The embodied CO2e of sustainable energy technologies used in buildings: A review article

Energy & Buildings 181 (2018) 50–61

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The embodied CO2 e of sustainable energy technologies used in buildings: A review article Stephen Finnegan a,∗, Craig Jones b, Steve Sharples a a b

University of Liverpool, School of Architecture, Liverpool, UK Circular Ecology, UK

a r t i c l e

i n f o

Article history: Received 9 July 2017 Revised 14 June 2018 Accepted 27 September 2018 Available online 17 October 2018 Keywords: Embodied carbon CO2 e Sustainable energy technology Solar PV Solar thermal Air source heat pump (ASHP) Ground source heat pump (GSHP) LED lighting Life Cycle Assessment (LCA)

a b s t r a c t Sustainable energy technologies are frequently considered for use with buildings in order to reduce their environmental impact. However, each technology will come with its own associated embodied carbon, which might potentially represent a significant proportion of a building’s total embodied carbon impact. There is a need for further studies on the embodied carbon or CO2 equivalent (CO2 e) impact of sustainable energy technologies and it is important to understand how they contribute to the total CO2 e budget of a building. Life Cycle Assessment (LCA) is used for the CO2 e calculations and this paper has reviewed a significant number of existing studies. The results show that LCA methodologies can and do present information which has a significant degree of inaccuracy. Furthermore, the impact of some technologies can significantly increase the embodied CO2 e impact of modern low to zero energy buildings. Considering the whole life CO2 e impact of each aspect of a building is crucial for the successful creation of a truly low to zero carbon building. Many current studies omit the CO2 e impact from sustainable energy technologies. This leads to results which are under representative and misleading. © 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)

1. Introduction A sustainable energy technology can be defined as a piece of equipment to power, ventilate, heat and/or cool a building that relies on resources that have no long term adverse environmental impact. The definition of environmental impact is important and generally refers to the whole life impact of the technology, which includes the operational (in use) and so-called embodied impact. Studies [1–4] have detailed the methodology and approach to this type of assessment. The embodied impact refers to the energy and emissions (such as CO2 ) released to create, manufacture, transport, use and dispose of each technology. Studies by, for example Fthenakis and Kim [5], Ito et al. [6], Jayathissaa et al. [7], Lin Lu and Yang [8] and Nawaz and Tiwari [9] have focused on the embodied impact of solar photovoltaic (SPV) panels, whilst USDoE [10] and Tähkämö et al. [11] have assessed Light Emitting Diode (LED) lighting. In this paper, all technologies are considered based on their embodied carbon dioxide equivalent (CO2 e) impact. The equivalent includes the other significant greenhouse gases that contribute to global warming potential.

∗

Measuring the CO2 e impact of any product can be achieved using the universally established technique of Life Cycle Assessment (LCA). Each LCA will contain a database, of which there are numerous types, see Section 2.2. Most current databases do not include information on sustainable energy technologies, although the processes to create this information are already in place. For example, the Inventory of Carbon and Energy (ICE) database [12] reports on solar photovoltaics [13] while the Building Research Establishment (BRE) Green Guide [14] does not consider any technologies. As these technologies are becoming increasingly popular [15], it is essential for decision makers to appreciate the true holistic CO2 e impact. In this review of the embodied CO2 e of sustainable energy technologies, the paper starts by selecting the technologies to investigate. This is followed by a review of the methods within which the environmental impacts are measured using LCA. A meta-analysis of existing LCA studies follows and from that analysis the embodied CO2 e data is presented. A consideration of the significance of the results concludes the review.

Corresponding author. E-mail address: s.fi[email protected] (S. Finnegan).

https://doi.org/10.1016/j.enbuild.2018.09.037 0378-7788/© 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)

S. Finnegan et al. / Energy & Buildings 181 (2018) 50–61 Table 1 Common sustainable technologies [18]. Activities

Sustainable Technologies

Heating, Ventilation and Air Conditioning

Biomass Boiler

Power

Lighting

Ground and Air Source Heat Pumps (GSHP/ASHP) Solar Thermal (ST) Mechanical Ventilation and Heat Recovery (MVHR) Solar Photovoltaics (SPV) Micro-Combined Heat and Power (CHP) Micro-Wind Generation Voltage optimisers LED Lighting

2. Methodology 2.1. Selection of sustainable energy technologies There is a long list of new sustainable energy technologies that are primarily used to reduce the reliance on fossil fuel energy use in buildings. Ideally, these technologies themselves should use less or zero energy in comparison to an equivalent conventional energy system. Table 1 shows several common technologies that are used for buildings [17], with those in bold deemed to be the most popular and selected for analysis in this paper. Most of these highlighted technologies have been used on a large number of projects in the UK [19–21], EU [22–25], US [26,27] and the UAE [28]. Typically, they are designed to last 20 years plus. However, with advancements in, for example, BuildingIntegrated Photovoltaics (BIPV) [29], each technology is now becoming more robust and connected to the building fabric over a much longer period. At present, there is limited information on the whole life CO2 e impact of each of these technologies. In addition, it is difficult to understand the processes and techniques used for assessment. This requires the use and understanding of a LCA, of which there are different types exhibiting different characteristics. 2.2. Types of LCA study A key aspect in the construction of a LCA is the creation of a Life Cycle Inventory (LCI). The LCI will hold the key data which are then used in the analysis and interpretation phases. Currently, there are three approaches to creating this inventory: (i) process analysis (ii) input-output analysis (IOA) and (iii) hybrid analysis [30], and each can be used to calculate the total energy use and CO2 e impact. A number of studies have been conducted [31– 42] which explain and comment on the approach and relevant pros and cons of each, as detailed below. 2.2.1. Process analysis With this type of “bottom up” LCA the technology would be broken down into individual stages and production data would be collected from manufacturers and/or industries. A process analysis LCA relies on databases such as Ecoinvent [43], SimaPro [44] or GaBi [45] which collects averaged data. A process analysis LCA is process specific and can be used to compare individual products. Pros – Relatively simple to use and any product or service can be assessed at a detailed level. This method can yield accurate results specific to a location and production condition as identified by Säynäjoki et al. [36]. This type of LCA analysis is the most established [39,46] and according to Treloar [41] is more accurate than the Input-Output Analysis (IOA) method. Cons – It is limited by a truncated system boundary that is recognised to underrepresent the total environmental impact. Work by Majeau-Bettez et al. [35], Lenzen and Dey [47], Lenzen [34], Treloar [40] and Crawford and Stephan [32] comment on this

