Life cycle energy balance of residential buildings: A case study on hypothetical building models in Finland

Accepted Manuscript Title: Life cycle energy balance of residential buildings: A case study on hypothetical building models in Finland Author: Atsushi Takano Sudip Kumar Pal Matti Kuittinen Kari Alanne PII: DOI: Reference:

S0378-7788(15)30176-6 http://dx.doi.org/doi:10.1016/j.enbuild.2015.07.060 ENB 6054

To appear in:

ENB

Received date: Revised date: Accepted date:

5-5-2015 3-7-2015 22-7-2015

Please cite this article as: A. Takano, S.K. Pal, M. Kuittinen, K. Alanne, Life cycle energy balance of residential buildings: A case study on hypothetical building models in Finland, Energy and Buildings (2015), http://dx.doi.org/10.1016/j.enbuild.2015.07.060 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

*Highlights

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The life cycle energy balance of four residential building types was studied. The influence of structural frame material selection was also observed. There are clear differences between the types regardless of the frame material. The differences appeared evenly among the building life cycle stages. The results were discussed focusing on the geometrical factors of each housing type.

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*Manuscript Click here to view linked References

Life cycle energy balance of residential buildings:

Atsushi Takano a, *, Sudip Kumar Pal b, Matti Kuittinen a, Kari Alanne b a

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A case study on hypothetical building models in Finland

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Department of Architecture, School of Arts, Design and Architecture, Aalto University, Miestentie 3, 02150 Espoo, Finland b

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Abstract

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Corresponding author Email: atsushi.takano @aalto.fi, Tel: +358(0)503442098 Address: Miestentie 3, 02150 Espoo, Finland

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Department of Energy Technology, School of Engineering, Aalto University, Otakaari 4, 02150 Espoo, Finland

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This study has demonstrated the life cycle primary energy balance of the four residential building types (detached house, row house, townhouse and apartment block) based on current Finnish design. The differences in the energy balance arising from the geometrical characteristics of each housing type were investigated using hypothetical building models. In addition, the influence of structural frame material selection was observed in relation to the housing types. The results showed that there are clear differences between the housing types: the detached house is the highest energy consumer, the row house the second (about 20% less), the townhouse the third (about 30% less) and the apartment block the lowest (about 45% less), regardless of the frame materials selection. The differences appeared evenly among the building life cycle stages. A correlation has been observed between the geometrical factors and life cycle primary energy balance of the reference buildings.

Key words Life cycle assessment; Primary energy balance; Residential building types; Structural material; Geometrical factor; City planning

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1. Introduction The building sector significantly contributes to the overall environmental impact of humankind’s activities. For instance, the sector globally accounts for more than 40% of the total primary energy consumption [1]. In this context, the life cycle energy use and associated environmental impacts of buildings have been intensively studied over the past few decades. Buildings need energy for their construction (embodied energy) as well as their functioning (operational energy). In the effort to

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reduce the life cycle energy consumption of buildings, most attention has thus far been paid to operational energy because of its dominance. In the case of conventional buildings, in many cases the

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operational energy accounts for more than 70% of the life cycle energy [2-5]. As a result of efforts in this area, such as improvements of the thermal insulation performance of the building envelope and

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the development of building service equipment, the operational energy demand has been significantly mitigated. Although the operational energy is still responsible for the major part of the life cycle energy use of buildings, the relative importance of embodied energy has increased, for instance,

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accounting for up to 46% of the life cycle energy use (service life of 50 years) in the case of lowenergy buildings [6-10]. In addition, the nearly zero-energy buildings (nZEBs) will become the norm

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for all new buildings in the European Union (EU) by the end of 2020 [11], meaning that the life cycle aspect is becoming more important in the discussion of building sustainability. As building operation becomes efficient, the relative importance of the other life cycle phases becomes higher and several

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aspects (e.g. type of energy use, metric of balance) are recently discussed in the definition of nZEB [12, 13]. For instance, as D’Agostino schematised [13], the embodied energy is one of the main

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arguments around the nZEB concept at the moment.

Although the energy consumption trend varies depending on countries, in many cases, residential buildings are responsible for a major part of the energy consumption of the building sector [14, 15]. Due to population growth and economic development, the construction of residential buildings can be expected to increase in the years to come. For instance, in Finland, the population in Helsinki has thus far been steadily growing, and it has been predicted to increase about 8% between 2013 to 2022 because of immigration and domestic migration based on economic growth [16]. Housing supply has, therefore, been being a main topic in the city planning. In principle, a living environment that has a peace, quietness and closeness to nature is preferred by most Finns [17]. Thus, low-density housing area development has occurred in the outer suburbs, especially from the 1990s; as a consequence, the Helsinki region has become among the most sprawling city regions in Europe [18]. In response to urban sprawl, recently dense and diverse residential area development has been aimed by incorporating several housing types to control the compactness and living condition of city districts [19]. In addition, the aims for sustainable urban development have been included in the city’s action

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plan since 2002, and sustainable strategies (e.g. energy-efficient buildings and urban structure) have become a top priority in the field of urban development [20, 21].

In this context, it is important for the decision making in city planning to understand the environmental features of different residential building types. Although a number of life cycle assessment (LCA) studies have been conducted to estimate the environmental profile of buildings,

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there have thus far been few studies that have investigated a relative relationship between different residential building types. For instance, Rosa et al. [22] have studied the life cycle environmental impacts (mainly global warming potential (GWP)) of the most common types of house in the UK:

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detached house, semi-detached house and terraced house. They reported that the semi-detached house and terrace house respectively emitted about 82% and 68% of greenhouse gas (GHG) compared to the

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detached house over the 50 years of building service life. The major differences between the three houses were caused from the use stage of the buildings. It was noted that the emissions arising from

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household appliances and water heating highly relate to the number of occupants in the house, whilst the emission from space heating and lighting mainly depends on the physical features of the house, such as composition, size, geometry, material, etc. Nemry and Uihlein [23] compared the

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environmental impacts of residential buildings (single-family houses, including two-family houses and terraced houses, multi-family houses and high-rise buildings) covering both existing and new constructions in the EU-25, for the 40 years of building service life. The study reported quite similar

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results as Rosa et al. [22], where, in general, single-family houses showed the highest impacts and

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high-rise buildings the lowest, regardless the climate zones and either new or existing construction. Gustavsson and Joelsson [24] simulated the life cycle primary energy balance of residential buildings (single family house, row house unit and apartment block) in Sweden for a period of 50 years. They also studied the influence of building material selection and different energy supply systems to discuss potential life cycle energy improvements. Although it is difficult to observe the differences between the housing types, due to significant variations in energy performance of the reference buildings, this study clearly demonstrated that the choice of energy supply system had greater influences than the energy efficiency building envelope measures. It showed that conventional buildings had the possibility to use less operational energy than the passive house level buildings, depending on the choice of energy supply system. The energy supply system also influences life cycle cost balance of a building (e.g. initial and operational cost, payback period) as demonstrated, for instance, in [25].

