Top-down or bottom-up? – How environmental benchmarks can support the design process

Accepted Manuscript Top-down or bottom-up? – How environmental benchmarks can support the design process Alexander Hollberg, Thomas Lützkendorf, Guillaume Habert PII:

S0360-1323(19)30129-5

DOI:

https://doi.org/10.1016/j.buildenv.2019.02.026

Reference:

BAE 5985

To appear in:

Building and Environment

Received Date: 23 October 2018 Revised Date:

1 February 2019

Accepted Date: 19 February 2019

Please cite this article as: Hollberg A, Lützkendorf T, Habert G, Top-down or bottom-up? – How environmental benchmarks can support the design process, Building and Environment (2019), doi: https://doi.org/10.1016/j.buildenv.2019.02.026. 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.

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Number of words: 7810 words (without references)

Top-down or bottom-up? – How environmental benchmarks can support the design process

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Alexander Hollberg1*, Thomas Lützkendorf2, Guillaume Habert1

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Centre for Real Estate, Department of Economics, Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany

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*Corresponding author, e-mail address: [email protected]

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Buildings are responsible for a large share of greenhouse gas (GHG) emissions. The use of Life Cycle Assessment (LCA) during the design phase can help to improve the environmental performance of buildings. However, designers and clients find it difficult to set environmental performance targets and interpret the results obtained through LCA in order to improve the building design. Therefore, reference values or benchmarks are needed. Current available LCA-based benchmarks have mostly been developed for certification systems on whole building level and do not provide design guidance on material or element level. To close this gap, this paper introduces an alternative approach that supports the design process by providing guidance and encouraging to improve the environmental performance. The aim of this approach is to support exploiting the optimization potential particularly regarding the embodied GHG emissions related to the manufacturing of construction products and to the construction, maintenance and demolition of the building. The concept consists in combining topdown benchmarks per capita derived from the capacity of the global eco system with bottom-up reference values for building components that are defined based on a statistical best-in-class approach (top 5%) using the market share of different construction products. Benchmarks for GHG emissions for new residential buildings in Switzerland are discussed. The results of applying the dual benchmark approach to a case study show that it can facilitate the use of LCA-based tools for design support and promote the optimization of the building-related environmental performance.

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Abstract

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Institute of Construction and Infrastructure Management, Chair of Sustainable Construction, Swiss Federal Institute of Technology (ETH Zurich), Stefano Franscini Platz 5, 8093 Zurich, Switzerland

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Keywords: Life Cycle Assessment, Benchmarks, Greenhouse gas emissions, Climate targets, Environmental design

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1 Introduction

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1.1 Need for environmental benchmarks for buildings

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In total, the built environment is responsible for more than one third of global greenhouse gas (GHG) emissions [1]. As such, the built environment must be addressed for climate change mitigation. Until now, the efforts to reduce GHG emissions in the building sector mainly focused on the use phase of 1

ACCEPTED MANUSCRIPT buildings. Due to the achievements in reducing the operational energy demand, amongst other reasons, researchers have turned to other fields to investigate additional saving potentials. An important aspect are the so-called embodied GHG emissions related to the manufacturing of construction products and to the construction, maintenance and end of life of buildings. Next to databases, suitable calculation tools are needed for assessing embodied GHG emissions. In this context, the particular importance of environmental benchmarks has been recognized early [2]. Driven by the increasing spread and application of Life Cycle Assessment (LCA) and sustainability certification systems, there is a need for benchmarks for the evaluation of the environmental performance of buildings including GHG emissions throughout the whole life cycle.

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The requirements for environmental benchmarks depend on the actors using them. Designers can largely influence the environmental performance of a building through their decisions. Decisions regarding the type of construction, main materials, energy concept, etc., largely determine the environmental performance of the building for the next 50 to 100 years. Therefore, designers are key actors for reducing global GHG emissions during the life cycle of individual buildings. Evaluating the building design by using LCA is not sufficient on its own, as it does not improve the design automatically [3]. Therefore, optimization is needed. However, currently, designers often find it difficult to interpret the LCA results and use them to improve the building design. Amongst others, there is a demand for benchmarks on GHG emissions in the different phases of the building’s life cycle that serve as an orientation for designers [4]. In real design situations, designers rarely look for the most environmentally friendly building (just as one would rarely look for the cheapest building) [5], but for one that meets a certain environmental performance. Especially the early design stages have a great influence on the environmental performance of the building throughout its life cycle [6]. Therefore, benchmarks should provide design guidance from the beginning of the design. A number of software to facilitate LCA for designers has been published in the last years, e.g. Tally [7], oneClickLCA [8], Athena [9], or CAALA [10]. However, they do not provide benchmarks that indicate the potential for improvement during the design.

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Designers are not independent in their decisions. Next to valuation agents, banks and public funding agencies, key actors are clients, investors and building owners. It is their task to define targets for the project and to control and monitor achieving these targets. EN 15643-1 [11] explicitly states that targets for the environmental performance shall be defined among others. Clients need support in defining these targets. Therefore, there is a demand for target values for the environmental performance including targets for GHG emissions.

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1.2 LCA-based benchmarks – state of the art

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Various types of benchmarks for the environmental performance of buildings can be found in the literature or in sustainability certification systems today. Furthermore, a vast number of different terms for benchmarks can be found. In the following, existing approaches for developing and using benchmarks are categorized to provide an overview.

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Whole life cycle versus life cycle phase-related benchmarks

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A main question regarding benchmarks is whether a value for the whole life cycle of the building or a benchmark for individual life cycle phases should be provided. SIA 2040 [13] provides a common target value including embodied impacts, operational impacts, and impacts due to building-related mobility. On the one hand, combining these domains allows holistically optimizing the building and compensating a high demand in one domain with savings in another domain. On the other hand, combined benchmarks might be more difficult to use as guidance in the design process. The question whether a certain amount of embodied impact is high or low compared to similar buildings cannot be answered by these common benchmarks. SIA 2040 therefore provides individual target values for the three domains in addition.

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ACCEPTED MANUSCRIPT Limit, reference, best practice, and target values

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Häkkinen et al. [14] and Lützkendorf et al. [15] differentiate between limit, reference, best practice, and target values. The limit value is defined as the lowest acceptable value of an evaluation scale representing generally the minimum acceptable performance. The reference value represents the present state of the art (business as usual) and can be considered as an average or median value. Therefore, it is subject to temporal dynamics. The best-practise value represents values that have been reached in experimental or demonstration projects. Braune and Wittstock [16] call this approach "yardstick competition", for example taking 10% of the best performing buildings as benchmarks (also referred to as “best in class” approach). These values are subject to technological advances and consequently evolve with time. According to Häkkinen et al. [14], the target value is a value that can only be reached in medium or long-term perspective. It represents the upper limit of the scale and can be considered as the highest theoretically possible level (at least within a certain technology). Target values must adapt periodically to the scientific and technical progress.