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truncation error and explain that process based LCA studies can be significantly incomplete. An industry average magnitude error of approximately ±20% was noted by Crawford [48] with Lenzen [34] stating that due to the complexity of upstream requirements the error can be ±50%. Moreover, Crawford [48] and Stephan and Stephan [38] indicate that at the whole building level the order of inaccuracy can be greater than ±75%. In a further study [31] it was found that the truncation errors associated with process analysis could be up to ±87%. 2.2.2. Input-output analysis (IOA) This type of analysis can be considered as a “top down” approach and is based upon the use of macroeconomic data collated by national agencies in the form of input-output tables. These tables are typically combined with sector based environmental data. Pros – Is easier to perform than a process analysis LCA simply because it requires less data. It is also, according to Lenzen [34], Crawford [31], Treloar [41], less labour intensive and complete in comparison to process LCA. This type of LCA does not suffer from truncation error [36] but does suffer from aggregation error. Cons – IOA methods suffer from being aggregated at a sector level [35,36], reliant on prices which can and do fluctuate. This makes this type of LCA difficult to use when assessing specific products and as noted by Treloar [41] can be unreliable due to the assumptions made. Studies [49,4,50] estimate the average error to be ±40%. An additional study [34] stated that the uncertainty due to errors in using IOA can be as high as ±70%. 2.2.3. Hybrid analysis Combines process and IOA methodologies to address the shortcomings of both techniques. A variety of methods have been investigated but to date none have been implemented for application [30]. Pros – Many of the truncation error and IOA analysis shortcomings quoted by Lenzen [34] can be overcome via the use of a hybrid analysis. This type of analysis is considered by Stephan and Crawford [37] to be the most comprehensive and the four different hybridization techniques are highlighted in [30]. Cons – The most significant difficulty with hybrid analysis as identified by Crawford et al. [30] is the merger of process data with IOA data. Additionally, Crawford [31] and Treloar [41] state that process data unavailability is also a significant problem. 2.2.4. Choice of LCA study The above uncertainty and further confusion in selecting the right LCA analysis, leads to reduced confidence for LCA practitioners. This has been outlined in a recent study by Crawford et al. [51] who reviewed hybrid life cycle inventory methods and commented on the fact that most LCA users select process analysis with little understanding of its potential incompleteness. Independent of the type of LCA chosen, the most crucial consideration is the system boundary and the necessity for transparency and completeness. In 97 hybrid LCA peer reviewed publications reviewed by Crawford et al. [51], significant inconsistencies were found in the way methods and boundaries were applied. There is, therefore, a clear need for LCA practitioners to be more transparent in the methods used and boundaries considered. Inconsistency in system boundary consideration has also been noted by Dixit [52], Miller [53], Khasreen [54], Suh et al. [55] with Raynolds et al. [56] and Dixit et al. [57], in particular, stating that boundary definition is one of the most critical issues resulting in processes being left out of embodied CO2 e calculations. 2.3. Review of LCA case studies A limited number of publications [58–61] and LCA studies [12,14,62–68] contain information on the embodied CO2 e of sus-

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tainable technologies, see Table 2. These LCA studies are key as they contain the information necessary for each type of technology considered and the methods by which CO2 e is calculated. For example, Blum et al. [49] has conducted an LCA of Ground Source Heat Pumps (GSHP) and measured total CO2 e and CO2 e per kWh of thermal energy generated for space heating. The difficulty in collecting data from these studies is that each has a different functional unit (a measure of the function of the studied system). Some studies report figures in CO2 per m2 of heated floor area or CO2 e per kWh of energy used, whilst others report CO2 per unit or CO2 e per MJ of energy used. In addition, the type of LCA used is different. The scope, location, system boundary, year of assessment, service life and dataset can all differ but with some similarities i.e. the use of software such as GaBi [69] and/or the Ecoinvent [43] database. Each study investigated in this paper has been thoroughly reviewed, with Table 2 providing a summary of the key metadata including LCA method, method of data collection, Functional Unit (FU), CO2 and CO2 e calculation methods and uncertainty analysis.

3. Results 3.1. Meta-analysis of LCA studies As can be seen in Table 2 there is a wide variation in the year of study, methods of data collection and FU. Within each paper there are also numerous assumptions made. Furthermore, some technologies are extensively researched i.e. Solar PV, whilst for others there remains a lack of data. This is a significant problem for industry and academia, due to the fact that it makes comparative analysis difficult. In order to estimate the total embodied CO2 e of each sustainable energy technology, it was necessary to carefully review and comment on the relevant published literature and consider each of the following: • • • • • • •

LCA method used and scope of investigation, Method of data collection, Energy mix, Functional unit, Service life, CO2 and CO2 e reporting and conversion, Comparison of means.

3.1.1. LCA method used and scope of investigation For most studies reviewed in this paper, a process based LCA was considered, except for [4,49,50]. Furthermore, a process LCA cradle to grave analysis dominates, with [75,76,80] considering the cradle to gate only. In each paper, the system boundary was different, resulting in different functional units, which makes like-forlike comparisons problematic. For example, [75] investigated the CO2 impact of a MVHR system used in 14 homes, over a period of 20 years, in a specific location in the UK. For this study a process LCA was used. Whereby Hernandez and Kenny [4] considered an MHVR system in a single semi-detached house used for 20 years in Ireland, using an IOA LCA. Both studies are investigating the embodied impact of MVHR systems using different LCA methods in separate countries and houses. Therefore a comparison of one system with the other is not possible. The type of LCA used in each study is also a significant consideration, as each will have an inherent truncation error as described in Section 2.2. All but three of the studies examined in this review paper used a process LCA methodology which is subject to the average truncation error of ±20% with [4,49,79] potentially subject to a higher average error of ±40% due to the use of the IOA methodologies.