The material selection directly influences the environmental profiles of a building, since a building is a complex system consisting of many different materials. Several studies, therefore, have thus far been carried out to investigate the relationship between the building material selection and the resulting impacts. Thormark [26], for instance, studied the effect of material choice on both the

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embodied energy and recycling potential in an energy-efficient apartment block in Sweden. She noted that embodied energy could be reduced by approximately 17% or increased by about 6% by a simple material substitution. Cole [27] investigated the influence of material choice on the construction process. He found that the steel structure consumed the lowest energy during construction and the concrete structure the highest (the concrete structure requiring up to 40 times more energy than the steel construction). Wood construction typically required 2-3 times more construction energy than

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steel. Although this study is rather dated, it shows an interesting aspect. The effects of material selection on the operational energy have also been investigated [28-31]. It was commonly noted that a heavy-weight structure (e.g. concrete and brick) required less space heating energy (about 1.0-2.0%

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less) than a light-weight structure (e.g. steel and timber frame) thanks to thermal mass effect. The recycling aspect, which is highly related to the material selection as well, has been highlighted as

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being a potentially significant factor in reducing the life cycle energy use of buildings [12, 26].

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2. Objectives and scope

The objective of this study was to investigate the life cycle primary energy balance of residential

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building types: detached house, row house, townhouse and apartment block, in a Finnish context. A quantification of the differences in the life cycle energy efficiency arising from the compositional features of each housing type was the aim, as a case study in a cold climate area. The entire building

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life cycle, the production, operation (including maintenance) and end of life (EoL) stages, was

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covered, and the net primary energy benefits resulting from the reuse and recycling of materials exiting the system boundary was described as a potential resource for future use in accordance with [32]. In addition, this study was carried out in a comparative manner based on four structural frame materials typically used in Finland in order to observe the results in relation to the material selection. Understanding the relative life cycle energy profiles of the residential buildings would aid informed decision-making by professionals associated with the city planning and building design, leading to improved sustainability in urban development. Building service equipment and furniture were excluded from the calculation, since they were out of the scope of this study. Although, as Gustavsson and Joelsson [24] noted, the energy supply system (e.g. electricity mix, space heating technology, ventilation system) would have a major influence on the life cycle energy balance of a building, that was held constant as it is not within the focus of this study.

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3. Methodologies 3.1. Reference building models Simplified hypothetical building models reflecting the compositional features of four housing types, detached house (DH), row house (RH), townhouse (TH) and apartment block (AB), were used as the case study. Figure 1 shows the basic plan and section of the models with an indication of the

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building elements (e.g. party wall, intermediate floor, etc.). The building models were made based on a common module (6m*10m*3m). Table 1 shows the floor area and the area of each building element used in the calculation. Net heated floor area was used as the functional unit in this study. The reasons

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why hypothetical models were used in this paper were 1) to focus on the differences between the housing types in the life cycle energy balance arising from their compositional features, 2) to make

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assessment conditions as comparable as possible between the housing types and, as a consequence, 3) to generalise the results as much as possible. In practice, however, each building design is individual,

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and the results may differ based on design and material choices. Still, in the absence of statistical comparisons of building types’ environmental performance in Finland, parametric designs were used to exemplify the potential differences between building types. The interior partition wall (non-

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structural) was excluded from the model, since its layout depends upon the case. The embodied energy associated with building service equipment and furniture was also excluded from the assessment, because that is out of the scope of this study and because of high case-specific variation related to

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them. The reference buildings were assumed to be located in Helsinki (60°N, 25°E). In accordance

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with Finnish building code G1 [33], the window area was assumed to be 10% of the net room area, which is the minimum requirement. Window orientation was set towards north and south in all cases. The dimensions and window area of the model would naturally have a certain influence on the assessment results [34], however, they were held constant for the purposes of this study. The structural fire protection was taken into account according to Finnish building code E1 [35]. In addition to the assessment of the reference building models, parametric analysis was carried out on the TH building model in order to observe how the building scale (number of house unit connected in row and story) affects the result. Detailed information regarding this study is described in section 4.2. 3.2. Structural frame materials compared

Since structural frame material selection seemed to have some influence on this study, the reference buildings were assessed according to building elements with four different frame materials: light weight timber (LWT), cross laminated timber (CLT), reinforced concrete panel (RC) and light gauge steel (Steel), in a comparative manner. The typical configurations of building elements for each structural frame were selected from the literature [36] listed in table 2. U-value was constant in all

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cases regardless of the frame material (Exterior wall and floor = 0.16W/m2K, Roof = 0.09 W/m2K, according to Finnish building code D3 [37]). 3.3. Calculation at each stage of the building life cycle This study is based on the life cycle assessment (LCA) method [38, 39], and both renewable and non-renewable primary energy (PER and PENR, respectively) consumptions and benefits are

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calculated using the unit impact value (in MJ/kg of product or MJ/MJ of final energy) obtained from the ecoinvent database [40]. The final operational energy demand was simulated with IDA ICE [41], which is a whole building simulation software. The life cycle stages studied are identified according to

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method in each life cycle stage is given in the following sections.

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the modularity principle of a building life cycle [32]. Detailed information about the calculation

3.3.1. Material production stage (Module A1-3)

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Primary energy consumption during the manufacturing process of all components in the reference buildings was assessed by referring to the method used by Takano et al. [42]. The calculation was carried out by multiplying the unit values, which are the values derived from one square metre of the

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building elements (MJ/m2) by the area of each building element (m2) shown in table 1.

3.3.2. Use stage: Maintenance (Module B2+4)

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The primary energy consumed in the maintenance of the reference buildings was assessed

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according to the expected service life and maintenance intervals of the building components [43] listed in table 3. It was assumed that all maintenance was carried out using the same materials and same primary energy inputs as originally used. The replacement of the roofing materials was counted once and repainting of the surface components was taken into account according to the maintenance interval. No repair or refurbishment work was assumed to be carried out during the reference study period. The waste management process for the components replaced was not included because of its assumed minor influence on the end results.

3.3.3. Use stage: Building operation (Module B6) The operational final energy use for space heating, ventilation, household electricity and domestic hot water heating (50 year service life) was simulated with IDA ICE and the operational primary energy consumption was calculated based on an average energy mix in Finland [40, 44]. The simulation used the Finnish test reference year weather file (TRY2012) for Helsinki [45]. It was assumed that space heating was supplied by a district heating system and the mechanical ventilation system had 60% heat recovery efficiency. The set-point indoor temperature was 21°C. The ventilation system was modelled with a mechanical air-handling unit (AHU) with a CAV (constant air volume)

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system. For an AHU heating coil, the supply air temperature was 18°C. The internal heat gains due to occupants, lighting and electrical appliances were 10.3, 7.8 and 17.8 kWh/m2y respectively, which is in accordance with Finnish building code D5 [46]. The dynamic profiles of domestic hot water [37], lighting, electrical appliances and occupants are based on the Finnish reference single-family house model by the technical research centre of Finland (VTT) [47]. The air tightness of the building envelope was set as the air change rate at 50Pa: n50, 2/h, based on the Finnish building code [37]. The

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properties (e.g. density, thermal conductivity, specific heat capacity) of the materials studied were obtained from ISO/FDIS 10456 [48]. In chapter 4, space heating energy was mainly discussed since other energy uses were set to a constant value irrespective of the residential building types. In addition,

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space cooling energy was excluded from the study because it is normally minor in the Nordic climate.