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Top-down benchmarks

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Top-down benchmarks are typically defined based on a political target, for example, the 2-degree target defined in the Paris Agreement in 2015 or the 2000 Watt society [17]. Braune and Wittstock [16] call this type of benchmarks "externally motivated benchmarks". The targets must be “translated” into building specific targets [14]. For Switzerland, the Swiss energy efficiency path described in SIA 2040 [13] defines targets for GHG emissions based on the 2000 Watt society. Zimmermann et. al. [18] define a target value for GHG emissions of 370 kg CO2-e/(c⋅a) for the housing sector per capita also based on the goals of the 2000 Watt society. Hoxha et al. [19] use a similar approach to define top-down targets for GHG emissions per energy reference area for different building types. The values relate to the intermediate target for the year 2050 defined in the 2000-Watt Society vision and assume a use phase of 60 years. Depending on the type of building, the targets for annual GHG emissions including embodied and operational impacts vary from 11 kg CO2-e/(m²⋅a) for residential buildings to 20.3 kg CO2-e/(m²⋅a) for restaurants. Russell-Smith et al. [20] use top-down reduction targets for a target value design strategy. The target values are defined for the whole life cycle of commercial buildings assuming a 50-year use phase. The target aims for a 70% reduction for operational impacts from 1990 levels and a 15% reduction for embodied impacts. The resulting target value for total GHG emissions is 45.9 kg CO2-e/(m²⋅a).

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Bottom-up benchmarks

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Bottom-up benchmarks can be derived from theoretical values, in particular technical and economic optimum values. The problem is that these values change with time and technological progress [14]. Most benchmarks found in the literature are bottom-up benchmarks derived from assessing a number of reference buildings. Ji et al. [21] assessed the environmental impacts of 23 elementary school buildings in South Korea. König and De Cristofaro [22] and König et al. [23] use “representative building types” for new residential buildings in Germany and derive benchmarks based on 86 generated building variants. The context is described in Lützkendorf et al. [24]. Wyss et al. [25] analysed 31 existing buildings in Switzerland for a feasibility study with regard to the 2000 Watt society. The study defines target values for residential, school and office buildings. Lavagna et. al. [26] use 24 statistically-based dwelling archetypes, representative of the EU housing stock in 2010 to quantify the average environmental impacts related to housing. They report average life cycle GHG emissions of 2.62 t CO2-e per capita per year. Simonen et. al. [27] define reference values for different types of buildings using a US database with more than 1000 published LCA results of buildings. However, the authors state the database only includes embodied GHG emissions of primary building components and the analysis methods used to generate the data were not aligned, making it difficult to compare buildings directly. Resch and Andresen [28] present an approach of generating benchmarks

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ACCEPTED MANUSCRIPT based on a database of published LCA studies of buildings in Norway. However, the database does not contain enough cases of buildings yet to derive representative values.

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Absolute values

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Absolute values are fixed values that can be limit, reference or target values. Ganassali et al. [29] call this type external benchmarks. SIA 2040 defines absolute values based on the floor area of a building for both embodied and operational impacts. The DGNB system provides absolute values for the embodied impacts. In addition, BREEAM system [30] uses this approach for evaluating the embodied impact.

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Relative values

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Relative values, or internal benchmarks as Ganassali et al. [29] call them, refer to a baseline. In the LEED V4 certification system, the baseline is a building modelled according to the standard ASHRAE 90.1-2010. In comparison with the baseline building’s environmental impacts, the propose-building must demonstrate a minimum reduction of 10% of three environmental impact indicators to obtain the score [29]. The DGNB benchmarks for the operational impact depend on the energy demand of the reference building according to the German energy performance regulation [31]. As the reference building and therefore the performance threshold changes with every change to the geometry, the benchmark for the operational impact is a relative value.

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Whole building versus building element-related benchmarks

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Most benchmarks found in the literature provide values for the whole building, but not for individual building elements, such as exterior walls, roof, windows, etc. For Switzerland, SNARC [32] defines characteristic values for the embodied energy per surface area of the main elements for different types of constructions. The values are calculated using statistic simulation based on data from 1998 [33]. The aim is to use these values to provide preliminary results in architectural competitions and early design stages. The assumed average service life for building elements is 30 years. SIA 2032 [34] provides characteristic values for embodied energy and embodied GHG emissions for different elements that can be used in preliminary design stages. Hoxha et al. [19] simulate 168 design options for one case study building and then derive average values and ranges of the variability for the different main elements such as walls, windows and the heating system. As such, the results can be seen as internal benchmarks for different elements for one specific building. Ruuska and Häkkinen [35] use a similar approach to vary design parameters for a multi-storey residential building and assess the relative importance of various building components including minimum and maximum values. Since the study is based on one fixed geometry, the results are only valid for this single building and provide an internal benchmark.

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1.3 Problems of current available benchmarks for application in the design process

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The reviewed literature provides various definitions and approaches to benchmarks. Fundamental work on the definition, application and interpretation of benchmarking and benchmarks was started in ISO TC 59 SC17 WG2 and will soon lead to the standard ISO 21678 Sustainability in buildings and civil engineering works -- Methodological principles for the development of benchmarks for sustainable building [36] currently under development. However, to support designers in the decision making process in early design stages, the current ongoing works on benchmarks are not yet sufficient.

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Most benchmarks described in the literature have been developed for sustainability certification of buildings, for example König and De Cristofaro [22], or to define a design target for the whole building, for example Russell-Smith et al. [20]. However, they only provide limited guidance during the design process. Target values for the embodied impact of the whole building can help to show if the building meets the desired environmental performance, but cannot indicate optimization potentials.

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ACCEPTED MANUSCRIPT The designer does not have a “feeling” of how much better the building could perform and how the environmental performance could be improved through the choice of different materials. Therefore, benchmarks on element level considering different material options are needed.

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The reference values for the specific building elements of SNARC [32] and SIA 2032 [37] have been developed to estimate the environmental performance of a building in early design stages, for example in architectural competitions. They consider a limited number of material options and types of construction. The values of SIA 2032 are not very detailed; for example, they only differentiate between load bearing and non-load bearing interior walls, but not the material. SNARC only provides values for embodied energy, not for embodied GHG emissions. The results are based on data from 1998 and the statistic simulation is not very clear.

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Another problem is that the existing target values for the whole building and benchmarks for specific building elements are not linked. The target values are typically provided per floor area, while the benchmarks for the elements are provided per surface area of element. As such, designers do not receive feedback if deciding for a type of construction or material will contribute to achieving a global environmental target.

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1.4 Goal for an alternative approach

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This paper focusses on the early design stages of residential buildings where architects and clients have most influence on the decision-making. Regarding the impact of the choice of type of construction and the kind of construction products on the environmental performance of the building, the focus lies on two questions commonly asked by architects and clients in addition to other design tasks:

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1. Is the building climate-friendly? 2. How can the environmental performance of the building be improved through the choice of materials and construction principles?

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To answer the first question, the term climate-friendly has to be specified for the context of this paper. Here, lifecycle-related GHG emissions are used as indicator to describe the objective of climate protection and protection of the eco-system. If the building meets a top-down benchmark for GHG emissions, it is considered as “climate-friendly”.