3.1.2. Method of data collection Each LCA study investigated in Table 2 used information from a database and/or independent source of information i.e. a published paper, report or manufacturers data sheet. The earliest assessment was completed in 1990 [72] with the most recent in 2017 [10]. Ideally, each study would be assessed and compared using the same method i.e. the Simapro software using the Ecoinvent database. The popularity of different methods, for the studies investigated in this paper, can be seen in Table 3. Clearly the independent publications, reports, manufacturers’ data and Ecoinvent are the most popular sources of information. With Simapro being the most commonly used LCA software. This fragmented approach to data collection is a significant problem, as technologies cannot be compared on a like-for-like basis. For example, Greening and Azapagic [70] examined the life cycle impact of GSHP using the Ecoinvent v2.1 database and GaBi v4.4 software. The Ecoinvent database uses the very latest ISO [81] and EN15804 Environmental Product Declaration (EPD) standards [82] and is therefore considered to be the industry standard. GaBi v4.4 is one of the most well established LCA tools used in the creation of a LCA. In contrast, Blum et al. [49] also examined the environmental impact of GSHP. The data collected to undertake the analysis in this paper, was collected from a private study undertaken by an energy company. Therefore the information provided in [70] is significantly more reliable than that of [49]. 3.1.3. Energy mix The energy mix i.e. the percentage of coal, gas, nuclear, renewables and other that are used to generate electricity, differ by year and country for each study in Table 2. These factors can significantly affect the resultant embodied CO2 e of a sustainable energy technology. For example, in 2007 the UK electricity mix consisted of approximately 38% Gas, 29% Coal, 28% nuclear, 2% renewables, 3% other [83]. In 2017, that mix changed to 40% gas, 30% renewables, 18% nuclear, 9% coal, 3% other [84]. According to DECC [85], in 2007 the CO2 e impact of electricity generation was 0.47 kg CO2 e/kWh generated. In 2017 this number had reduced to 0.35 kg CO2 e/kWh. This is due to the fact that the UK has increased the amount of electricity generated from renewables and reduced the amount of electricity generated from coal fired power stations. This has resulted in a “greener” less carbon intensive energy mix. Therefore for every kWh of electricity used in any piece of conventional or sustainable technology to power, ventilate, heat or cool a building in 2017, the operational CO2 e impact is 26% less than that used in 2007. In this paper, the embodied CO2 e for each technology is estimated through interpretation of the individual LCA studies. This interpretation is heavily reliant upon the use phase of the technology, which is significantly dependent upon the country and year of use. For example, the embodied CO2 e of an ASHP [70] used in the UK for 20 years has been estimated by assuming 5% of the total life cycle impact. This is based on the 2008 UK grid mix. Therefore, if this study was updated to 2017 the embodied CO2 e estimate would be lower. 3.1.4. Functional unit The Functional Unit (FU) is the reference on which the LCA results are based. In order for one study to be compared with the next the FU needs to be the same. For each study highlighted in Table 2, the FU differs by time period, base assessment year, equipment size, area and location. For example, the FU for an ASHP assessed by Greening and Azapagic [70] is 1 kWh of thermal energy generated over a 20-year period for domestic heating in a UK case study. The FU for a second ASHP study [71] is 1 kWh of heat generated for 18 UK houses over a 15-year period. Ideally all FUs would have the same normalised measure i.e. kgCO2 e/m2 or kgCO2 e/kWh for each sustainable energy technology. In this paper the measure

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Table 2 LCA case studies. Author

Sustainable Energy Technology

Greening et al. [70]

Blum et al. [49]

Year of study

Country Functional unit (FU) CO2 / CO2 e impact or region (including service calculated life)

CO2 /CO2 e calculation method

Ground Source Process – cradle to GaBi v4.3 and Heat Pump grave Ecoinvent v.2.1 (GSHP)

2008

UK

2001 CML 2 Baseline No

GSHP

Private sector qualitative and quantitative

2006

Germany

Greening and Air Source Azapagic[70] Heat Pump (ASHP)

Process – cradle to GaBi v4.3 and grave Ecoinvent v.2.1

2008

UK

Johnson [71]

Process – cradle to GaBi v4.3 and grave Ecoinvent v.2.2

2008

UK

ASHP

LCA Method and System Boundary

IOA – use stage only

Method of data collection

Ardente et al. Solar Thermal Process – cradle to Private sector study 1990– [72] (ST) grave 1994

Italy

Aini Masruroh ST et al. [73]

Process – cradle to ISO 14040 with no grave database specified

UK

Goggins et al. Mechanical [74] ventilation with Heat Recovery (MVHR)

Process – cradle to ICE database v2 and 2011 grave Ecoinvent v2.2

Ireland

Monahan and MVHR Powell [75]

Process – cradle to SimaPro v7.1 plus gate only private

2009

UK

Hernandez MVHR and Kenny [4]

IOA – cradle to grave

Ecoinvent v.2.1 and ICE v.1.6

2010

Ireland

Nawaz and Towari [9]

Solar Photovoltaic (SPV)

Process – cradle to Siemens grave Manufacturers data sheet

2004

India

Alsema [76]

SPV

Process – cradle to Manufacturers data gate only sheets and publications

1999

Western Europe

Pacca et al. [77]

SPV

Process – cradle to SimaPro and private 2006 grave manufacturers data

2005

US

1 kWh of GSHP CO2 e Total and thermal energy operational generated over a 20-year period for domestic heating in a UK case study 1 kWh of GSHP CO2 Total lifecycle residential heating for residences in the Baden-Wurttemberg region of Germany over an assumed period of 20 years 1 kWh of ASHP CO2 e Total and thermal energy operational generated over a 20-year period for domestic heating in a UK case study 1 kWh of ASHP heat CO2 e Total, generated for 18 UK operational and domestic house embodied types over a 15-year period 1 kWh of solar CO2 e Total and thermal (ST) heat operational generated using a collector with a net surface area of 2.13 m2 for 25 years in domestic housing in Italy 1 kWh of ST energy CO2 e Total lifecycle provided in UK residential housing by the Solarstore system over a period of 15 years 1 m2 of MVHR CO2 e Embodied heated floor area in a two-storey semi-detached residential building over 20 years in Ireland 1 m2 of MVHR CO2 Embodied heated floor area in a development of 14 homes in Norfolk (UK) over a period of 20 years 1 m2 of MVHR kWh Embodied heated floor area in energy only a two-storey semi-detached house in use for 20 years in Ireland 1 kWh of electricity CO2 Embodied created by a 10 m2 1.2 kWp Siemens SPV on the IIT building in Delhi (India) 1 kWh of energy CO2 Embodied created from a Western European manufactured SPV used for 30 years 1 kWh of electricity CO2 Embodied created by a 33 kW SPV system in the University of Michigan (US) in use for 20 years

Uncertainty analysis conducted

2006 Global Emission Model for Integrated Systems (GEMIS)

No

2001 CML 2 Baseline No

2008 UK DECC Conversion Factors

Yes – adjustments made and averages presented

1992 Italian Environment Protection Agency conversion factors

No

2005 UK DECC Conversion Factors

No

2011 Dwelling Energy Assessment Procedure (DEAP)

No

2009 UK DECC Conversion Factors

No

2010 Dwelling Energy Assessment Procedure (DEAP)

Yes – Estimated at 44% for IOA

2004 Indian conversion factors

No

1999 Western European emission factors

No

2006 US emission factors

Yes – adjustment of energy consumption values

(continued on next page)