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3.3.4. End of life stage (Module C)

It was assumed that the buildings were demolished by selective dismantling, and the building

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components were managed according to the scenarios listed in table 4. The scenarios were created based on the literature [49, 50]. The primary energy consumed during the EoL stage - deconstruction, transportation, waste processing for reuse or recycling and disposal - was assessed up to where the

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end-of-waste state of the materials is reached [32].

3.3.5. Net primary energy benefit (Module D)

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The net energy benefit of the recycled materials was calculated as the primary energy use avoided

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through substitution of primary production with the materials recycled (table 4), according to provisions in the standard [32]. Here, the aim was to describe the possible energy benefit of each building material after its service life, based on current recycling methods. The concrete was assumed to be crushed to form aggregate, which replaces gravel in road construction. The steel was assumed to be recycled into feedstock, which replaces ore-based steel for the production of new steel products. Gypsum board was assumed to be crushed into gypsum powder, replacing the primary gypsum. The secondary fuel (recycled wood and plastic materials) was assumed to replace coal in a power plant. 90% of each material was assumed to be recycled, whilst the remaining 10% was lost during the recycling, except mineral wastes, which were assumed to be fully landfilled. 3.4. Statistical analysis For the comparative study of the housing types, the percentage relative differences (PRD) were used. The detached house model (DH) was set as the reference value, and PRDs in the result of the other housing types were determined using Equation (1).

(1)

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Where PRD is Percentage of relative differences (%) Value.x is the value of housing type x (MJ/m2) Value.ref is the value of the detached house model (DH, MJ/m2) This method can indicate a positive or negative difference compared with the reference case and facilitates a comparison as an index. For instance, PRDs of -66.6% and -50% mean that the results

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from the housing type are, respectively, one-third or one-half of the results given by the reference housing type [51].

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3.5. Limitation and validity

This study includes uncertainties in the building models studied. As explained in section 3.1, the

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models were defined as a multiplication of the common space module without interior partition wall. Thus, the zoning of the interior space (e.g. living room, bath room, bed room) was not taken into

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consideration in the operational energy simulation. This simplification of the models would affect the results of the energy simulation to some extent. As demonstrated by Silva and Ghisi [52], for instance, the simplification of the thermal zones of the office building in Brasil increased the space heating

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energy demand up to 95.9% and decreased the cooling energy demand up to 45.0%. In addition, the exclusion of interior partition wall affects the embodied energy. Although it highly depends on the specifications and layout, the partition wall may share about 5-10% of the total production energy of a

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building [42, 53]. Geographical and temporal representativeness would also be a limitation of this

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study. The results of the study is limited to the current climate condition in Helsinki region. The operational energy profiles naturally vary depending on location, climate area and temporal climate condition used in the simulation, as demonstrated by several studies [12, 54-58]. For instance, Dodoo et al. [12] compared the final energy use for space heating of the case study building at the three different locations in Sweden; Växjö (56°9’N, 14°5’E), Östersund (63°2’N, 14°4’E) and Kiruna (67°8’N, 20°0’E). The results showed that the three locations bring about 1.5-2.5 times differences in the space heating energy demand. The simulation in different climate area would also influence the profile of building energy use (a ratio of energy use for heating, cooling, hot water, etc.) [55]. Furthermore, as Heinonen and Junnila [59] and Wright [60] noted, the functional unit (e.g. m2, capita, household) naturally affects the results, and also other factors (e.g. occupation rate, occupant’s incentives for energy efficient behaviour) may exceed the operational energy efficiency differences arising from the building types [59, 61]. However, on the other hand, as Nemry and Uilhein demonstrated [23], the order of magnitude differences between the housing types in terms of the primary energy use in the use and EoL stages seem to be the same regardless of the geographical zones (south, middle and north Europe). In addition, the embodied energy and the space heating energy demand seem to still be deeply related to the physical and compositional features of buildings

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[22]. After having understood these points, it can be thought that the methods and conditions used in this paper have a certain validity according to the purpose and scope of this study.

4. Results and Discussion

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4.1. Life cycle energy balance of the housing types Table 5 shows the life cycle primary energy balance of the reference buildings with the four structural frame materials, whilst figure 2 displays an overview of the results. Renewable and non-renewable

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primary energy (PER and PENR, respectively) consumptions and benefits are described in accordance with the life cycle stages studied. The black dotted line in Fig. 2 indicates the life cycle energy balance

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defined as the primary energy consumption (module A1-3, B2+4, B6 and C) minus the net primary energy benefit (module D). Module B6 shows only space heating energy use in order to clarify the influence of the configuration of the reference buildings. As a whole, the differences between the

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housing types are significant regardless of the frame materials. The detached house (DH) exhibits the highest value, the row house (RH) the second, the townhouse (TH) the third and the apartment block

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the lowest, on a per square meter basis. The PRDs in the results of the RH, TH and AB are respectively around -20%, -30% and -45% on the basis of the primary energy consumption. This finding is comparable to the results reported by previous studies [22, 23]. According to Nemry and

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Uihlein [23], for instance in north European countries, detached houses (single-family houses)

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required about 1.5 and 2.5 times more life cycle primary energy than apartment blocks (multi-family houses) and high-rise buildings, respectively. In addition, the results in terms of the embodied energy were compared with the study on the existing housings [62]. The actual values naturally differed each other, but it was confirmed that the relative relationship (order of magnitude differences) between the housing types are the same. The same trend could be seen in each life cycle stage as well, but the share of module B2+4 and C is very minor in the end results. The other operational renewable and nonrenewable primary energy (for ventilation, household electricity and domestic hot water heating) simulated are 5,785 MJ/m2 and 22,223 MJ/m2 respectively. This, of course, significantly affects the results in module B6 and the life cycle energy balance. The dominance of module B6 becomes much higher and the PRD between the reference buildings becomes less, although the relative relation of the building as such does not change. In general, the influence of the frame material selection seems to be relatively minor compared to the differences in the housing types. However, the differences between the wooden buildings (LWT and CLT) and non-wooden buildings (RC and Steel) are quite visible in module A1-3, C and D, corresponding with [12]. This result indicates the importance of looking out over the building life cycle when selecting the building material. For instance, CLT showed the largest primary energy consumption, which mainly originates in module A1-3. On the other hand, it also has the largest

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energy benefit from recycling of the building materials at the EoL stage. As a consequence, CLT shows the best results on the basis of the life cycle energy balance, which are more or less the same as LWT, which has the lowest energy consumption. In addition, other perspectives (e.g. cost, environmental impacts, psychological perception) should be taken into account in the material selection process [28, 42].