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To answer the second question, the construction type and material-related optimization potential is analysed. The embodied impact of each building element is compared to bottom-up benchmarks for this specific element under consideration of the type of building.

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Finally, the goal of this paper is to demonstrate the advantages of a dual benchmark approach combining top-down targets for the whole building with bottom-up targets for building elements in a consistent manner to provide answers to these two questions. The paper focuses on GHG emissions as a starting point to provide guidance for the choice of materials. Furthermore, the approach aims at allowing to connect design choices taken at building element level with global environmental targets.

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2 Method

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The proposed method is based on a top-down and a bottom-up approach. The top-down approach is derived from a global budget of GHG emissions per capita. The budget results from the capacity of the eco system in relation to global GHG emissions and the world’s population. The bottom-up approach is based on the embodied GHG emissions of typical building elements used for residential buildings in Switzerland and is expressed per surface area of building elements. The benchmarks derived from both approaches cannot be compared directly, but they can be related at building level.

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ACCEPTED MANUSCRIPT The combination of the top-down and bottom-up approach is called dual benchmark approach in this paper. The dual benchmark approach allows distinguishing between the different available options to reduce the embodied environmental impact of a building, namely the choice of material/type of construction and the design. Clearly, the choice of material is part of the design, however, in this context, both aspects are analysed separately. Design options refer to the shape and size of the building, but also the organization of floor plans or the window to wall ratio. Further aspects, such as the building’s adaptability to react to changes in the use phase as well as building components’ ability to be deconstructed and recycled are excluded here, but could be added in the future.

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2.1 Determination of top-down benchmarks

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To define benchmarks for residential buildings in Switzerland in this paper, the global 2-degree target serves as a basis. This target was described at the United Nations conference on climate change in Paris in 2015. The Paris Agreement aims for the long-term goal of keeping the increase in global average temperature to well below 2°C above pre-industrial levels; and to limit the increase to 1.5°C if possible, since this would significantly reduce risks and the negative impacts of climate change.

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The planetary boundaries framework [38,39] can be used to calculate the maximum concentration of GHG in the atmosphere to keep within the 2- or better 1.5-degree target. Based on the maximum concentration a so-called “carbon budget” can be calculated that can be released until the maximum concentration has been reached. For further description of the budget and the calculation methods for the 2-degree target see for example Meinshausen et al. [40], Messner et al. [41] and Millar et al. [42], Mengis et al., [43] for the 1.5-degree target. In all scenarios, the GHG emissions have to be zero after the budget has been used up. This so-called transition period is defined until the year 2050 in most scenarios. The global carbon budget can be transferred to a budget per capita, see for example Sandin et al. [44] and Grasso [45]. In this paper, the target of 1 t CO2-e per capita and year by the year 2050 is used. According to the Swiss 2000 Watt society [17], but also according to the German Environment Agency [46], this value is sufficient to achieve “climate neutrality”.

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For Switzerland, SIA 2040 was introduced to define a roadmap to a 2000 Watt society and a 1 t CO2-e society. To achieve this value, the Swiss yearly mean GHG emissions of 7.8 t CO2-e per capita of the year 2010 [47] have to be reduced by the factor 7.8. The goal defined by the 2000 Watt society is to achieve this target of 1 t CO2-e/(c⋅a) by the year 2100 [47]. SIA 2040 describes the roadmap towards an intermediate target for the year 2050, which is defined as 2 t CO2-e/(c⋅a).

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SIA 2040 splits the budget of 2 t CO2-e/(c⋅a) into different sectors, such as housing, mobility or private and public consumption. 36% of GHG emissions are attributed to housing. The GHG emissions consist of an embodied and an operational part. The embodied part relates to production of materials and components, replacement, de-construction and disposal of the building and its components. The reference study period for residential buildings is defined as 60 years in SIA 2032. The embodied GHG emissions are summed up and declared per each year of the reference study period. The operational part relates to the use phase including heating, hot water supply, ventilation, airconditioning, lighting, and user equipment.

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To define individual targets for both parts, SIA 2040 employs two steps. First, the current GHG emissions in Switzerland are multiplied with reduction factors to provide the target values [47]. Second, these target values are analysed for feasibility. The feasibility studies show that for new residential buildings the actual embodied GHG emissions can only be marginally reduced, while the current operational GHG emissions can be reduced to a large extend [48]. As such, the target values are adapted accordingly. Both fields are added up and the sum defines the threshold that has to be met.

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Global climate protection targets and carbon budget

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National targets for Switzerland

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ACCEPTED MANUSCRIPT As such, a high embodied impact can be compensated by a very low operational impact and vice versa.

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The target values as defined in SIA 2040 are employed in this paper, however, they are adapted to meet the global target of 1 t CO2-e/(c⋅a). Therefore, the targets based on 2 t CO2-e/(c⋅a) must be divided by 2.

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2.2 Determination of bottom-up benchmarks

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The proposed method to define the bottom-up benchmarks for embodied GHG emissions combines statistical data on the market share of materials used for construction in Switzerland [49] with the national building component catalogue containing LCA results [50]. The percentages of market share serve as weighting factor of the components in the catalogue. Next to the weighted mean values, benchmarks as target values based on the fifth percentile are calculated. The method consists of four steps (see Figure 1), which are explained in the following.

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Figure 1. Methodological steps to calculate the bottom-up benchmarks for individual building elements

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Structured list of building components

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The assessment of the embodied impact for buildings in Switzerland is regulated in the standard SIA 2032 [37], which is currently revised and updated. The standard defines which building elements have to be included in the assessment. It refers to the elements defined in the Swiss standard for building cost regulation SN 506 500 [51] “Baukostenplan Hochbau” (BKP-H), which is used for all residential buildings. A building can be decomposed into elements in many different ways. For the purpose of this paper, eleven building elements are defined. Each element consists of a number of components. The BKP-H classifies building components using an alphanumeric code. For example, C2.1B is the load-bearing part of the external wall above ground. The eleven building elements each consist of a combination of different components of the BKP-H structure, see Table 1. More details on the structuring can be found in [52]. A similar approach using the MasterFormat ® data structure was described by Tecchio et. al. [53].