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Table 2 (continued) Author

Sustainable Energy Technology

LCA Method and System Boundary

Tripanagno stopoules et al. [78]

SPV

Process – cradle to SimaPro grave

Meier [50]

SPV

Hybrid– cradle to Publications and 20 0 0 grave Carnegie Mellon EIO database

Hammond et al. [2]

SPV

Process – cradle to Simapro 7.1 and grave Ecoinvent 2.1

2007

Allen et al. [79]

SPV

Process and IOA – Simapro 7.1 and Ecoinvent 2.1 cradle to grave

2006

US DoE [10]

Light Emitting Process – cradle to Ecoinvent 2.2 and Diode (LED) grave Manufacturer data sheet

Tähkämö et al. LED [11]

Method of data collection

Process – cradle to Simapro 7.1 and grave EcoInvent

Year of study

Country Functional unit (FU) CO2 / CO2 e impact or region (including service calculated life)

CO2 /CO2 e calculation method

2005

European 1 kWh of electricity CO2 e Embodied created from a 3 kWp flat roof mounted SPV system used for 30 years at the University of Patras (Greece) US 1 kWh of electricity CO2 e Embodied created from a 8 kWp SPV system used for 30 years in Colorado (US) UK A 40 m2 2.1 kWp CO2 e Embodied mono-crystalline SPV roof tile system used for 25 years in the UK UK A 15 m2 2.1 kWp CO2 e Embodied mono-crystalline PV roof tile system used for 25 years in the UK US Total light output of CO2 e Total and a Philips EnduraLED embodied 12.5 W lamp over its lifetime of 20 years in the US. EU Total light output of CO2 e Total and a 19 W luminaire embodied used for 20 years in the EU.

20 0 0 CML 2 Baseline Yes – using the Eco-indicator 95 method

2017

2010

Uncertainty analysis conducted

20 0 0 US emission factors

No

2001 Eco-indicator 99

Yes – for the financial evaluation only

2006 UK DECC Conversion Factors

No

2017 US Department Yes – errors in of Energy (DoE) manufacturing, Conversion Factors recycling and transport 2010 CML 2 Baseline Yes – missing data 2001 reported

Table 3 Methods of data collection and analysis. Author

Greening and Azapagic [70] Blum et al. [49] Greening and Azapagic et al. [70] Johnson [71] Ardente et al. [72] Aini Masruroh et al. [73] Goggins et al. [74] Monahan and Powell [75] Hernandez and Kenny [4] Nawaz and Tiwari [9] Alsema [76] Pacca et al. [77] Tripanagnostopoules et al. [78] Meier [50] Hammond et al. [2] Allen et al. [79] US DoE [10] Tähkämö et al. [11]

Methods of data collection and analysis Ecoinvent √

GaBi √

√ √

√ √

ICE

ISO14040

Independent

Simapro

√

√ √ √

√

√

√

√ √ √ √

√

√ √

√ √ √ √ √

of the embodied CO2 e impact is therefore expressed as kgCO2 e/FU. The FU is of critical importance in the generation of this embodied CO2 e value, as it is dependent upon a number of factors including the service life of the technology considered. For example, Ardente et al. [72] considered the impact of a Solar Thermal (ST) system used for 25 years in Italy and Aini Masruroh et al. [73] considered the impact of a different ST system used for 15 years in the UK. 3.1.5. Service life Service life for each study is different with the minimum of 15 years considered for ASHP by [71] and ST by [73] and the maximum of 30 years for SPV by Alsema [76], Pacca et al. [78] and Meier [50]. Calculating the embodied CO2 e of each technology can and is dependent upon service life. For those studies that do not

√ √ √ √

provide a direct embodied CO2 e figure [70,49,72,73], an estimate based on service life is made. This estimate is a percentage of the total lifetime emission and is 5% for [49,70] and 1% for [72,73]. If the service life is reduced or increase this percentage estimate would change. For example, [2] examined the use of a 40 m2 2.1 kWp monocrystalline SPV roof system generating 1720 kWh of electricity per year for 25 years in the UK. The total embodied CO2 e is reported as 4500 kg or 300 kg/m2 and the kgCO2 e/FU is 0.105, see Table 4. Should this particular technology be considered over 15 years, the embodied CO2 e would remain at 4500 kg or 300 kg/m2 and the kgCO2 e/FU would change from 0.105 to 0.174. A 66% increase in embodied CO2 e per FU. This example serves to highlight the importance and significance of the service life in the calculation of the embodied CO2 e impact.

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Table 4 Embodied CO2 e. Year

Author

Sustainable Energy Technology

Country or Region

Total Embodied CO2 e (kg)

Embodied CO2 e per Functional Unit (kgCO2 e/FU)

Total and Embodied CO2 e estimates from derived from

2012

Greening and Azapagic [70] Blum et al. [49] Greening and Azapagic [70] Johnson [71] Ardente et al. [72] Aini Masruroh et al. [73] Goggins et al. [74] Monahan and Powell [75] Hernandez and Kenny [4] Nawaz and Tiwari [9] Alsema [76] Pacca et al. [77] Tripanagnostopoules et al. [78] Meier [50] Hammond et al. [2] Allen et al. [79] US DoE [10] Tähkämö et al. [11]

GSHP

UK

3916

0.010

[70] Section 3.2.1

±20%

GSHP ASHP

Germany UK

3200a 5600

0.008c 0.014

[49] Section 3.2.1 [70] Section 3.2.2

±40% ±20%

ASHP ST ST

UK Italy UK

1563 650 750

0.026 0.026 0.030

[71] Section 3.2.2 [72] Section 3.2.3 [73] Section 3.2.3

±20% ±20% ±20%

MVHR MVHR

Ireland UK

661 600a

0.073 0.066c

[74] Section 3.2.4 [75] Section 3.2.4

±20% ±20%

MVHR

Ireland

661

0.073

[4] Section 3.2.4

±40%

SPV

India

1330a , b

0.028c

[9] Section 3.2.5

±20%

SPV SPV SPV

Europe US EU

2104a , b 273a , b 610b

0.190c 0.072c 0.082

[76] Section 3.2.5 [77] Section 3.2.5 [78] Section 3.2.5

±20% ±20% ±20%

SPV SPV SPV LED LED

US UK UK US EU

219b 300b 249b 200d 134d

0.039 0.105 0.087 0.005 0.018

[50] Section 3.2.5 [2] Section 3.2.5 [79] Section 3.2.5 [10] Section 3.2.6 [11] Section 3.2.6

±40% ±20% ±40% ±20% ±20%

2010 2012 2011 2005 2006 2016 2011 2011 2006 20 0 0 2007 2005 2002 2012 2008 2012 2013 a b c d

Average % error

kgCO2 . per m2 . kgCO2 /FU. 40 LED lights.