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4.2. Effects of building scale In order to observe the effects of building scale, a parametric study was carried out using the TH model with CLT frame (TH – CLT). As shown in figure 3, the calculation was conducted on the

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model as changing the number of apartments in a row and story. Table 6 shows the results of the study in comparison with the original TH – CLT model (3 apartments / 3 stories (3A3S)), whilst figure 4

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shows an overview of the results. As can be seen in the figure, the primary energy consumption and the life cycle energy balance decreased linearly as the number of apartments increased. The PRDs in

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the cases of 6 and 9 apartments (6A3S and 9A3S) are around -4% and -8%, respectively compared to the case of 3 apartments (3A3S), on the basis of the primary energy consumption. Increasing the number of apartments seems to be effective on every life cycle stage studied. On the other hand,

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although the result became better as the number of stories increased (from 3 to 4), decreasing the stories (from 3 to 2) made the result much worse. The PRDs in the results of 4 stories (3A4S) and 2 stories (3A2S) are respectively about -3% and 13%, compared to the case of 3 stories (3A3S), on the

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basis of the primary energy consumption. The effect of increasing the number of apartments (from 3 to

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6) and the number of stories (from 3 to 4) seems to be quite equal in this case.

4.3. Discussion

The results shown in previous sections would indicate that there is a correlation between the housing types and scale, and their life cycle energy balance, at least, on a per square metre basis. Each housing type has inherent features in its composition. For instance, in general, an apartment block has a larger floor area compared to a detached house, since it is a complex of several apartments, and apartments are sharing walls and floors (party wall and party floor) with each other in the block. This compositional difference would appear in ageometrical factor. Table 7 shows a comparison of the four housing types and the models used in the parametric study in terms of their geometrical factors. The ratio of outer surface area to net floor area (SA/NFA) represents the compactness of the buildings [63, 64]. The ratio of perimeter area (interior space under the roof and within 3m from the exterior walls) to net floor area (PA/NFA) indicates susceptibility of a building to outdoor condition (e.g. temperature). The ratio of net floor area to area in contact with ground (NFA/AG) represents an efficiency in terms of building footprint. The ratio of shared building element area (e.g. party wall) to

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total building element area (SEA/TEA) represents an efficiency in terms of space enclosure. The factors naturally vary when the basic compositions of the housing models (e.g. scale, number of story) are altered. However, an interrelation between the housing types would not significantly be changed as far as they are designed in commonsensible conditions.

Several studies have thus far been conducted in order to investigate the effect of building scale and

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shape on its energy performance [63-66]. It was commonly reported that the compactness of a building has a strong correlation with its energy efficiency. For instance, Depecker et al. [66] noted that the operational energy consumption is inversely proportional to the compactness in case of cold climate,

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whilst it cannot be applied in case of mild climate as the heat loss from the exterior wall surfaces are compensated by solar contributions penetrating through the glazing. In addition, in Lithuanian climate

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conditions, Parasonis et al. [63] demonstrated the relationship between the compactness and scale (50 to 5000m2) of a building on its annual heat loss through the external envelopes. The results showed

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that, in general, more compact and larger buildings have less heat losses. The results shown in sections 4.1 and 4.2 are in line with the trends reported in the previous studies; the operational energy consumption changes in proportion to the compactness and scale of the reference buildings. For

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instance, the TH and AB show about three-fourths and one-half of the DH as the SA/NFA ratio changes to two-thirds and one-third, respectively. The same trend could be observed when the number of apartments and stories changed. The effects of the compactness can be found over the building life

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cycle, which means that both the material quantity used and operational (space heating) energy

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demand can be reduced by increasing the compactness. The PA/NFA ratio should influence the space heating energy demand of the buildings. In the case of the DH showing the value 1.0, whole interior space subjects to the influence of outside temperature change and solar radiation, whilst 20% and 40% of the interior space in the RH/TH and AB, respectively, have the little influence. This index directly relates to the scale of a building. In general, the larger scale building is favourable to reduce the ratio, resulting in more stable indoor temperature change. The results shown in the previous sections can be explained from this aspect as well, although to enlarge the building scale in vertical direction would not be so effective, as can be seen in Tab 7. The NFA/AG ratio affects the embodied energy efficiency since, in many cases, the foundation accounts for major part of the material production energy of a building [53]. In this case, this ratio is simply correlated with the number of story. More story would be preferable in order to optimize the embodied energy due to the foundation, although the effect would not be in proportion to that since the size of the foundation normally increases when the number of story increases. For instance, the NFA/AG ratio improves when the number of story increases (from 3A3S to 3A4S), but as shown in figure 4, the effect of increasing the number of apartments (6A3S) and the number of story (3A4S) on the life cycle energy efficiency are almost the same. This results would indicate that the effect of this factor is relatively minor compared to the other factors. The

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SEA/TEA ratio seems to contribute both the embodied and operational energy efficiency. For instance, the value 0.5 (AB) indicates that a half of building elements are shared by different apartments. This would significantly save the building materials as well as improve the compactness of the building as appeared in the differences between the housing types. In this sense, the whole building should be constructed at the same time, instead of letting the individual owners do their construction work independently over a period of several years. If a row of the RH/TH, for example,

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would not be built at the same time, each apartment would require its own thermally insulated, loadbearing external wall also between the apartments. This would increase the energy required for

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modules A and C.

The differences between the RH and TH would originate mainly from the difference in the number

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of stories. However, the building configuration would also affect the end results to some extent. The townhouse includes the party floor for possible vertical division of the building into two apartments,

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which, in many cases, consists of more layers than an ordinary intermediate floor due to functions required, as shown in Tab 2. Thus, the party floor tends to bring higher embodied energy. The reason of the result for the TH with 2 stories (3A2S in table 6) showed much higher primary energy

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consumption than the case of 3 stories (3A3S in table 6), and an even worse result compared to the RH model shown in table 5, could be explained from this aspect.

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From the energy-efficiency perspective, planning denser and larger buildings would be reasonable.

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In this sense, an apartment block would be a better option due to its compositional feature, whilst a detached house seems not to be an energy-efficient housing type. However, on the basis of gross energy consumption, the larger building consumes more energy than the smaller one if they are totally the same in other conditions (e.g. energy performance, function, number of occupant). In addition, the energy efficiency per capita decreases when the building get larger [59, 67]. These aspects in terms of building energy use should be kept in mind when the scale of a building is considered. Moreover, from qualitative aspects, such as the amenity originating in the privacy of living and density of a housing area, a detached house would be preferable. City planning is a complex issue, in which several aspects need to be taken into account. In such a context, a townhouse building might be a good solution as an intermediate option that could balance several criteria. In addition, it would also be reasonable to combine different housing types in an area for the sustainable urban development. For instance, the energy efficiency level may be set on an areal basis rather than on a building level. In this case, the energy requirement may be able to be compensated among buildings in the area. This kind of approach may bring more flexible planning and rational investment to the city development.

12 Page 13 of 31

5. Conclusions This study has demonstrated the life cycle primary energy balance of the four residential building types (detached house, row house, townhouse and apartment block) based on current building codes and common building services in Finland. The differences in the life cycle energy efficiency arising from the geometrical characteristics of each housing type were investigated using hypothetical building models. In addition, the influence of structural material selection was observed in relation to

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There are clear differences between the housing types: the detached house is the highest energy consumer, the row house the second (about 20% less), the townhouse the third (about 30% less) and the apartment block the lowest (about 45% less). The differences appear evenly among the building life cycle stages. The influence of structural material selection is relatively minor compared to the differences in the housing types. In principle, the life cycle energy efficiency of a building increases as the number of stories and floor area increase.