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ACCEPTED MANUSCRIPT 292 Building element 1. Base slab

BKP-H Component C1 Base slab, foundation G2 Floor covering C2.1A Exterior wall under ground E1 Exterior wall finishing under ground C2.1B Exterior wall above ground E2 Exterior wall finishing above ground G3 Interior wall finishing E3 Window C2.2 Interior wall G3 Interior wall finishing G1 Partition wall G3 Interior wall finishing C3 Column C4.1 Ceiling G2 Floor covering G4 Interior ceiling/roof finishing C4.3 Balcony C4.4 Roof F1 Roof covering G4 Interior ceiling/roof finishing D1 Electric equipment D5.2 Heat generation D5.3 / D5.4 Heat distribution and delivery D7 Ventilation equipment D8 Water (sanitary) equipment

2. Exterior wall under ground 3. Exterior wall above ground

4. Window 5. Interior wall 6. Partition wall

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Table 1. Structure of building elements and components

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9. Balcony 10. Roof

11. Technical equipment

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The LCA data for building components are provided in the freely available Swiss national building component catalogue called “Bauteilkatalog” [50] that is structured according to BKP-H. The data are conform with SIA 2032 and based on the Swiss database for LCA results for construction products “Ökobilanzdaten im Baubereich” version 2012 [54]1. The building component catalogue provides data for the primary energy non-renewable (PE,nr). To describe the potential impact on climate change the indicator Global Warming Potential 100 (GWP) expressed in kg CO2-equivalent as defined by IPCC [55] is used. In additions, so-called “Ecopoints (Umweltbelastungspunkte)” - a single score indicator based on the method of ecological scarcity [56] are given. The building component catalogue provides the data per m2 of building component and per year taking the reference service life of the component declared in SIA 2032 into account. The values are provided including construction (life cycle modules A1-A3 according to EN 15978) and end-of-life (modules C3 and C4). When the values are multiplied by the reference study period of 60 years for residential buildings, the replacement (module B4) is implicitly considered.

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2.2.2

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The market share of different typical building materials used in Switzerland are provided in the yearly report Immo-Monitoring by Wüest & Partner [49]. The material typically used for construction depends on the building type. Therefore, the report differs between single-family, multi-family and

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Market share of building materials

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The building component catalogue is based on an old version of the Swiss building material database “Ökobilanzdaten im Baubereich” from 2012 [54]. This database for building materials uses Ecoinvent V2.2 with extensions as background data. It will be updated in the near future. As such, the current data is used as a ‘place holder’ until the new version is available and should then be updated.

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different kinds of non-residential buildings. In this paper, the focus lies on residential multi-family buildings, but the method can be employed for the other types as well.

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To use the percentages of market share, they have to be matched with the BKP-H component structure. The components of the catalogue are grouped according to the categories of the market share data. Within one category, the components are not weighted, but a uniform distribution is assumed.

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Some components with a very low market share are not available in the component catalogue. For example, lightweight constructions e.g. steel frame for the structure of residential buildings with a share of 1.3%. Therefore, the percentages of market share are divided by the sum of the available components. As such, it can be guaranteed that the sum of the weighting factors wi equals one. The weighted mean value x̅ of environmental impact for each component can be calculated using Equation 1.

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̅ =

Weighted mean values per element

To calculate the weighted mean value for each of the eleven building elements, the weighted mean values of the BKP-H components are added according to Table 1.

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2.2.4

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To calculate the benchmarks as target values all components in the catalogue are combined to building elements according to Table 1. Technically impossible combinations such as prefabricated concrete facade panels on a timber frame construction are not included, however, it is not checked whether a combination is commonly used in practice. In the case of the external wall aboveground, a combination of 10 structural components (C2.1B) with 15 kinds of exterior wall finishing (E2) and 5 kinds of interior wall finishing (G3) results in 404 possible solutions when excluding the obviously technically impossible combinations. The default insulation thicknesses provided in the building component cause the final U-value of the wall to be around 0.2 W/(m2·K). Therefore, they provide about the same thermal function and are comparable. For the windows, the building component catalogue provides double and triple glazing windows with PVC, timber or aluminium frames. The Uvalue varies between 0.9 and 1.3. The thicknesses of the load-bearing layers vary slightly, for example from 20 cm to 25 cm for concrete. These variations are plausible for residential buildings and were not considered in detail, as no structural dimensioning was carried out. Furthermore, no special foundation is considered, but it is assumed that the base slab is sufficient to support the building.

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According to Heijungs & Frischknecht [57] four different kinds of distribution can be used to describe uncertainty in LCA: the uniform distribution, the triangular distribution, the normal distribution, and the lognormal distribution. In this paper, the focus is on the variability within the material choices rather than the uncertainty. Nevertheless, the distributions can be used. Here, a lognormal distribution is assumed to exclude negative values.

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To calculate the probability density function f∆ for the lognormal distribution using the weighted components, first the weighted variance is calculated according to Equation 2 where n is the number of possible solutions.

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Target values for GWP per m² of building element

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− ̅)

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Then the shape and scale parameters µ and σ are calculated according to Equations 3 and 4. Finally, f∆ is calculated using Equation 5. 9

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σ = ln ∆(

)=

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+ 1 (4) 1

! √2#

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µ = ln

Furthermore, the target value per m² of element is set to the 0.05 quantile, meaning that the chosen solution is within the best 5% of available solutions. The benchmark x for the 0.05 quantile can be calculated according to Equation 6. The z-score for the 0.05 quantile is 1.645.

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The weighted mean and the 0.05 quantile as target value are calculated for each building element as described above. In addition, the minimum and maximum values are calculated to indicate the total range of possibilities.

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3 Determination of benchmarks

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3.1 Top-down targets for residential buildings

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According to the feasibility study for SIA 2040, 27% of GHG emissions are attributed to the embodied part and 9 % to the operational part. Adapting the targets of SIA 2040 to the global target of 1 t CO2e/(c⋅a) for this paper provides the targets for housing per capita shown in Table 2.

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Table 2. Targets for GWP per capita and year for housing in Switzerland based on the global target of 1 t CO2-e/(c⋅a)

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= $ µ % σ∙/ (6)

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GWP [kg CO2-e/(m ·a)] 270 90 360

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Embodied (including construction, replacement and demolition) Operation Total

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To relate the global target to a target for the environmental impact of residential buildings, a benchmark per resident and per year has been defined here. The goal of the top-down benchmark is to define a GWP value for the whole building that serves as a target in the design process. To define this target, the number of residents can be multiplied with the values of Table 2. For example, the target for a single-family house for four residents equals 1.44 t CO2-e/a. The resulting target values highly depend on the number of residents. However, the number of residents might be unknown in the design process, for example when designing a large apartment building. Furthermore, the number of residents might change over the building’s life cycle introducing further uncertainty. This requires using an assumption for the number of residents based either on the number and type of rooms in each apartment or an assumption based on the average floor area per resident.

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SIA 2040 defines targets for GWP based on a fixed value of 60 m2 energy reference area (AE) per capita. AE is defined as the gross floor area within the thermal building envelope [58] and is also used as reference unit for the calculation of the operational energy demand in Switzerland. According to 10

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Pfäffli et al. [59] a factor of 1.33 can be used to convert to useful floor area. This value matches the 45 m2 of average living space reported by the Swiss Federal Office for Statistic [60] for the year 2016.

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To show the relation between targets per capita and per floor area different occupation scenarios are shown in Table 3. Here, the importance and potential for sufficiency strategies to reduce the floor area per resident become apparent, see also Pfäffli et al. [59].