3.1.6. CO2 and CO2 e reporting and conversion The methods by which each of these LCA studies have calculated embodied CO2 and CO2 e vary. For example, CO2 only was calculated by Blum et al. [49], Monahan and Powell [75], Nawaz and Tiwari [9], Alsema [76] and Pacca et al. [77] and a study by Hernandez and Kenny [4] calculated embodied energy use (kWh) only. Calculated CO2 e figures are presented in the remainder of the studies which have used the ISO standards [81] and Greenhouse Gas (GHG) Protocol [86] as outlined by [3]. All of the reviewed studies, except for [49,76,80] use the GHG protocol methodology, whereby CO2 e is calculated following Eq. 1:

Emission = Act ivit y Data x Emission F actor

(1)

where: Emission is the total [CO2 e]; Activity Data is the amount of energy i.e. electricity generated in [kWh] and Emission Factor is the average value for a given time period of emission per unit [kgCO2 e/kWh]. 3.1.7. Comparison of means Analysis of the LCA studies has revealed the inherent lack of any form of uncertainty analysis, with [2,4,10,11,71,77,78] commenting on the lack of data and errors in using process and IOA LCA methodologies only. In [71] the LCA software GaBi was used and in [2,11,77,78] SimaPro was used. The uncertainty analysis function available in each software was not used. This would have been beneficial given the large number of variables, with varied system boundaries and the inherent truncation errors as discussed in Section 2.2. The software’s used to conduct LCA studies, for the articles reviewed in this paper, are either GaBi or Simapro. As discussed, both have the ability to conduct uncertainty analysis. For example, GaBi Analyst [87] has a feature contained with the software to enable a user to conduct sensitivity and Monte Carlo analysis. Similarly, Simapro has the ability to conduct uncertainty analysis via the use of Monte Carlo simulation [88]. Which is a numerical way of processing uncertainty data to establish an uncertainty

range. Within each software, the user is able to consider different distribution types for each data set, from which simulations can be run and uncertainty can be found. 3.1.8. Commonality In order for a sustainable energy technologies database to exist there needs to be a consistent and fixed method of assessment. This will include: - A consistent use of one type of LCA method with a fixed system boundary i.e. a process LCA using a cradle to grave approach, - The method of data collection must be from one source i.e. Ecoinvent 2.1, - The software used for the calculation should ideally be the same i.e. GaBi v.4.3, - The year of study and country of assessed must be fixed, - The FU must be consistent, based on a fixed unit of measure over a fixed time period, - The calculation of CO2 e must consider the total lifecycle of the technology and furthermore the method used should be the same i.e. UK DECC Conversion Factors, - Finally, there is a need to consider uncertainty and the use of analysis within the LCA software. With all of these fixed measures in place the database technologies could then be compared to each other. 3.2. Embodied CO2 e data As can be seen in Table 2 and the proceeding examination of the studies, each LCA has reported total, operational and/or embodied CO2 or CO2 e using different approaches with a high degree of variation. Should an individual wish to discover the embodied CO2 e of a sustainable energy technology being considered for their own building it is recommended that an independent and specific process, IOA or hybrid LCA, is conducted. Should, however, a user

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wish to quickly estimate the embodied CO2 e for a technology then at present this is not a straightforward task. The aim of this review paper is to overcome this problem by presenting information in a more readily accessible format using total CO2 e (kg) and total CO2 e per functional unit (kgCO2 e/FU). To create this measure, it has been necessary to analysis each LCA study presented in Table 2 and convert different sets of data as outlined below. A new set of embodied CO2 e values for each sustainable energy technology is presented in Table 3. All the values presented in Table 3 have been derived directly or indirectly from the LCA studies highlighted in Table 2. Details of the conversion methodologies, assumed kWh, time periods, country of origin are provided below. Five of the studies [9,49,75–77] are reported as CO2 only. 3.2.1. Ground Source Heat Pump (GSHP) A GSHP uses buried pipes to extract heat from the ground. The heat can then be used in radiators, underfloor or warm air heating systems and hot water. The GSHP will circulate a mixture of water and antifreeze around a series of pipes which require energy. Heat from the ground is absorbed into the fluid and then passes through a heat exchanger into a heat pump. A study by [70] reported on the impact of a GSHP in use for 20 years in the UK. The total embodied lifetime CO2 e emission was estimated as 3916 kg. This calculation was based on a 10 kW GSHP, operating 20 0 0 h/year, generating 20,0 0 0 kWh of energy per year for 20 years, with 95% of the CO2 e assigned to the use phase. The total embodied CO2 e/kWh can then be estimated as 0.01 kgCO2 e/kWh. In contrast, a German study [49] quoted the total lifecycle CO2 e emissions of a similar 20 year GSHP to be 0.15 kg CO2 e/kWh. If it is assumed that 95% of these emissions were derived from the use phase, then the lifetime embodied CO2 e can be rounded up to 0.008 kg CO2 /kWh. Furthermore, if an assumption is made that the GSHP operates for 20 0 0 h/year, generating 20,0 0 0 kWh of energy per year then total embodied CO2 e can be estimated as 3200 kg. 3.2.2. Air Source Heat Pump (ASHP) An ASHP is commonly used to replace/supplement a conventional heating system. In short, the pump will absorb heat from the outside air to supplement underfloor heating systems and/or provide hot water. The ASHP can extract heat from the outside air even when temperatures are as low as −15 °C. In a study by Johnson [71] the total 15 year lifecycle impact of a typical UK ASHP was assessed using the Publicly Available Standard (PAS) 2050 [89]. A bill of quantities had been produced for a typical 10 kW pump used in a residential building in the EU. The results show that the total heat generated over 15 years was 59,135 kWh and the embodied CO2 e impact of this specific type of ASHP used in a semi-detached home in the UK with cavity walls was approximately 1563 kg. This value is the summation of the CO2 e values presented in Table 11 of that study [71] from refrigerant production (630 kg), heat pump (260 kg) and the distribution system (673 kg). Therefore, to provide this amount of heat, the embodied CO2 e per kWh is 0.026 kg. In [70], the total 20-year lifecycle CO2 e per kWh from an ASHP is estimated as 0.276 kgCO2 e/kWh of delivered energy. If 95% of this value presents the operational CO2 e impact then an estimate of 0.014 kgCO2 e/kWh is representative of the embodied impact. In [70] it is assumed that an ASHP operates for 20 0 0 h/year and generates 20,0 0 0 kWh of energy per year. The total embodied CO2 e for 20 years of operational use can then be estimated as 5600 kg. 3.2.3. Solar Thermal Unlike solar PV systems, Solar Thermal (ST) systems capture heat directly from the sun and use it to heat water for use within the building. They are most commonly used for residential buildings and operate using a simple process. Further details and a breakdown of the component parts of a typical Italian system can

