti, F. and F. Bisegna, Saving energy in residential buildings: The use of fully reversible windows. Energy, 2007. 32(7): p. 1235-1247.

45. Hassouneh, K., A. Alshboul, and A. Al-Salaymeh, Influence of windows on the energy balance of apartment buildings in Amman. Energy Conversion and Management, 2010. 51(8): p. 1583-1591.

46. Jaber, S. and S. Ajib, Thermal and economic windows design for different climate zones. Energy and Buildings, 2011. 43(11): p. 3208-3215.

47. Yaşar, Y. and S.M. Kalfa, The effects of window alternatives on energy efficiency and building economy in high-rise residential buildings in moderate to humid climates. Energy Conversion and Management, 2012. 64(0): p. 170-181.

48. Poirazis, H., Å. Blomsterberg, and M. Wall, Energy simulations for glazed office buildings in Sweden. Energy and Buildings, 2008. 40(7): p. 1161-1170.

49. Grynning, S., et al., Windows in the buildings of tomorrow: Energy losers or energy gainers? Energy and Buildings, 2013. 61(0): p. 185-192.

50. Leskovar, V.Ž. and M. Premrov, An approach in architectural design of energy-efficient timber buildings with a focus on the optimal glazing size in the south-oriented façade. Energy and Buildings, 2011. 43(12): p. 3410-3418.

51. Leskovar, V.Ž. and M. Premrov, Influence of glazing size on energy efficiency of timber-frame buildings. Construction and Building Materials, 2012. 30(0): p. 92-99.

52. Badescu, V., N. Laaser, and R. Crutescu, Warm season cooling requirements for passive buildings in Southeastern Europe (Romania). Energy, 2010. 35(8): p. 3284-3300.

53. Mlakar, J. and J. Štrancar, Overheating in residential passive house: Solution strategies revealed and confirmed through data analysis and simulations. Energy and Buildings, 2011. 43(6): p. 1443-1451.

54. Persson, J. and M. Westermark, Phase change material cool storage for a Swedish Passive House. Energy and Buildings, 2012. 54: p. 490-495.

55. McLeod, R.S., C.J. Hopfe, and A. Kwan, An investigation into future performance and overheating risks in Passivhaus dwellings. Building and Environment, 2013. 70: p. 189-209.

56. Rohdin, P., A. Molin, and B. Moshfegh, Experiences from nine passive houses in Sweden – Indoor thermal environment and energy use. Building and Environment, 2014. 71: p. 176-185.

59

87. D. Kellenberger, H.-J.A., T. Künniger, M. Lehmann, N. Jungbluth, P.Thalmann, , Life cycle inventories of building products, data v2.0, in: Ecoin-vent Report No. 7, EMPA-Swiss Centre for Life Cycle Inventories, Dübendorf. 2007.

88. Gustavsson, L. and R. Sathre, Variability in energy and carbon dioxide balances of wood and concrete building materials. Building and Environment, 2006. 41(7): p. 940-951.

89. US Department of Energy. Building energy software tools directory - Whole building Analysis: energy simulation. Accessed at http://apps1.eere.energy.gov/ October 01, 2014. 2011.

90. StruSoft, VIP-Energy, Version 2.1.0 StruSoft AB, Editor. 2012: Sweden. http://www.strusoft.com/products/vip-energy

91. Wichlaj, M., Energisimulering i VIP Energy. Solenergihus Del av Berga 10:19 Plusenergyihus. Project Byggaren. Arb nr. 5210025. 2010.

92. Holmstedt, B., Energibilaga. Kv Täppan Flerbostadshus, Nybyggnation av bostäder, Växjöhem. Projektnr: 8695601/3 Bengt Dahlgren AB. 2012.

93. Noris, F., et al., Implications of weighting factors on technology preference in net zero energy buildings. Energy and Buildings, 2014. 82: p. 250-262.

94. Siggelsten, S., Reallocation of heating costs due to heat transfer between adjacent apartments. Energy and Buildings, 2014. 75: p. 256-263.

95. Boverket, Optimala kostnader för energieffektivisering. Underlag enligt Europaparlamentets och rådets direktiv 2010/31/EU om byggnaders energiprestanda. (In Swedish). Web accessed at http://www.boverket.se/globalassets/publikationer/dokument/2013/optimala-kostnader-for-energieffektivisering.pdf on October, 2015. 2013.