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Table 3. Relation between energy reference area (AE) and living space per resident and the target values for the budget per capita and year based on the global target of 1 t CO2-e/(c⋅a)

45 60 4.5 1.5 6.0

37.5 50 5.4 1.8 7.2

30 40 6.8 2.3 9.0

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3.2 Bottom-up benchmarks for building elements

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The results for benchmarks for the 11 building elements are shows in Table 4. Next to the target value (0.05 quantile) the weighted mean, minimum and maximum values are given.

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Sample Reference GWP [kg CO2-e/(m2·a)] Min. W. mean Max. Target (0.05) size unit 1. Base slab 80 m2element 1.32 2.23 2.82 1.87 2 2. Exterior walls underground 3 m element 3.52 3.72 3.87 3.35 3. Exterior walls aboveground 404 m2element 0.82 2.11 3.82 1.37 4. Windows 16 m2element 1.49 3.16 5.57 1.85 5. Interior walls 35 m2element 0.59 1.28 4.46 0.82 2 6. Partition walls 30 m element 0.58 1.05 3.97 0.83 7. Columns 7 piece 1.29 6.04 11.76 1.91 8. Ceilings 1260 m2element 0.66 2.24 4.69 1.37 9. Balconies 4 m2element 1.2 1.48 1.76 1.13 2 10. Roof 273 m element 0.79 4.05 7.71 2.32 11. Technical equipment* 29 m2AE 1.18 3.36 1.18* * Due to a small number of solutions in the building component catalogue, no benchmark is calculated, but the minimum is used. The target value is the sum of minimum values for electric equipment, heat generation, heat distribution and delivery, ventilation equipment and water (sanitary) equipment of residential buildings.

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The results are diagrammed in Figure 2 to visualize the variability. The box plots indicate the 5th percentile as lower and the 95th percentile as upper benchmark. The whiskers indicate the minimum and maximum value. The middle line describes the weighted mean value.

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The values for columns are provided per piece in the component catalogue with an assumed length of 3 m. Therefore, the results cannot directly be compared and are shown in a separate graph.

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b)

Figure 2. a) Variability of the elements per m2 of element, b) Variability for the columns per piece

Differences in the variability can be seen. All options for exterior wall underground and balcony in the building component catalogue consist of concrete, for example. As such, the variability is low for these elements. Especially, windows, roofs and ceilings show a high variability.

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The interior and partition walls have a low weighted mean value and upper 95th percentile, however, both show very high maximum values. This is due to a solution for interior insulation based on XPS, which is very rarely employed, but has a very high value for GWP.

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For the exterior wall underground and the balcony, the benchmarks are lower than the minimum and higher than the maximum value, which clearly does not make sense. The building component catalogue only provides a very small number of options for both elements. In these cases, the method does not seem to work well. As such, the building component catalogue should be extended in the future.

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The number of solutions for technical building equipment for residential buildings in the building component catalogue is very low. Therefore, no weighting was employed and no distribution could be assumed. To provide a target value nevertheless, the sum of minimum values for electric equipment, heat generation, heat distribution and delivery, ventilation equipment and water (sanitary) equipment of residential buildings is used.

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4 Proposed application in the design process

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The proposed workflow of using the dual benchmark approach in the design process is visualized in Figure 3. The workflow proposes to first calculate the environmental impact of the building and check whether the top-down benchmark can be met. If the benchmark cannot be met, the impact of the individual building elements is calculated and compared to the bottom-up benchmarks to indicate the material-related optimization potential. Of course, this step should also be carried out to analyse the improvement potential even if the top-down benchmark can be met by the initial design. If the selected material/type of construction for an element is not within the top 5%, it is recommended to modify the material and redo the analysis. There are exceptional cases where a specific material or type of construction cannot be changed due to other characteristics needed, e.g. fire or earthquake resistance. If the chosen solution is within the top 5%, the improvement potential is considered as small. In this case, it is assumed that the most efficient way to reduce the embodied impact is through design changes. For example, the compactness of the building can be increased, or the floor plans can be

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modified to decrease the built area. The change of the design has many consequences on other architectural and functional aspects, for example daylight availability and energy demand for lighting. These have to be considered, but are not within the scope of this paper. The aim of dividing between specific material-related and overall design-related options is to provide guidance for environmental performance optimization of the building and its components. The proposed workflow is exemplified by means of a case study that can be found in the supplementary information (S.I.).

Figure 3. Flow chart of applying the dual benchmark approach in the design process

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The application to a case study in this paper (see S.I.) is a first step to validate the dual benchmark approach. The results for the actual embodied GWP for the whole building are lower than the bottomup benchmarks based on the 0.05 quantile. This proves that the statistically derived benchmarks can be reached in practice. However, in this case study, the top-down benchmarks can only be achieved using the components with minimum values.

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Furthermore, the results highlight the importance of the embodied GHG emissions. Depending on the building, the environmental impact that results from the use phase can be a major part of the overall life cycle impact. However, for this specific case study building, the operational impact is only about half of the embodied impact. As such, the embodied GHG emissions are responsible for two thirds of the GHG emissions during the life cycle of 60 years. This confirms the findings of recent publications stating that the embodied impact of very energy efficient residential buildings often exceeds the impact from the use phase [61].

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Buildings built today will still be around in the year 2050 – the end of the transition period towards 1 t CO2-e/(c⋅a). As such, new buildings have to fulfil the targets already today. This is especially true

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ACCEPTED MANUSCRIPT regarding embodied GHG emissions, because most components are manufactured today and will remain in the building for a long time, in particular structural parts. The yearly operational impact could possibly be lowered in the future, for example by lowering the GHG emissions of the electricity mix, if an electricity-powered heating system is used. Furthermore, the technical equipment usually has shorter replacement cycles allowing to install more efficient systems in the future.

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Clearly, the results presented here are only a first step for the development of design-guiding benchmarks. The current limitations and further developments are discussed in the following.

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5.1 Limitations of top-down benchmarks

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The global community aims to limit global warming to maximum 2 degrees. Many scientists agree that a limitation to 1.5 degrees or below should be aimed for to mitigate undesired consequences of climate change. However, translating this global declaration of intention into clear manageable targets is difficult. So far, no consistent definition of a stabilized climate has been agreed on. The different use of terms like climate neutrality, GHG neutrality or carbon neutrality without additional definitions does not improve the situation. One approach is the definition of a budget per capita considering the capacity of the global eco system and the growing global population. Here, the equal per capita target of 1 t per capita and year for the year 2050 was used. This target is strongly influenced by the assumed development of the global population and the state of the art of climate models.

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To relate the global target to a target for the environmental impact of residential buildings, a benchmark per resident and per year has been defined here. To facilitate the application of the benchmarks in the design process when the number of residents is unknown a target per floor area for different scenarios is provided here. Table 3 clearly shows that it is easier to achieve the targets for small apartments, respectively less floor area per resident. A future potential division of responsibility becomes apparent: project developers and designers can provide efficient buildings while buyers or renters of the apartments should ask for an appropriate size and follow a sufficiency approach.