be seen in a study by Ardente et al. [72]. In this study, it is estimated that the 25-year lifecycle CO2 e impact of a typical solar thermal system is 650 kg, of which 99% is generated at the embodied CO2 e stage. Estimates suggest that a typical domestic generation figure for ST is approximately 10 0 0 kWh per year [90]. Then, the kg CO2 e/kWh over a 25-year period can be estimated as 0.026 kgCO2 e/kWh. In a further study [73], the LCA impact following ISO 14040 guidelines of a ST collector used in the EU was calculated. This study found that for every kWh of energy created, the solar thermal system equivalent lifecycle CO2 e was between the ranges of 0.023 kg and 0.036 kg, of which 99% was reported to be from the embodied CO2 e stages. Assuming a higher estimate of 0.036 kg CO2 e per kWh and a typical domestic generation figure for each panel of approximately 10 0 0 kWh per year, the total annual CO2 e is therefore 30 kg. Assuming the system would be in use for 25 years, this would result in a total CO2 e output of 750 kg. This is comparable to the 650 kg as reported by [72]. 3.2.4. Mechanical Ventilation and Heat Recovery (MVHR) MVHR systems are becoming increasingly popular because they not only allow heat to be recovered from outgoing warm air but also allow a building’s envelope to be built airtight whilst providing good air quality. In short, a MVHR system will supply fresh air and extract stale air with negligible heat loss in the process. Recent reviews of the embodied CO2 impact of MVHR systems, following the ISO 14040 methodology, are sparse, with [4,74,75,91,92] providing the best sources of information. A LCA study of a typical Irish residential MVHR system [74] revealed that the total 20-year embodied CO2 e was 661 kg. Further analysis in the UK by Monahan and Powell [75] estimated the embodied CO2 of MVHR systems to be 600 kg. In a study by Hernandez and Kenny [4], the embodied energy per m2 of heated floor area over 20-years was estimated at approximately 90 0 0 kWh. Assuming the systems in use in [74] and [75] have the same embodied energy per m2 of 90 0 0 kWh over a 20-year period, then the total embodied kgCO2 e/kWh can be estimated and rounded to 0.073 kgCO2 e for [74] and 0.066 for [75]. For [4] an assumption is made that the total embodied CO2 e (661 kg) is the same as [74] as both studies were conducted in Ireland using the Ecoinvent database. Therefore, the same 0.073 kgCO2 e is assumed for [4]. However this study was conducted using the IOA LCA methodology and is therefore subject to a higher percentage error. 3.2.5. Solar PV A large number of studies undertaken on the embodied CO2 e impact of solar PV including [2,5–9,13,50,76–80,93–97]. Published LCAs are available and do quantify the life cycle CO2 e energy impacts. However, these studies are difficult to compare. Each uses different methods, system boundaries, data sources, technologies, locations and lifetimes. As a result, the range is large, as outlined in [77]. This paper is focused on the comparisons with 1st generation silicon cells, as approximately 85% of panels worldwide are of this type [98]. Most LCA studies from predominantly EU and US sources [2,9,50,76–80] estimate this embodied CO2 e impact with a wide range of variability. In this review paper the total embodied CO2 e (kg) is presented per m2 of panel. This is based on the estimate that every 1 m2 of panel is approximately equal to the output of a 0.14 kWp array. This estimate is based on similar values of 0.125 kWp, 0.14–0.07 kWp and 0.14–0.1 kWp as reported by [99,100,101] respectively. The CO2 e per functional unit (kg/FU) differs by type with most values presented as kgCO2 e per kWh of energy created. In a study by Nawaz and Tiwari [9] the CO2 emissions were presented for a range of solar PV systems in India. A rooftop mounted 10 m2 system used for 35-years created approximately 200 kWh/m2 /year with an embodied CO2 of 13,300 kg (or 1330 per m2 ). A 10 m2 solar PV array used for 35-years, therefore had an

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embodied CO2 /kWh of 0.19. In 20 0 0 [76] undertook research into the energy payback and CO2 of rooftop mounted solar PV systems manufactured in Europe and used for 30-years in Italy. A figure of 0.055 kgCO2 /kWh is presented. In this study, the panels had been exposed to 1700 kWh/m2 /yr of irradiation and the performance ratio was 0.75. Therefore, an estimate of total output over 30-years is 38,250 kWh. A total embodied CO2 can then be estimated as 2104 kg per m2 . A more thorough analysis of over 29 studies between 1989 and 2003 by [77] estimated a range of between 0.05 kg and 2 kg of CO2 e/kWh with for example [6,102] reporting values of 0.13 and 0.44 kg CO2 e/kWh respectively. It should be noted that each of these studies will differ by scope, system boundary, LCA type, timescale etc. and cannot be directly compared with each other. A 33 kWp multi-crystalline and thin film solar PV system was assessed for use in the US over a 20-year period by Pacca et al. [77]. This large solar PV array generated 44,794 kWh of electricity a year and the embodied life cycle CO2 emissions for panels manufactured in the US was reported as 0.072 kg of CO2 /kWh. Therefore, the total CO2 for 20 years was 64,503 kg. To compare to the other studies examined in this paper, the total embodied CO2 per m2 is estimated as 273 kg. This value was assumed based on the estimate that a 33 kWp array is approximately equal to 236 m2 of surface area (1 m2 equal to 0.14 kWp). More recent analysis by Tripanagnostopoules et al. [78] in Greece using the SimaPro database for a solar PV system in use for 30-years has shown that the lifetime embodied CO2 e/kWh of a 3 kWp array (approximately 21 m2 ) is 0.082 kg, based on an annual output of 5180 kWh and embodied CO2 e is 12,810 kg. Per m2 this is equivalent per m2 to 610 kg. In comparison Meier [50] examined a hybrid LCA of an 8 kWp (57 m2 ) rooftop mounted solar PV system in the USA in use for 30 years and found that the embodied CO2 e of the system was 12,500 kg and the annual electrical output was approximately 10,796 kWh per year. In use for 30-years this equates to an embodied value of 219 kg per m2 and 0.039 kg CO2 /kWh. Two UK studies by Allen et al. [79] and Hammond et al. [2] provide more accurate UK specific data with [79] reporting that a 15 m2 , 2.1 kWp monocrystalline solar PV system supplying 1720 kWh of electricity per year for 25 years (43,0 0 0 kWh over its lifetime) had an embodied CO2 e of 3740 kg (249 kg per m2 ), resulting in a lifetime embodied CO2 e of 0.087 kg/kWh. A second UK study by [2] analysed a 2.1 kW (∼15 m2 ) rooftop array with an embodied CO2 e of 4500 kg and the same energy generation of 1720 kWh per year for 25-years. This resulted in a lifetime CO2 e per m2 of 300 and 0.105 CO2 e per kWh.