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the housing types. A summary of the results are:

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The results were discussed by focusing on the geometrical factors (ratios of outer surface area/net floor area, perimeter area/net floor area, net floor area/ area in contact with ground and shared building element area/total building element area) of each housing type. Although it is difficult to explicitly

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quantify the relationship between the factors and the results, a clear correlation could be seen. The life

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cycle energy efficiency increases as the geometrical factors becomes better. It can be concluded that the apartment block has the highest life cycle energy efficiency (a per square meter basis) thanks to its 1) compactness, 2) scale in relation to perimeter area ratio and 3) ratio of shared building elements. On the contrary, the detached house has the worst efficiency due to the same reason. Nevertheless, since an arrangement of the geometrical factors would relatively be easy during the design phase, an awareness of the correlation is the first step in the energy efficient housing project regardless of the housing types.

Sustainable urban development shall take several aspects into consideration, such as amenity, cost and environmental impacts. A diverse areal concept should be important, and an exercise such as this study would be helpful to develop a criterion. Although the present study is limited to certain conditions, it gives an idea for reasonable residential area planning. A deeper study will be the next step, including, for instance, different geographical and temporal representativeness, different functional unit (e.g. per capita, per household), the survey of the actual energy profiles of the residential buildings including the occupant’s behaviour, the statistical analysis of existing buildings

13 Page 14 of 31

and the assessment of other sustainable indicators, such as life cycle cost and environmental impacts in order to develop a more comprehensive decision support system.

Acknowledgments This study was carried out in the research project Energy Efficient Townhouse, as a part of the

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Aalto University energy efficiency research programme. The authors gratefully acknowledge the

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assistance of all concerned.

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References

1. IEA (International Energy Agency). Technology roadmaps – Energy efficient buildings:

Ac ce pt e

d

M

an

us

cr

ip t

Heating and Cooling equipment. 2011. Available online at: http://www.iea.org/ (accessed on 3 April, 2013) 2. Fay R, Graham T, Usha IR. Life-cycle energy analysis of buildings: a case study. Build Res Inf 2000, 28(1):31–41. 3. Ortiz S, Castells F, Sonnemann G. Sustainability in the construction industry: A review of recent developments based on LCA. Constr Build Mater 2009, 23(1):28–39. 4. Passer A, Kreiner H, Maydl P. Assessment of the environmental performance of buildings: A critical evaluation of the influence of technical building equipment on residential buildings. Int J LCA 2012, 17(9):1116–1130. 5. Verbeeck, G, Hens H. Life Cycle Optimization of Extremely Low Energy Dwellings. J Build Phys 2007, 31(2):143–177. 6. Mohammed TI, Greenough R, Taylor S, Meida LO, Acquaye A. Operational vs. embodied emission in buildings – A review of current trends. Energy Build 2013, 66: 232-245. 7. Karimpour M, Belusko M, Xing K, Bruno F. Minimising the life cycle energy of buildings: Review and analysis. Build Environ 2014, 73: 106-114. 8. Verbeeck G, Hens H. Life cycle inventory of buildings: A contribution analysis. Build Environ 2010, 45: 964-967. 9. Ramesh T, Prakash R, Shukla KK. Life cycle energy analysis of buildings: An overview. Energy Build 2010, 42: 1592-1600. 10. Sartori I, Hestnes AG. Energy use in the life cycle of conventional and low-energy buildings: A review article. Energy Build 2007, 39: 249-257. 11. European commission. Report from the commission to the European parliament and the council, Progress by Member states towards Nearly Zero-Energy Buildings. Available online at: http://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:52013DC0483R%2801%29&from=EN (accessed at 12 October 2013) 12. Dodoo A, Gustavsson L, Sathre R. Effect of thermal mass on life cycle primary energy balances of a concrete- and a wood-frame building. Appl Energ 2012; 92: 462-472. 13. D’Agostino D. Assessment of the progress towards the establishment of definitions of Nearly Zero Energy Buildings (nZEBs) in European Member States. J Build Eng 2015, 1: 20-32.

14. UNEP (United Nations Environmental Programme). Building and Climate change, Status, Challenges and Opportunities. 2007. Available online at: http://www.unep.fr/shared/publications/pdf/DTIx0916xPA-BuildingsClimate.pdf (accessed on 21 October, 2014) 15. Agence de l’Environnement et de la Maîtrise de l’Énergie (ADEME). Energy Efficiency Trends in Buildings in the EU – Lessons from the ODYSSEE MURE project. enerdata. 2012. Available online at: http://www.odyssee-mure.eu/publications/br/Buildings-brochure-2012.pdf (accessed on 11 November 2014) 16. City of Helsinki Urban facts. City of Helsinki statistical service. 2013. Available online at: http://www.hel.fi/hki/tieke/en/etusivu (accessed on 9 November 2014) 17. Strandell A. Asukasbarnometri 2010. Asukaskysely suomalaisista asuinympäristöistä. Suomen ympäristö 2011, 31 (Finnish). Suomen ympäristökeskus (Finnish Environment Institute). Helsinki 18. European Environmental Agency. Urban sprawl in Europe, The ignored challenge. EEA report 10/2006. 2006. Available online at: www.eea.europa.eu/publications/eea_report.../eea_report_10_2006.pdf (accessed on 11 January 2015) 19. City of Helsinki Economic and Planning Centre. Home town Helsinki – The goals and objectives of housing and land use planning. 2012. Available online at:

15 Page 16 of 31

Ac ce pt e

d

M

an

us

cr

ip t

http://www.uuttahelsinkia.fi/sites/default/files/osion_artikkelisivun_osa/liitetiedostot/home_to wn_helsinki_2012.pdf (accessed on 9 November 2014) 20. City of Helsinki. The Helsinki action plan for sustainability. 2002. Available online at: http://www.hel.fi/static/ymk/esitteet/action-plan-for-sustainability.pdf (accessed on 12 December 2014) 21. Silfverberg K, Huuska P, Lukin M. Environmental sustainability issues and challenges in Helsinki 2010. City of Helsinki. 2010. Available online at: http://www.hel.fi/static/ymk/esitteet/environmental-sustainability.pdf (accessed on 12 December 2014) 22. Cuéllar-Franca RM, Azapagic A. Environmental impacts of the UK residential sector: Life cycle assessment of houses. Build Environ 2012, 54: 86-99. 23. Nemry F and Uihlein A. Environmental improvement potentials of residential buildings (IMPRO-Building). European Comission, Joint Research Centre (JRC) Scientific and Technical Reports. 2008. 24. Gustavsson L and Joelsson A. Life cycle primary energy analysis of residential buildings. Energy Build 2010, 42: 210-220. 25. Esen H, Inalli M, Esen M. Technoeconomic appraisal of a ground source heat pump system for a heating season in eastern Turkey. Energ Convers Manage 2006, 47: 1281-1297. 26. Thormark C. The effect of material choice on the total energy need and recycling potential of a building. Build Environ. 2006; 41: 1019-1026. 27. Cole RJ. Energy and greenhouse gas emissions associate with the construction of alternative structural systems. Build Environ 1999; 34(3): 335-348. 28. Takano A, Sudip SK, Kuittinen M, Alanne K, Hughes M, Winter S. The effect of material selection on life cycle energy balance: A case study on a hypothetical building model in Finland. Build Environ 2015; 89:192-202. 29. Jokisalo J, Kurnitski J. 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. Laboratory of Heating, ventilating and Air-Conditioning. 2005 30. Ståhl F. Influence of thermal mass on the heating and cooling demands of a building unit. PhD dissertation, Department of Civil and Environmental Engineering, Chalmers University of Technology. Göteborg. 2009 31. Zhu L, Hurt R, Correia D, Boehm R. Detailed energy saving performance analyses on thermal mass walls demonstrated in a zero energy house. Energy Build. 2009; 41: 303-310. 32. EN15978: 2011, Sustainability of construction works – Assessment of environmental performance of buildings – Calculation method. European Committee for Standardization. 33. The national building code of Finland, G1 Housing design, Regulation and guidelines. 2005. Ministry of the Environment of Finland. 34. Ourghi R, Al-Anzi A, Krarti M. A simplified analysis method to predict the impact of shape on annual energy use for office buildings. Energ Convers Manage. 2007; 48: 300-305. 35. The national building code of Finland, E1 Fire safety of buildings, Regulation and guidelines. 2002. Ministry of the Environment of Finland. 36. Palolahti T, Kivimäki C, Mäki T. ROK – Rakennusosien Kustannuksia 2013. Rakennustieto Oy. 2013. ISBN 9789522670359. 37. The national building code of Finland, D3 Energy efficiency of buildings, Regulations and guidelines. 2012. Ministry of the Environment of Finland. 38. ISO 14040: 2006, Environmental management – Life cycle assessment – Principles and frameworks. International Organization for Standardization. 39. ISO 14044: 2006, Environmental management – Life cycle assessment – Requirements and guidelines. International Organization for Standardization.

16 Page 17 of 31

40. Ecoinvent

Ac ce pt e

d

M

an

us

cr

ip t

center. The ecoinvent database V3.01. Available online at: http://ecoinvent.org/database/ (accessed on 10 October 2014) 41. EQUA Simulation AB. IDA indoor climate and energy (IDA ICE). Available online at: http://www.equa.se/index.php/en/ (accessed on 30 October 2014) 42. Takano A, Hughes M, Winter S. A multidisciplinary approach to sustainable building material selection: A case study in a Finnish context. Build Environ 2014; 82: 526-535. 43. Finnish ministry of the Environment. Pientalon Huoltokirja (Single family house service book). 2008. Available online at: http://www.neuvoo.fi/LinkClick.aspx?fileticket=vEPqO6/HHDc= (accessed on 7 July 2014) 44. Finnish energy industries (Energiateollisuus ry). District heating in Finland 2013. Available online at: http://energia.fi/en/statistics-and-publications/district-heating-statistics/districtheating (accessed on 9 November 2014) 45. Kalamees T, Jylhä K, Tietäväinen H, Jokisalo J, Ilomets S, Hyvönen R, Saku S. Development of weighing factors for climate variables for selecting the energy reference year acoording to the EN ISO 15927-4 standard. Energy Build 2012; 47: 53-60. 46. The national building code of Finland, D5 Calculation of power and energy needs for heating of buildings, Guidelines. 2012. Ministry of the Environment of Finland. 47. Shemeikka J, Laitinen A. Specification of RET-single family house. Technical research center of Finland VTT, Building and Transport. Version 2.0. 2005. (in Finnish) 48. ISO/FDIS 10456:2007(E). Building materials and products – Hygrothermal properties – Tabulated design values and procedures for determining declared and design thermal values. International Standards Organization 49. European Commission (DG ENV). Service contract on management of construction and demolition waste – SR1, Final report Task 2. 2011. Available online at: http://ec.europa.eu/environment/waste/pdf/2011_CDW_Report.pdf (accessed on 20 September 2014) 50. Kuosa H. Reuse of recycled aggregates and other C&D wastes. technical research centre of Finland VTT, research report VV-R-05984-12. 2012. Available online at: http://www.vtt.fi/inf/julkaisut/muut/2012/VTT-R-05984-12.pdf (accessed on 20 September 2014) 51. Peeredoom EC, Kleijn R, Lemkowitz S. Lundie S. Influence of Inventory Data Sets on LiceCycle Assessment Results: A Case study on PVC. J Ind Eco. 1999; 2 (3): 109-147. 52. Silva AS, Ghisi E. Uncertainty analysis of the computer model in building performance simulation. Energy Build 2014; 76: 258-269. 53. Kuittinen M, Ludvig A, Weiss G (eds). Wood in carbon efficient construction - Tools, methods and application. 2013. CEI –Bois, Belgium. 54. Olofsson T, Mahlia TMI. Modeling and simulation of the energy use in an occupied residential building in cold climate. Appl Energ 2012; 91: 432-438. 55. Zhao M, Künzel HM, Antretter F. Parameters influencing the energy performance of residential buildings in different Chinese climate zones. Energy Build 2015; 96: 64-75. 56. Tuhus-Dubrow D, Krarti M. Genetic-algorithm based approach to optimize building envelope design for residential buildings. Build Environ 2010; 45: 1574-1581. 57. Jylhä K et al. Energy demand for the heating and cooling of residential houses in Finland in a changing climate. Energy Build 2015; 99: 104-116. 58. Kalvelage K, Passe U, Rabideau S, takle ES. Changing climate: The effects on energy demand and human comfort. Energy Build 2014; 76: 373-380.

17 Page 18 of 31

59. Heinonen J, Junnila S. Residential energy consumption patterns and the overall housing

Ac ce pt e

d

M

an

us

cr

ip t

energy requirements of urban and rural households in Finland. Energy Build 2014; 76: 295303. 60. Wright A. What is the relationship between built form and energy use in dwellings? Energy Policy 2008; 36: 4544-4547. 61. Audenaert A, Briffaerts K, Engels L. Practical versus theoretical domestic energy consumption for space heating. Energy Policy 2011; 39: 5219-5227. 62. Takano A. Rakennusmateriaalien energiatehokkuus (Energy efficiency from building material perspectives), in Kuittinen M (eds) Energiatehokas townhouse (Energy efficient townhouse). In Finnish. Aalto University publication series Cross Over. 2014. Finland 63. Parasonis J, Keizikas A, Kalibatien D. The relationship between the shape of a building and its energy performance. AEDM. 2012; 8: 246-256. 64. Parasonis J, Keizikas A, Endriukaityte A, Kalibatien D. Architectural solutions to increase the energy efficiency of buildings. J Civ Eng Manag. 2012; 18 (1): 71-80. 65. Bostancioglu E. Effect of building shape on a residential building’s construction, energy and life cycle cost. Archit Sci Rev. 2010; 53: 441-467. 66. Depecker P, Menezo C, Virgone J, Lepers S. Design of building shape and energetic consumption. Build Environ. 2001; 36: 627-635. 67. Bastos J, Batterman SA, Freire F. Life-cycle energy and greehouse gas analysis of three building types in a residential area in Lisbon. Energy Build 2014; 69: 344-353.