96. Karlsson, Å., ENSYST, Version 1.2. 2003, Lund University: Lund. 97. Boverkets Byggregler, Boverkets Författningssamling, The national

Board of Housing Building and planning, Karlskrona. Available at http://www.boverket.se (In Swedish).

98. FEBY 12, Kravspecifikation för nollenergihus passivhus och minienergihus Bostäder. Available at www.passivhuscentrum.se/sites/default/files/kravspecifikation (In Swedish). 2012.

99. Menezes, A.C., et al., Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap. Applied Energy, 2012. 97: p. 355-364.

100. CIBSE, Guide A: Environmental design, Chartered Institute of Building Services Engineers, London. . 2006.

101. UNEP United Nations Environment Programme, Buildings and Climate Change, Summary for Decision-makers. 2009, United Nations Environment Programme, : Paris, 2009, ISBN: 987-92-807-3064-7 DTI/1240/PA.

102. Fossdal, S., Energi-og Miljøregnskap for bygg (Energy and environmental accounts of building construction), in: Report 173, The

58

Misleads Policy Makers. Journal of Industrial Ecology, 2014. 18(1): p. 73-83.

72. Curran, M.A., M. Mann, and G. Norris, The international workshop on electricity data for life cycle inventories. Journal of Cleaner Production, 2005. 13(8): p. 853-862.

73. Ramesh, T., R. Prakash, and K.K. Shukla, Life cycle energy analysis of buildings: An overview. Energy and Buildings, 2010. 42(10): p. 1592-1600.

74. Cabeza, L.F., et al., Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: A review. Renewable and Sustainable Energy Reviews, 2014. 29: p. 394-416.

75. Checkland, P., Systems Thinking, Systems Practice. 1999: John Wiley and Sons Limited, Chichester, UK.

76. Churchman, C.W., The Systems Approach. 1968: New York: Dell Publishing Co.

77. Sathre, R., Life-cycle energy and carbon implications of wood-based products and construction, in Department of Engineering,Physics and Mathematics 2007, Mid Sweden University: Östersund, Sweden.

78. Truong, N.L., District heat production under different environmental and social cost scenarios, in Department of building and energy technology. 2014, Linnaeus University: Växjö, Sweden.

79. Swedish Energy Agency, Energy in Sweden 2015. Swedish Energy Agency: Available at www.energimyndigheten.se.

80. Ekvall, T. and G. Finnveden, Allocation in ISO 14041—a critical review. Journal of Cleaner Production, 2001. 9(3): p. 197-208.

81. Gustavsson, L. and Å. Karlsson, CO2 mitigation: on methods and parameters forcomparison of fossil fuel and biofuel systems. Mitigation and Adaptation Strategies for Global Change, 2006. 11 p. 935–959.

82. Gustavsson, L. and R. Sathre, Energy and CO2 analysis of wood substitution in construction. Climatic Change, 2011. 105(1‐2): p. 129‐153.

83. Hall, T. and S. VidÉN, The Million Homes Programme: a review of the great Swedish planning project. Planning Perspectives, 2005. 20(3): p. 301-328.

84. Gustavsson, L., K. Pingoud, and R. Sathre, Carbon Dioxide Balance of Wood Substitution: Comparing Concrete- and Wood-Framed Buildings. Mitigation and Adaptation Strategies for Global Change, 2006. 11(3): p. 667-691.

85. Björklund, T. and A.-M. Tillman, LCA of building frame structures: environmental impact over the life cycle of wooden and concrete frames in: Technical Environmental Planning Report 2. 1997, Chalmers University of Technology: Gothenburg, Sweden.

86. Fossdal, S., Energi‐ og Miljøregnskap for bygg (Energy and environmental accounts of building construction). Report 173 1995, The Norwegian Institute of Building Research, Oslo. (In Norwegian).

59

87. D. Kellenberger, H.-J.A., T. Künniger, M. Lehmann, N. Jungbluth, P.Thalmann, , Life cycle inventories of building products, data v2.0, in: Ecoin-vent Report No. 7, EMPA-Swiss Centre for Life Cycle Inventories, Dübendorf. 2007.

88. Gustavsson, L. and R. Sathre, Variability in energy and carbon dioxide balances of wood and concrete building materials. Building and Environment, 2006. 41(7): p. 940-951.

89. US Department of Energy. Building energy software tools directory - Whole building Analysis: energy simulation. Accessed at http://apps1.eere.energy.gov/ October 01, 2014. 2011.