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A European investigation [11] found that the whole life CO2 e impact of a single LED light, used for 20 years, was 167 kg. Assuming a 2% embodied CO2 e impact this equates to 3.34 kg per light. Therefore 40 LEDs, in use for 20 years, would emit the equivalent of 134 kg. Significantly less than the 200 kg USA estimated above. Annual energy use for a typical domestic European LED light has been estimated by TheGreenAge [106], who calculated a value of 9.13 kWh per light. Therefore 40 lights used over 20 years would use approximately 7304 kWh. Considerably less than the USA study estimated. The total European CO2 e per kWh is estimated as 0.018 kg. A summary of the above information is presented in Table 4, which shows the technology considered, the country or region of origin, the total embodied CO2 e and embodied CO2 e per functional unit. The average % error for each study is also considered. 3.3. Comparison of means Each of the figures presented in Table 3 are inherently under or over representative due to the average ±20% error for process LCA studies and average ±40% error for IOA LCA studies as identified earlier in this study. As noted in Section 2.2 this percentage error could be much higher than these assumed averages. The results show that uncertainty in the data can have a significant effect on the contribution of the embodied CO2 and CO2 e impact. For example, the study by Pacca et al. [77] investigated a solar PV system used in the US in 2006. A process LCA based on a cradle to grave analysis has shown that the embodied CO2 to create a kWh of electricity was 0.072 kg. This value could be under represented or overrepresented by on average ±20% resulting in new values of 0.086 kg and 0.058 kg respectively. Furthermore, the study by Hernandez and Kenny [4] on the use of MVHR in Ireland used an IOA cradle to grave technique which is known to be under or overrepresented by on average of 40%. This would change the original estimate of 0.073 kgCO2 e/kWh to a possible 0.102 kg and 0.044 kg respectively. Fig. 1 presents the embodied CO2 e per functional unit and possible average minimum and maximum values as error bars. There has been no statistical analysis performed in the derivation of the error bars and they simply serve to highlight the average inaccuracy. A more accurate analysis of each LCA study, using for example an analysis of variance (ANOVA) is beyond the scope of this paper and would need to be conducted to obtain a higher degree of certainty. 3.4. Significance of results

3.2.6. LED Lighting The high luminous efficacy of Light Emitting Diode (LED) lighting means that they use less energy and therefore would emit less CO2 e than conventional lighting systems. Less is known of the embodied impact of this new type of lighting but the potential life cycle impacts have been investigated in several studies [10,103–105]. A review of the life cycle energy and environment impact of LED lighting products was conducted by the US Department of Energy [10]. In this study, a comparative LCA of the impacts of incandescent and LED lights was investigated. An LED luminaire used for 20-years would emit the equivalent of 0.32 kg CO2 e per lumen, where a lumen is the unit of light flux from a light source. In a USA study [10] it was estimated that a 2017 LED’s total light output would be 824 lm and would use approximately 3900 MJ (1084 kWh) over its lifetime. Therefore, the total kg of CO2 e per light over 20 years is 264 kg of which 98% is the operational CO2 e [10] (259 kg) and 2% (5 kg) is the embodied CO2 e. Assuming the average residential building contains 40 LED lights, the total embodied CO2 e would therefore be approximately 200 kg and the total embodied CO2 e per kWh (for 40 lights) is 0.0046, which is rounded to 0.005 for this paper.

Sustainable energy technologies are used to supplement or replace existing technologies that provide power and heat to buildings. Power to most buildings, in the form of electricity, is commonly supplied direct from the national grid and heating and hot water are largely delivered through central heating systems powered by natural gas fired boilers, providing approximately 83% of heating demand in the UK [107]. An Environmental Product Declaration (EPD) report created for an ‘A’ rated domestic gas fired boiler used in the EU [108] concluded that the total CO2 e is 330 kg when used to create 10 0 0 kWh of thermal energy. The embodied CO2 e per kWh is therefore 0.330 kg. A study by Koubogiannis and Nouhou [109] in Greece calculated that the embodied CO2 e of a similar type of boiler was approximately 353 kg. Therefore, an estimated CO2 e/kWh (based on 10 0 0 kWh created) is 0.353 kg. These values of 330 kg and 353 kg are approximately half of the impact of a Solar Thermal system used in one region of Italy [72], or an MVHR system used in a specific study in Ireland [74], see Table 4. The values are also minimal in comparison to the total embodied CO2 e impact of a building. In 2012 [110] conducted an LCA of a typical UK brick and block built 2-storey detached house. In

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Fig. 1. Comparison of means.

their assessment all life cycle stages were considered, including house construction, use and demolition after 50 years. The total embodied CO2 e impact was 41,273 kg. The calculation of CO2 e was undertaken using the Ecoinvent V3.1 database [62] and GaBi LCA tool [69]. The study [110] did not include the impact of building services needed for power and heating. However, if the embodied CO2 e impact of a typical ‘A’ rated domestic gas fired boiler is added then the total CO2 e increases from 41,273 kg to 41,603 kg - a 1% increase in embodied CO2 e. Although this seems insignificant, a move to more energy efficient buildings, has created the need for more highly insulating products, enhanced glazing and sustainable energy technologies. This can increase the embodied CO2 e of buildings significantly [52,111]. In a study by Sartori and Hestnes [112], 60 case studies across different countries were examined. It was reported that embodied emissions account for between 2 and 38% and 9 and 46% of the total life cycle emissions for a conventional building and low energy building respectively. Further examination by Ramesh et al. [113] of 73 residential and office buildings across 13 countries, concluded that embodied emissions accounted for 10–20%. A paper by Ibn-Mohammed et al. [114] commented on the large variation in embodied emissions of conventional and more energy efficient buildings with values of 3–35% [115], 37–43% [116], 60% [117], 67% [118] and 80%+ [119,120] being reported. More extreme examples, including very low energy and Nearly Zero Energy Buildings (NZEB), see the embodied CO2 e percentage share being 26 to 57% and 74 to 100% respectively [121]. Further analysis by Cullura et al. [122] reported the embodied CO2 e of NZEB as 78% with further details on additional buildings provided in [123]. Given the significant forecasted increase in sustainable energy technologies and lack of detailed LCA studies, this paper has shown that the choice of system is a very important consideration.