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Benchmarks defined by SIA 2040 or certification systems like Minergie Eco or DGNB and all benchmarks found in the literature employ a benchmark based on the floor area of the building. As this measure does not take into account the floor area per resident, aspects of sufficiency are not accounted for. As such, a target based on floor area is only suitable for optimization towards efficiency. Furthermore, the relative impact per floor area of bigger buildings is usually lower than that of small buildings. This means that targets based on floor area tend to favour big buildings and therefore could push designers to bigger buildings [62].

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For all target values for embodied impacts per year, the reference study period is of large importance. A reference study period of 60 years as defined by SIA 2032 is not necessarily in line with an expected service life of a residential building. The average service life of residential buildings in Switzerland is between 75 and 100 years [63], for example. Furthermore, the recycling potential of components can influence the embodied impact and should be integrated in the future.

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The results show that the method works well for components with more than ten datasets in the components catalogue, for example exterior walls, ceilings and roofs. For specific components with few (less than five) datasets, for example balconies, the method does not produce meaningful results. In these cases, the database has to be improved. Furthermore, the current available data on technical equipment is very limited. In the future, the building component catalogue could easily be extended.

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The data in the building component catalogue are from 2012. In the meantime, new solutions for building components and construction products might have been developed and the GHG emissions

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As the method depends on the building component catalogue, it is limited in terms of indicating the environmental potential of innovative constructive solutions that are not part of a catalogue of standard solutions. The catalogue employed covers the solutions available on the market, which means the majority of constructions. The proposed method is therefore useful for mass construction, but not for the few ground-breaking solutions.

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Finally, a building is more than a sum of its building components. As such, there are interdependencies between different components, for example load-bearing exterior or interior walls. Next to the embodied impact, the choice of materials and construction types influence many other building performance criteria. The presented approach is therefore a rough estimation to provide guidance based on the currently available data.

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Here, the method was applied for new residential buildings. The same method can be adapted to nonresidential buildings as well as retrofit projects. Furthermore, the benchmarks should be implemented into LCA tools applied during design to provide direct feedback on the optimization potential to decision makers.

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In the future, the method can be transferred to other countries to derive national benchmarks for material-related environmental impacts as long as a building component catalogue and market share data are available. In Belgium a similar building component catalogue is available [64], for example. Clearly, the database has to provide enough datasets to allow the application. The direct use of the values for benchmarks provided in this paper in other countries is difficult. First, the typical construction practice varies. But even, if exactly the same building as described in the case study would be built in North America, for example, the results would be different. The material would be manufactured in local production facilities with the local energy mix resulting in different values for embodied impact. In addition, the results for the operational impact would be different as the GWP factors for the energy carriers differ. The benchmarks have been calculated using the Swiss methodology and need to be adapted to the North American context. As such, the method can be generalized and employed in different countries, but the resulting regional or national benchmarks cannot.

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6 Summary and Conclusion

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As LCA is more commonly applied to assess the environmental performance of buildings different actors have a need for LCA-based benchmarks. Investors, building owners and public funding institutions need them to define environmental performance targets and architects need them for design guidance. This paper showed that the question is not whether top-down or bottom-up benchmarks should be used, but how they can be combined to answer two questions in the design process: 1) Is the building climate-friendly? and 2) How can the environmental performance of the building be improved through the choice of materials and construction principles? Therefore, a dual benchmark approach was developed. This novel approach combines a top-down target for the whole building with bottom-up targets for the building elements that have not been linked before. The topdown benchmark is based on the global target of limiting GHG emissions to 1 t CO2-e per capita and year. The bottom-up benchmarks are statistically derived from typical building components for new residential buildings in Switzerland and the market share of different building materials following a best in class approach. A method for using the dual benchmark approach in the design process is proposed. Differentiating between material and design-related options provides guidance on how to optimize the environmental performance of the building and its components efficiently. Using the dual

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benchmark approach in a case study of a multi-family house shows that the method is applicable. As such, the proposed approach can facilitate using LCA as a design-supporting method in design practice and promote the environmental performance optimization of buildings. The current limitations also show that further discussions are needed to define targets for a lifecycle-based carbon footprint of individual buildings. The proposed approach is one contribution to this discussion.

References

546 [1]

UNEP SBCI, Building Design and Construction : Forging Resource Efficiency and Sustainable Development, 2012. http://www.unep.org/sbci/pdfs/UNEP_SBCI_PositionPaperJune2012.pdf.

549 550 551

[2]

M. Zimmermann, H.-J. Althaus, A. Haas, Benchmarks für die Beurteilung von Umweltverträglichkeit von Hochbauten–Beitrag zur Entwicklung eines Standards für nachhaltiges Bauen., Dübendorf, 2005.

552 553

[3]

B. Wittstock, S. Albrecht, C. Makishi Colodel, J.P. Lindner, G. Hauser, K. Sedlbauer, Gebäude aus Lebenszyklusperspektive − Ökobilanzen im Bauwesen, Bauphysik. 31 (2009).

554 555 556

[4]

E. Meex, A. Hollberg, E. Knapen, L. Hildebrand, G. Verbeeck, Requirements for applying LCA-based environmental impact assessment tools in the early stages of building design, Build. Environ. 133 (2018). doi:10.1016/j.buildenv.2018.02.016.

557 558

[5]

N. Kohler, T. Lützkendorf, Integrated life-cycle analysis, Build. Res. Inf. 30 (2002) 338–348. doi:10.1080/09613210110117584.

559 560

[6]

U. Bogenstätter, Prediction and optimization of life-cycle costs in early design, Build. Res. Inf. 28 (2000) 376–386. doi:10.1080/096132100418528.

561

[7]

KT Innovations, Tally, (2014). http://www.choosetally.com/ (accessed October 10, 2017).

562

[8]

Bionova, optimi360, (2015). http://www.360optimi.com/ (accessed October 10, 2017).

563 564

[9]

Athena, Athena Impact Estimator, (2015). http://calculatelca.com/software/impact-estimator/ (accessed August 8, 2015).

565 566

[10]

CAALA GmbH, Computer-Aided Architectural Life cycle Assessment (CAALA), (2018). www.caala.de (accessed July 7, 2018).

567 568

[11]

CEN, EN 15643-1:2010 Sustainability of construction works - Sustainability assessment of buildings - General framework, (2010).

569 570 571

[12]

H. Hakaste, Roadmap for integrating carbon footprint of construction materials into building regulation in Finland, in: GABC Roadmap Public Policies Meet. Paris, Ministry of the Environment, 2016.

572

[13]

573 574 575 576

[14]

577 578 579

[15]

T. Lützkendorf, N. Kohler, H. König, Integrated Life Cycle Assessment: Benchmarks and Uncertainty, in: Int. Symp. Life Cycle Assess. Constr., Nantes, 2012. http://lcaconstruction2012.ifsttar.fr/downloads/s1/12108_Kohler.pdf.

580 581

[16]

A. Braune, B. Wittstock, Measuring environmental sustainability: The use of LCA based building performance indicators, in: Life Cycle Manag., Berlin, 2011.