90. StruSoft, VIP-Energy, Version 2.1.0 StruSoft AB, Editor. 2012: Sweden. http://www.strusoft.com/products/vip-energy

91. Wichlaj, M., Energisimulering i VIP Energy. Solenergihus Del av Berga 10:19 Plusenergyihus. Project Byggaren. Arb nr. 5210025. 2010.

92. Holmstedt, B., Energibilaga. Kv Täppan Flerbostadshus, Nybyggnation av bostäder, Växjöhem. Projektnr: 8695601/3 Bengt Dahlgren AB. 2012.

93. Noris, F., et al., Implications of weighting factors on technology preference in net zero energy buildings. Energy and Buildings, 2014. 82: p. 250-262.

94. Siggelsten, S., Reallocation of heating costs due to heat transfer between adjacent apartments. Energy and Buildings, 2014. 75: p. 256-263.

95. Boverket, Optimala kostnader för energieffektivisering. Underlag enligt Europaparlamentets och rådets direktiv 2010/31/EU om byggnaders energiprestanda. (In Swedish). Web accessed at http://www.boverket.se/globalassets/publikationer/dokument/2013/optimala-kostnader-for-energieffektivisering.pdf on October, 2015. 2013.

96. Karlsson, Å., ENSYST, Version 1.2. 2003, Lund University: Lund. 97. Boverkets Byggregler, Boverkets Författningssamling, The national

Board of Housing Building and planning, Karlskrona. Available at http://www.boverket.se (In Swedish).

98. FEBY 12, Kravspecifikation för nollenergihus passivhus och minienergihus Bostäder. Available at www.passivhuscentrum.se/sites/default/files/kravspecifikation (In Swedish). 2012.

99. Menezes, A.C., et al., Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap. Applied Energy, 2012. 97: p. 355-364.

100. CIBSE, Guide A: Environmental design, Chartered Institute of Building Services Engineers, London. . 2006.

101. UNEP United Nations Environment Programme, Buildings and Climate Change, Summary for Decision-makers. 2009, United Nations Environment Programme, : Paris, 2009, ISBN: 987-92-807-3064-7 DTI/1240/PA.

102. Fossdal, S., Energi-og Miljøregnskap for bygg (Energy and environmental accounts of building construction), in: Report 173, The

58

Misleads Policy Makers. Journal of Industrial Ecology, 2014. 18(1): p. 73-83.

72. Curran, M.A., M. Mann, and G. Norris, The international workshop on electricity data for life cycle inventories. Journal of Cleaner Production, 2005. 13(8): p. 853-862.

73. Ramesh, T., R. Prakash, and K.K. Shukla, Life cycle energy analysis of buildings: An overview. Energy and Buildings, 2010. 42(10): p. 1592-1600.

74. Cabeza, L.F., et al., Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: A review. Renewable and Sustainable Energy Reviews, 2014. 29: p. 394-416.

75. Checkland, P., Systems Thinking, Systems Practice. 1999: John Wiley and Sons Limited, Chichester, UK.

76. Churchman, C.W., The Systems Approach. 1968: New York: Dell Publishing Co.

77. Sathre, R., Life-cycle energy and carbon implications of wood-based products and construction, in Department of Engineering,Physics and Mathematics 2007, Mid Sweden University: Östersund, Sweden.

78. Truong, N.L., District heat production under different environmental and social cost scenarios, in Department of building and energy technology. 2014, Linnaeus University: Växjö, Sweden.

79. Swedish Energy Agency, Energy in Sweden 2015. Swedish Energy Agency: Available at www.energimyndigheten.se.

80. Ekvall, T. and G. Finnveden, Allocation in ISO 14041—a critical review. Journal of Cleaner Production, 2001. 9(3): p. 197-208.

81. Gustavsson, L. and Å. Karlsson, CO2 mitigation: on methods and parameters forcomparison of fossil fuel and biofuel systems. Mitigation and Adaptation Strategies for Global Change, 2006. 11 p. 935–959.

82. Gustavsson, L. and R. Sathre, Energy and CO2 analysis of wood substitution in construction. Climatic Change, 2011. 105(1‐2): p. 129‐153.

83. Hall, T. and S. VidÉN, The Million Homes Programme: a review of the great Swedish planning project. Planning Perspectives, 2005. 20(3): p. 301-328.

84. Gustavsson, L., K. Pingoud, and R. Sathre, Carbon Dioxide Balance of Wood Substitution: Comparing Concrete- and Wood-Framed Buildings. Mitigation and Adaptation Strategies for Global Change, 2006. 11(3): p. 667-691.