3.5. Embodied vs operational impact It should be noted that although there is a significant embodied CO2 e footprint for some sustainable energy technologies, this does not indicate that they are poor options. The savings made during the use (operational) stage can and do overshadow these results. For example, Sturgis [124] states that installing a solar PV array on a typical home will save around 900 kgCO2 e/year. Given that in a UK study by Hammond et al. [2] a typical residential development with a 2.1 kW rooftop array had an embodied CO2 e of 4500 kg, the payback is 5 years. In addition for every kWh of UK electricity delivered to a building in 2017, 0.3516 kg of CO2 e were released [125]. Therefore if this solar PV system was fitted, knowing that it can generate 1720 kWh per year, this is a further operational CO2 e saving of 6058 kg.

3.6. Limitations of the study There are a number of limitations to this study. The most obvious is the lack of supporting LCA data for each of the chosen sustainable energy technologies. All figures presented are based upon limited case studies apart from solar PV. The sample size, is therefore, insufficient to place a high level of high confidence in the data. Should the sample size be increased, through the generation of more LCA studies in this area, then the uncertainty would decrease and the confidence level would increase. A second limitation can be seen in Table 2 with the functional units and assumptions made in each LCA study. Ideally, each technology should be assessed in one global location with the same functional unit. This would enable a more accurate comparison to be made and ensure that the user is able to use the embodied CO2 e value with a higher degree of confidence.

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4. Conclusions A number of conclusions can be drawn from this review of the embodied CO2 e impact of sustainable energy technologies. Additional LCA case studies for all existing and new technologies are essential, as there remains a lack of accurate data. This is a significant knowledge gap, as these technologies are becoming increasingly popular. Furthermore, it should also be noted that, although these technologies have a significant embodied CO2 e footprint (specifically for low and zero carbon buildings), this does not indicate that they are poor options. Typically, the savings made during the use stage overshadow the embodied impact. For example, Sturgis [124] states that installing a solar thermal system into a typical UK home will save approximately 550 kgCO2 e/year. Given that the total embodied CO2 e of a solar thermal system used in the UK is approximately 750 kgCO2 e [73], see Table 4, then the embodied CO2 e becomes less significant when the full 50-year life cycle of a building is considered. If, however, this typical UK home was replaced with a zero carbon equivalent, then the embodied CO2 e of solar thermal becomes much more significant. Clearly there are environmental benefits in the use of sustainable energy technology but there remains a significant problem - the finance and the extra capital expenditure required to install and maintain the technology, as considered by Finnegan et al. [126], Audenaert et al. [127], Anderson et al. [128], Bolton and Hannon [129], Contreras [130] and Leckner and Zmeureanu [131]. References [1] C. De Wolf, F. Pomponi, A. Moncaster, Measuring embodied carbon dioxide equivalent of buildings: a review and critique of current industry practice, Energy Build. 140 (April) (2017) 68–80. [2] G. Hammond, H. Harajli, C. Jones, A. Winnett, Whole systems appraisal of a UK Building Integrated Photovoltaic (BIPV) system: energy, environmental and economic evaluations, Energy Policy 40 (2012) 219–230. [3] R. Heijungs, J. Guinée, G. Huppes, R. Lankreijer, H. Udo de Haes, A. Wegener Sleeswijk, A. Ansems, P. Eggels, V. Duin R, H. Goede, Environmental Life Cycle Assessment of products. Guide and Backgrounds, Leiden University, Leiden, 1992. [4] P. Hernandez, P. Kenny, Development of a methodology for life cycle building energy ratings, Energy Policy 39 (6) (2011) 3779–3788. [5] V. Fthenakis, H. Kim, Photovoltaics: life-cycle analyses, Sol. Energy 85 (2011) 1609–1628. [6] M. Ito, K. Kato, H. Sugihara, T. Kichimi, J. Song, K. Kurokawa, A preliminary study on potential for very large scale photovoltaic power generation (VLS-PV) system in the Gobi Desert from economic and environmental viewpoints, Sol. Energy Mater. Sol. Cells 75 (2003) 507–517. [7] P. Jayathissaa, M. Jansen, N. Heeren, Z. Nagy, A. Schluetera, Life cycle assessment of dynamic building integrated photovoltaics, Sol. Energy Mater. Sol. Cells 156 (2016) 75–82. [8] J. Lin Lu, H. Yang, Review on life cycle assessment of energy payback and greenhouse gas emission of solar photovoltaic systems, Renewable Sustainable Energy Rev. 19 (2013) 255–274. [9] I. Nawaz, G.N. Tiwari, Embodied energy analysis of photovoltaic (PV) system based on macro- and micro-level, Energy Policy 34 (17) (2006) 314–3152. [10] USDoE, Life Cycle Assessment of Energy and Environmental Impacts of LED Lighting Products. Part 2: LED Manufacturing and Performance, Pacific Northwest National Laboratory N14 Energy Limited, 2012. [11] L. Tähkämö, M. Bazzana, P. Ravel, F. Grannec, C. Martinsons, G. Zissis, Life cycle assessment of light-emitting diode downlight luminaire—a case study, Int. J. Life Cycle Assess. 18 (5) (2013) 1009–1018. [12] G. Hammond, C. Jones, Inventory of Carbon and Energy, University of Bath, Bath, 2005. [13] Y. Kemmoku, K. Ishikawa, S. Naka, T. Kawamoto, T. Sakakibara, Life cycle CO2 emissions of a photovoltaic/wind/diesel generating system, Electr. Eng. Jpn. 138 (November (2)) (2001) 14–23. [14] J. Anderson, D. Shiers, Green Guide to Specification, John Wiley & Sons, London, 2009. [15] D.D. &. Analytics, World Green Building Trends Developing Markets Accelerate Global Green Growth 2016, Dodge Data & Analytics, 2016. [17] N. Foundation, Sustainable Technologies - The Experience of Housing Associations, HIS BRE Press, London, 2015. [18] S. Finnegan, in: New Financial Strategies for Sustainable Buildings, Taylor and Francis, Liverpool, 2017, p. 140. [19] T. W. Institute, Is Sustainability Still Possible, Island press, 2013. [20] G. Simon, Sustainable buildings: BREEAM case studies, J. Build. Surv. Apprais. Valuation 2 (2013) 7–15.

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