582 583

[17]

E. Jochem, G. Andersson, D. Favrat, H. Gutscher, K. Hungerbühler, P.R. von Rohr, D. Spreng, A. Wokaun, M. Zimmermann, A White Book for R&D of energy-efficient technologies,

AC C

EP

TE D

M AN U

SC

RI PT

547 548

SIA, SIA 2040: SIA-Effizienzpfad Energie, (2017).

T. Häkkinen, C. Antuña, T. Mäkeläinen, T. Lützkendorf, M. Balouktsi, A. Immendörfer, S. Nibel, B. Bosdevigie, A. Lebert, B. Fies, P.H. Iñarra, A. Lupíšek, P. Hajek, S. Supper, E. Alsema, L. Delem, J. Van Dessel, Sustainability and performance assessment and benchmarking of a building – Final report, VTT, 2012. http://cic.vtt.fi/superbuildings/.

16

ACCEPTED MANUSCRIPT Novalantis, Zurich, 2004. [18]

M. Zimmermann, H.-J. Althaus, A. Haas, Benchmarks for sustainable construction, Energy Build. 37 (2005) 1147–1157. doi:10.1016/j.enbuild.2005.06.017.

587 588 589

[19]

E. Hoxha, T. Jusselme, A. Brambilla, S. Cozza, M. Andersen, E. Rey, Impact Targets as Guidelines towards Low Carbon Buildings : A preliminary concept, in: 36th Int. Conf. Passiv. Low Energy Archit., Los Angeles, 2016.

590 591 592 593

[20]

S. V. Russell-Smith, M.D. Lepech, R. Fruchter, Y.B. Meyer, Sustainable target value design: Integrating life cycle assessment and target value design to improve building energy and environmental performance, J. Clean. Prod. 88 (2015) 43–51. doi:10.1016/j.jclepro.2014.03.025.

594 595 596

[21]

C. Ji, T. Hong, J. Jeong, J. Kim, M. Lee, K. Jeong, Establishing environmental benchmarks to determine the environmental performance of elementary school buildings using LCA, Energy Build. 127 (2016) 818–829. doi:10.1016/j.enbuild.2016.06.042.

597 598

[22]

H. König, M.L. De Cristofaro, Benchmarks for life cycle costs and life cycle assessment of residential buildings, Build. Res. Inf. 40 (2012) 558–580. doi:10.1080/09613218.2012.702017.

599 600

[23]

H. König, L. De Cristofaro, G. Löhnert, Entwicklung von Bewertungsmaßstäben für das Bewertungssystem Nachhaltiger Wohnungsbau, 2010.

601 602

[24]

T. Lützkendorf, N. Kohler, H. König, M. Balouktsi, Building Sustainability Assessment – from Calculation to Valuation, in: 1st Int. Conf. Build. Sustain. Assess., Porto, Portugal, 2012.

603 604

[25]

F. Wyss, R. Frischknecht, K. Pfäffli, V. John, Zielwert Gesamtumweltbelastung Gebäude Machbarkeitsstudie, 2014.

605 606 607 608

[26]

M. Lavagna, C. Baldassarri, A. Campioli, S. Giorgi, A.D. Valle, V. Castellani, S. Sala, Benchmarks for environmental impact of housing in Europe: Definition of archetypes and LCA of the residential building stock, Build. Environ. 145 (2018) 260–275. doi:10.1016/j.buildenv.2018.09.008.

609 610

[27]

K. Simonen, B.X. Rodriguez, C. De Wolf, Benchmarking the Embodied Carbon of Buildings, Technol. + Des. 1 (2017) 208–218. doi:10.1080/24751448.2017.1354623.

611 612

[28]

E. Resch, I. Andresen, A Database Tool for Systematic Analysis of Embodied Emissions in Buildings and Neighborhoods, Buildings. 8 (2018) 106. doi:10.3390/buildings8080106.

613 614

[29]

S. Ganassali, M. Lavagna, A. Campioli, LCA Benchmarks in Building’s Environmental Certification Systems, in: IAHS WORLD Congr., 2016.

615

[30]

bre, BREEAM, (2015). http://www.breeam.com/ (accessed November 11, 2015).

616 617 618

[31]

619 620

[32]

621

[33]

U. Kasser, Gebäude gesamtenergetisch beurteilt, Schweizer Ing. Und Archit. 116 (1998).

622

[34]

SIA, Graue Energie von Gebäuden Korrigenda C1 zu SIA 2032: 2010, 2010.

623 624

[35]

A.P. Ruuska, T.M. Häkkinen, The significance of various factors for GHG emissions of buildings, Int. J. Sustain. Eng. 8 (2015) 317–330. doi:10.1080/19397038.2014.934931.

625 626 627

[36]

ISO, ISO 21678 [Under development] Sustainability in buildings and civil engineering works - Methodological principles for the development of benchmarks for sustainable buildings, 2018. https://www.iso.org/standard/71344.html?browse=tc.

EP

TE D

M AN U

SC

RI PT

585 586

AC C

584

Bundesregierung, EnEV 2014: Energieeinsparverordnung - Nichtamtliche Lesefassung zur Zweiten Verordnung zur Änderung der Energieeinsparverordnung vom 18. November 2013, Bundesanzeigerverlag, Germany, 2013.

SIA, SIA D 0200 SNARC - Systematik zur Beurteilung der Nachhaltigkeit von Architekturprojekten für den Bereich Umwelt, 2004.

17

ACCEPTED MANUSCRIPT [37]

SIA, SIA 2032 Graue Energie von Gebäuden, (2010).

629 630 631 632 633 634

[38]

J. Rockström, W. Steffen, K. Noone, Å. Persson, F.S.I. Chapin, E. Lambin, T.M. Lenton, M. Scheffer, C. Folke, H.J. Schellnhuber, B. Nykvist, C.A. de Wit, T. Hughes, S. van der Leeuw, H. Rodhe, S. Sörlin, P.K. Snyder, R. Costanza, U. Svedin, M. Falkenmark, L. Karlberg, R.W. Corell, V.J. Fabry, J. Hansen, B. Walker, D. Liverman, K. Richardson, P. Crutzen, J. Foley, Planetary Boundaries: Exploring the Safe Operating Space for Humanity, Ecol. Soc. 14 (2009) art32. doi:10.5751/ES-03180-140232.

635 636 637 638

[39]

W. Steffen, K. Richardson, J. Rockström, S.E. Cornell, I. Fetzer, E.M. Bennett, R. Biggs, S.R. Carpenter, W. de Vries, C.A. de Wit, C. Folke, D. Gerten, J. Heinke, G.M. Mace, L.M. Persson, V. Ramanathan, B. Reyers, S. Sörlin, Planetary boundaries: Guiding human development on a changing planet, Science (80-. ). 347 (2015). doi:10.1126/ science.1259855.

639 640 641

[40]

M. Meinshausen, N. Meinshausen, W. Hare, S.C.B. Raper, K. Frieler, R. Knutti, D.J. Frame, M.R. Allen, Greenhouse-gas emission targets for limiting global warming to 2°C, Nature. 458 (2009) 1158–1162. doi:10.1038/nature08017.