18 Page 19 of 31

Table captions Table 1 Basic information of the reference buildings and surface area of each building element Table 2 Composition of each building element with the four frame materials Table 3

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Expected service life, maintenance interval and maintenance measure of the building materials Table 4

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End of life recycling scenarios of the materials Table 5

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Life cycle primary energy balance (renewable (PER) and non-renewable (PENR)) of the reference building with the four structural frame materials Table 6

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Life cycle primary energy balance (renewable (PER) and non-renewable (PENR)) of the townhouse model with CLT frame, changes in the number of apartments and floors Table 7

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Figure captions

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Geometrical factors of the reference buildings and the models used in the parametric study

Figure 1

Plan and section of the reference building models with the indication of building elements Figure 2

Overview of the results from the comparison of the reference buildings with the four alternative frame materials Figure 3

Parametric study by changing the number of apartment and floor on the TH model with CLT frame Figure 4

Overview of the results from the parametric study

19 Page 20 of 31

Table(s) with Caption(s)

Table 1. Basic information of the reference buildings and surface area of each building element

(m2) RH 3 2

TH 3 3

AB 20 4

Gross floor area

120

360

540

1920

Net heated floor area

96

316

475

1775

Foundation + ground floor slab

48

154

154

425

Exterior wall

186

301

453

933

Party wall

0

103

230

684

Interior structural wall

0

0

0

197

Intermediate floor

52

166

166

0

Party floor

0

0

166

1335

Roof

60

180

180

480

Window / Door

10

32

47

178

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included in the intermediate and party floor

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Staircase

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Apartment Story

DH 1 2

Page 21 of 31

Table 2. Composition of each building element with the four frame materials Foundation + Ground floor Exterior wall Material

RC

Steel

Wood plank (Painted)

t (mm) kg/m2 28 13

Interior structural wall

t (mm) kg/m2 Gypsum board (Painted) 26 *2 52 Material

Intermediate floor

t (mm) kg/m2 Gypsum board (Painted) 30*2 60 Material

Material Wood plank (Painted)

Party floor t (mm) kg/m2 28 13

Roof

Material Wood plank (Painted)

t (mm) kg/m2 28 13

Material PVC sheet

t (mm) kg/m2 1.2 2

Reinforced concrete slab

80

194

Wood batten

30

2

Timber stud

100*2

8

Timber stud

120

13

Particleboard

22

15

Concrete

60

120

OSB

18

Reinforced concrete footing

440

741

Vapour barrier sheet

0.1

0.2

Rock wool

100*2

5

Rock wool

120

3

Timber joist

225

23

PVC sheet

0.2

0.2

Wood batten

38+50

7

Vapour barrier fleece

0.5

0.2

Timber stud

270

27

Rock wool

150

3

Timber joist

225

23

Rock wool

500

27

EPS

150

5

Rock wool

270

8

Gypsum board (Painted)

13

13

Rock wool

130

4

Timber truss

-

9

Gravel

100

90

Gypsum board (Painted)

25

15

Plywood

18

8

Vapour barrier sheet

0.1

0.2

Gypsum board (Painted)

30

30

Wood backing

48

3

Gypsum board (Painted)

30

30

10

28

13

Wood plank (Painted)

28

13

Gypsum board (Painted)

15*2

30

Gypsum board (Painted)

30*2

60

Wood plank (Painted)

28

13

Wood plank + Paint

28

13

PVC sheet

1.2

2

Reinforced concrete slab

80

194

Wood batten

30

2

CLT

100*2

94

CLT

100

47

Particleboard

22

15

Concrete

75

150

OSB

18

10

Reinforced concrete footing

440

931

Rock wool

360

25

Rock wool

50

1.5

Timber joist

225

23

PVC sheet

0.2

0.2

LVL beam

300

18

Vapour barrier fleece

0.5

0.5

CLT

100

47

Rock wool

150

3

Wood board

18

8

Rock wool

400

20

EPS

150

5

*Gypsum board (Painted)

15

15

Gypsum board (Painted)

13

13

Timber joist

300

30

CLT

120

56

Gravel

100

90

Rock wool

100

2

*Gypsum board (Painted)

30

30

CLT

80

38 20

ed

Wood plank (Painted)

Gypsum board (Painted)

20

Wood plank (Painted)

28

13

Wood plank (Painted)

28

13

PVC sheet

1.2

2

2

Cement screed

5

10

Reinforced concrete

70

140

OSB

18

10

220

533

Hollow concrete slab

265

289

Rock wool

30

2

Wood batten

38

4

240

19

Sand

5

9

Rock wool

430

30

Hollow concrete slab

200

240

ce pt

CLT

Wood plank (Painted)

Party wall

Material

Wood plank (Painted)

28

13

Wood plank (Painted)

28

13

Reinforced concrete slab

80

194

Wood batten

30

Reinforced concrete footing

440

1.299

Reinforced concrete

Vapour barrier fleece

0.5

0.2

Rock wool

EPS

150

5

Gravel

100

90

Reinforced concrete

180

442

Reinforced concrete

180

442

Timber truss

-

9

Vapour barrier sheet

0.1

0.2

Hollow concrete slab

175

205

Wood plank (Painted)

28

13

Wood plank (Painted)

28

13

Gypsum board (Painted)

26*2

52

Gypsum board (Painted)

26*2

52

Wood plank (Painted)

28

13

Wood plank (Painted)

28

13

PVC sheet

1.2

2

Reinforced concrete slab

80

194

Wood batten

30

2

Steel stud

150

4

Steel stud

150

4

Particleboard

22

15

Cement screed

5

10

OSB

18

10

Reinforced concrete footing

440

726

Rock wool

100

3

Rock wool

100

3

30

Vapour barrier fleece

0.5

0.2

EPS

150

5

Gravel

100

90

* Only in the case of TH and AB

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LWT

t (mm) kg/m2 28 13

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Table(s) with Caption(s)

Gypsum board

9

9

Steel joist

200

7

Reinforced concrete

200

482

Rock wool

500

Steel stud

250

8

Rock wool

150

5

Corrugated steel sheet

0.7

7

Steel truss

-

10

Rock wool

250

8

Gypsum board (Painted)

13

13

Gypsum board (Painted)

13

13

Vapour barrier sheet

0.1

0.2

Gypsum board (Painted)

13

13

Steel backing

50

5

Gypsum board (Painted)

30

30

Page 22 of 31

Table(s) with Caption(s)

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Table 3. Expected service life, maintenance interval and maintenance measure of the building materials Expected service life (year) Maintenance interval (year) Maintenance Structural frame All 50 Sheathing Gypsum board 50 20 (wall) or 30 (ceiling) Repaint Cladding / Flooring Wood plank 50 10 Repaint Roofing PVC sheet 25 Inner components All 50 Window / Door Wood frame 50 10 Repaint

Page 23 of 31

Table(s) with Caption(s)