85. Björklund, T. and A.-M. Tillman, LCA of building frame structures: environmental impact over the life cycle of wooden and concrete frames in: Technical Environmental Planning Report 2. 1997, Chalmers University of Technology: Gothenburg, Sweden.

86. Fossdal, S., Energi‐ og Miljøregnskap for bygg (Energy and environmental accounts of building construction). Report 173 1995, The Norwegian Institute of Building Research, Oslo. (In Norwegian).

61

Appended papers

Paper I: Effects of different insulation materials on primary energy and CO2 emission of a multi-storey residential building.

Paper II: On input parameters, methods and assumptions for energy balance and retrofit analyses for residential buildings.

Paper III: Influence of simulation assumptions and input parameters on energy balance calculations of residential buildings.

Paper IV: Primary energy implications of different design strategies for an apartment building.

Paper V: Energy use implications of different design strategies for multi-storey residential buildings under future climates.

60

Norwegian Institute of Building Research, Oslo, Norway, (in Norwegian). 1995

103. Nik, V.M. and A. Sasic Kalagasidis, Impact study of the climate change on the energy performance of the building stock in Stockholm considering four climate uncertainties. Building and Environment, 2013. 60: p. 291-304.

104. IPCC Intergovernmental Panel on Climate Change. What is a GCM? Available at http://www.ipcc-data.org/guidelines/pages/gcm_guide.html. . 2013.

105. Gustavsson, L. and A. Joelsson, Life cycle primary energy analysis of residential buildings. Energy and Buildings, 2010. 42(2): p. 210-220.

106. Cabeza, L.F., et al., Low carbon and low embodied energy materials in buildings: A review. Renewable and Sustainable Energy Reviews, 2013. 23(0): p. 536-542.

107. Jokisalo, J. and J. Kurnitski, Effect of the thermal inertia and other building and HVAC factors on energy performance and thermal comfort in finnish apartment buildings. Report B79, Helsinki University of Technology. 2005, Laboratory of Heating, Ventilating and Air-Conditioning. Helsinki, Finland.

108. Ståhl, F., Influence of thermal mass on the heating and cooling demands of a building unit, in Department of Civil and Environmental Engineering, . 2009, Chalmers University of Technology. Göteborg, Sweden.

109. Dodoo, A., L. Gustavsson, and R. Sathre, Effect of thermal mass on life cycle primary energy balances of a concrete- and a wood-frame building. Applied Energy, 2012. 92(0): p. 462-472.

61

Appended papers

Paper I: Effects of different insulation materials on primary energy and CO2 emission of a multi-storey residential building.

Paper II: On input parameters, methods and assumptions for energy balance and retrofit analyses for residential buildings.

Paper III: Influence of simulation assumptions and input parameters on energy balance calculations of residential buildings.

Paper IV: Primary energy implications of different design strategies for an apartment building.

Paper V: Energy use implications of different design strategies for multi-storey residential buildings under future climates.

60

Norwegian Institute of Building Research, Oslo, Norway, (in Norwegian). 1995

103. Nik, V.M. and A. Sasic Kalagasidis, Impact study of the climate change on the energy performance of the building stock in Stockholm considering four climate uncertainties. Building and Environment, 2013. 60: p. 291-304.

104. IPCC Intergovernmental Panel on Climate Change. What is a GCM? Available at http://www.ipcc-data.org/guidelines/pages/gcm_guide.html. . 2013.

105. Gustavsson, L. and A. Joelsson, Life cycle primary energy analysis of residential buildings. Energy and Buildings, 2010. 42(2): p. 210-220.

106. Cabeza, L.F., et al., Low carbon and low embodied energy materials in buildings: A review. Renewable and Sustainable Energy Reviews, 2013. 23(0): p. 536-542.

107. Jokisalo, J. and J. Kurnitski, Effect of the thermal inertia and other building and HVAC factors on energy performance and thermal comfort in finnish apartment buildings. Report B79, Helsinki University of Technology. 2005, Laboratory of Heating, Ventilating and Air-Conditioning. Helsinki, Finland.

108. Ståhl, F., Influence of thermal mass on the heating and cooling demands of a building unit, in Department of Civil and Environmental Engineering, . 2009, Chalmers University of Technology. Göteborg, Sweden.

109. Dodoo, A., L. Gustavsson, and R. Sathre, Effect of thermal mass on life cycle primary energy balances of a concrete- and a wood-frame building. Applied Energy, 2012. 92(0): p. 462-472.