642 643 644

[41]

D. Messner, J. Schellnhuber, S. Rahmstorf, D. Klingenfeld, The budget approach: A framework for a global transformation toward a low-carbon economy, J. Renew. Sustain. Energy. 2 (2010) 1–14. doi:10.1063/1.3318695.

645 646 647

[42]

R.J. Millar, J.S. Fuglestvedt, P. Friedlingstein, J. Rogelj, M.J. Grubb, H.D. Matthews, R.B. Skeie, P.M. Forster, D.J. Frame, M.R. Allen, Emission budgets and pathways consistent with limiting warming to 1.5 °C, Nat. Geosci. 10 (2017) 741–747. doi:10.1038/ngeo3031.

648 649 650

[43]

N. Mengis, A. Partanen, J. Jalbert, H.D. Matthews, 1.5 ° C carbon budget dependent on carbon cycle uncertainty and future non-CO2 forcing, Nat. Sci. Reports. (2018). doi:10.1038/s41598018-24241-1.

651 652 653

[44]

G. Sandin, G.M. Peters, M. Svanström, Using the planetary boundaries framework for setting impact-reduction targets in LCA contexts, Int. J. Life Cycle Assess. 20 (2015) 1684–1700. doi:10.1007/s11367-015-0984-6.

654 655

[45]

M. Grasso, Sharing the Emission Budget, Polit. Stud. 60 (2012) 668–686. doi:10.1111/j.14679248.2011.00929.x.

656 657 658 659 660 661 662

[46]

R. Benndorf, M. Bernicke, A. Bertram, W. Butz, F. Dettling, J. Drotleff, C. Elsner, E. Fee, C. Gabler, C. Galander, Y. Hargita, R. Herbener, T. Hermann, F. Jäger, J. Kanthak, H. Kessler, Y. Koch, D. Kuntze, M. Lambrecht, C. Lehmann, H. Lehmann, S. Leuthold, I. Lütkehus, K. Martens, F. Müller, K. Müschen, D. Nissler, S. Plickert, K. Purr, A. Reichart, J. Reichel, H. Salecker, J. Schuberth, D. Schulz, U. Strenge, M. Sieck, B. Westermann, K. Werner, C. Winde, D. Wunderlich, B. Zietlow, Treibhausgasneutrales Deutschland im Jahr 2050, Umweltbundesamt. (2013). www.umweltbundesamt.de%5Cnwww.umweltbundesamt.de.

663 664

[47]

665 666 667 668

[48]

669

[49]

Wüest & Partner AG, Immo-Monitoring 2016 | 1. Herbstausgabe, Zürich, 2016.

670 671

[50]

Holliger Consult, Bauteilkatalog, (2002). http://www.bauteilkatalog.ch/ch/de/Bauteilkatalog.asp (accessed June 6, 2018).

672

[51]

SIA, SN 506 500: Baukostenplan, (2001).

673

[52]

C. Cavalliere, G. Habert, G.R. Dell’Osso, A. Hollberg, Continuous BIM-based assessment of

AC C

EP

TE D

M AN U

SC

RI PT

628

SIA, SIA D 0258: SIA-Effizienzpfad Energie - Ergänzungen und Fallbeispiele zum Merkblatt SIA 2040:2017, (2018). K. Pfäffli, Grundlagenberichte zu SIA 2040 - Bestimmung der Ziel- und Richtwerte Top-down und Bottom-up, 2017. https://www.energytools.ch/index.php/de/downloads/grundlagenberichte/download/5grundlagenberichte/51-grundlagenberichte-sia-2040-de.

18

ACCEPTED MANUSCRIPT 674 675

embodied environmental impacts throughout the design process, J. Clean. Prod. 211 (2019) 941–952. doi:10.1016/j.jclepro.2018.11.247. [53]

P. Tecchio, J. Gregory, R. Ghattas, R. Kirchain, Structured Under-Specification of Life Cycle Impact Assessment Data for Building Assemblies, J. Ind. Ecol. 0 (2018) 1–16. doi:10.1111/jiec.12746.

679 680

[54]

KBOB, Ökobilanzen im Baubereich 2009/1, (2012). http://www.ecobau.ch/resources/uploads/KBOB_EMPFEHLUNG_2009_1_Juli_2012.pdf.

681

[55]

IPCC, IPCC Fourth Assessment Report: Climate Change 2007, 2007.

682 683

[56]

BAFU, Methode der ökologischen Knappheit – Ökofaktoren 2006, Schweizer Bundesamt für Umwelt BAFU, Bern, 2009.

684 685 686 687

[57]

R. Heijungs, R. Frischknecht, Representing Statistical Distributions for Uncertain Parameters in LCA. Relationships between mathematical forms, their representation in EcoSpold, and their representation in CMLCA, Int. J. Life Cycle Assess. 10 (2005) 248–254. doi:10.1065/lca2004.09.177.

688

[58]

SIA, SIA 380 - Grundlagen für energetische Berechnungen von Gebäuden, 2015.

689

[59]

K. Pfäffli, J. Nipkow, S. Schneider, M. Hänger, Suffizienzpfad Energie, Zürich, 2012.

690 691 692 693

[60]

BFS, Durchschnittliche Wohnfläche pro Bewohner, (2016). https://www.bfs.admin.ch/bfs/de/home/statistiken/bauwohnungswesen/wohnungen/wohnverhaeltnisse/flaechenverbrauch.html (accessed July 7, 2018).

694 695 696

[61]

R. Azari, N. Abbasabadi, Embodied energy of buildings: A review of data, methods, challenges, and research trends, Energy Build. 168 (2018) 225–235. doi:10.1016/j.enbuild.2018.03.003.

697 698 699

[62]

A. Stephan, R.H. Crawford, The relationship between house size and life cycle energy demand: Implications for energy efficiency regulations for buildings, Energy. 116 (2016) e221. doi:10.1016/j.energy.2016.10.038.

700 701 702

[63]

C. Buchschacher, Nachhaltige Sanierung von Wohnimmobilien : Lohnt es sich ?, 2015. https://www.marti-gesamtleistungen.ch/Documents/Fachbericht Nachhaltige Sanierung von Wohnimmobilien.pdf.

703 704 705

[64]

K. Allacker, W. Debacker, L. Delem, L. De Nocker, F. De Troyer, A. Janssen, K. Peeters, R. Servaes, C. Spirinckx, J. Van Dessel, Environmental Profile of Building elements, Towards an integrated environmental assessment of the use of materials in buildings, 2013.

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ACCEPTED MANUSCRIPT Highlights •

Novel method of combining top-down and bottom up benchmarks for greenhouse gas emissions during the life cycle of buildings to provide design decision support

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Determination of top-down targets based on the 2 degree goal and a global carbon budget per capita

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Determination of bottom-up targets for building elements based on a statistical approach using market share

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Application of the method for analysis of the environmental optimization potential in the design process

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data of building materials in Switzerland