Substitution Coal Gravel Ore-based steel Coal Gypsum (Stucco) -

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Table 4. End of life recycling scenarios of the materials Material End of life scenario Secondary application Wood Recycle Fuel Concrete Recycle Aggregate Steel Recycle Steel Plastic Recycle Fuel Gypsum / Plaster Recycle Gypsum powder Mineral Landfill -

Page 24 of 31

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Table(s) with Caption(s)

PENR -3926 -2712 -2756 -2316

PRD -31% -30% -41%

PRD -18% -29% -45%

13688 10919 9663 7415

-20% -29% -46%

5 5 4 4

201 176 157 151

-12% -22% -25%

-39 -33 -35 -32

-6273 -5196 -5708 -5147

-17% -9% -18%

6027 4840 4441 3509

11906 9343 7434 5129

-21% -34% -52%

130 101 83 62

-23% -36% -53%

4836 3819 3381 2459

13511 10667 9444 6868

-20% -30% -47%

18 13 12 10

610 438 424 342

-28% -30% -44%

-35 -27 -25 -19

-2493 -1886 -1651 -1233

-24% -34% -50%

5197 4076 3605 2625

15480 11994 10700 7883

-22% -31% -49%

160 122 106 80

-24% -34% -50%

4942 3937 3488 2693

13806 10998 9745 7523

-20% -29% -46%

5 4 5 6

177 143 162 193

-19% -9% 9%

-40 -29 -28 -23

-2599 -1892 -1738 -1367

-27% -33% -47%

5230 4147 3678 2840

14709 11881 10544 8313

-20% -29% -44%

4157 3323 3216 2631

-19% -20% -34%

7 7 6 5

133 122 106 80

RC

DH RH TH AB

370 266 232 171

3722 2675 2400 1845

-28% -36% -51%

7 5 5 4

Steel

DH RH TH AB

313 229 206 160

3166 2510 2269 1883

ed

M

1154 953 1007 878

ce pt

PRD -21% -29% -36%

Life cycle balance PER PENR 5450 12614 4303 10517 3873 8965 3050 6921

4900 3909 3459 2654

DH RH TH AB

Ac

9 7 6 5

PENR 192 152 135 123

D PER -28 -20 -20 -17

-8% -20% -40%

CLT

-21% -29% -41%

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Table 5. Life cycle primary energy balance (renewable (PER) and non-renewable (PENR)) of the reference building with the four structural frame materials MJ/m2 (net heated floor area) A1-3 B2+4 B6 C PER PENR PRD PER PENR PRD PER PENR PRD PER LWT DH 545 2445 9 160 4919 13743 5 RH 379 1959 -22% 8 132 -18% 3933 10986 -20% 4 TH 407 1788 -27% 5 84 -48% 3477 9714 -29% 4 AB 372 1528 -36% 5 80 -50% 2687 7506 -45% 4

Page 25 of 31

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Table(s) with Caption(s)

3216 2996 2928 3803 2921

-6% -8% 18% -9%

6 6 6 7 6

M

1007 963 949 1197 911

106 98 96 125 97

-8% -10% 17% -8%

3459 3354 3225 3891 3346

9663 9370 9010 10870 9348

-3% -7% 12% -3%

4 4 4 6 3

PRD

157 149 146 210 131

-5% -7% 34% -17%

-35 -33 -33 -41 -31

PENR -5708 -5466 -5393 -6621 -5251

PRD

Life cycle balance PER PENR

PRD

-4% -6% 16% -8%

4441 4293 4151 5060 4235

-4% -8% 13% -3%

7434 7146 6787 8386 7246

d

3 apartments / 3 stories (3A3S) 6 apartments / 3 stories (6A3S) 9 apartments / 3 stories (9A3S) 3 apartments / 2 stories (3A2S) 3 apartments / 4 stories (3A4S)

PENR

D PER

Ac ce pt e

TH with CLT frame

an

Table 6. Life cycle primary energy balance (renewable (PER) and non-renewable (PENR)) of the townhouse model with CLT frame, changes in the number of apartments and floors MJ/m2 (net heated floor area) A1-3 B2+4 B6 C PER PENR PRD PER PENR PRD PER PENR PRD PER

Page 26 of 31

Table(s) with Caption(s)

Table 7. Geometrical factors of the reference buildings and the models used in the parametric study

RH

3.2 1.0 2.0 0

2.1 0.8 2.1 0.1

TH (3A3S) 1.8 0.8 3.1 0.3

AB

6A3S

9A3S

3A2S

3A4S

1.1 0.6 4.2 0.5

1.53 0.75 3.12 0.32

1.46 0.74 3.12 0.33

2.12 0.85 2.05 0.33

1.58 0.77 4.11 0.25

Ac c

ep t

ed

M

an

us

cr

ip

t

Outer surface area / Net floor area (SF/NFA) Perimeter area / Net floor area (PA/NFA) Net floor area / Area in contact with ground (NFA/AG) Shared element area / Total element area (SEA/TEA)

DH

Page 27 of 31

M

an

us

cr

ip t

Figure(s)

Interior structural wall

Roof

Intermediate floor

2F

1F Detached house (DH)

18000

10000

10000

18000

10000

6000

Ac ce p

Party wall / Party floor

16000

Foundation / Ground floor / Exterior wall

te

N

d

30000

Row house (RH)

2-4F

2F

2-3F

1F

1F

1F

Townhouse (TH)

Apartment block (AB) Cold attic

4F 3F

3F 2F

2F

1F

1F

1F

2F28 of 31 Page 3000

2F

1F

ip t

Figure(s)

AB TH

cr

Steel RH

us

DH AB

an

TH RC

M

RH DH

d

AB TH

te

CLT RH

Ac ce p

DH AB TH

LWT

RH

DH

-10000

-5000

0

5000

10000

15000

20000

25000

2

MJ/m (net heated floor area) Module A1-3: PER

Module B2+4: PER

Module B6: PER

Module C: PER

Module D: PER

Module A1-3: PENR

Module B2+4: PENR

Module B6: PENR

Module C: PENR

Module D: PENR

Life cycle energy balance (Consumption (Module A1-3, B2+4, B6 and C) - Benefit (Module D))

Page 29 of 31

Figure(s)

Townhouse (TH) - CLT frame - 3 stories

us

cr

ip t

3 apartments “3A3S”

Ac ce p

te

d

M

an

6 apartments “6A3S”

9 apartments “9A3S”

Townhouse (TH) - CLT frame - 3 apartments

2 stories “3A2S”

3 stories “3A3S”

4 stories “3A4S”

Page 30 of 31

us

cr

ip t

Figure(s)

an

3A4S

3A2S

M

9A3S

CLT - TH

6A3S

0

5000

te

-5000

10000

15000

20000

25000

2

MJ/m (net heated floor area)

Module A1-3: PER

Module B2+4: PER

Ac ce p

-10000

d

3A3S (Original)

Module A1-3: PENR

Module B2+4: PENR

Module B6: PER

Module C: PER

Module D: PER

Module B6: PENR

Module C: PENR

Module D: PENR

Life cycle energy balance (Consumption (Module A1-3, B2+4, B6 and C) - Benefit (Module D))

Page 31 of 31