The Energy and Environmental Performance of Ground-Mounted Photovoltaic Systems—A Timely Update

Home , Balance of system, Cadmium telluride, Net energy gain, Solar Frontier

energies

Article The Energy and Environmental Performance of Ground-Mounted Photovoltaic Systems—A Timely Update

Enrica Leccisi 1,3, Marco Raugei 2,3 and Vasilis Fthenakis 3,4,* 1 Department of Science and Technology, Parthenope University of Naples, Centro Direzionale-Isola C4, Naples 80143, Italy; [email protected] 2 Department of Mechanical Engineering and Mathematical Sciences, Oxford Brookes University, Wheatley OX33 1HK, UK; [email protected] 3 Center for Life Cycle Analysis, Columbia University, New York, NY 10027, USA 4 Photovoltaic Environmental Research Center, Brookhaven National Laboratory, Upton, NY 11973, USA * Correspondence: [email protected]; Tel.: +1-212-854-8885

Academic Editor: Gabriele Grandi Received: 26 May 2016; Accepted: 27 July 2016; Published: 8 August 2016 Abstract: Given photovoltaics’ (PVs) constant improvements in terms of material usage and energy efficiency, this paper provides a timely update on their life-cycle energy and environmental performance. Single-crystalline Si (sc-Si), multi-crystalline Si (mc-Si), cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS) systems are analysed, considering the actual country of production and adapting the input electricity mix accordingly. Energy pay-back time (EPBT) results for fixed-tilt ground mounted installations range from 0.5 years for CdTe PV at high-irradiation (2300 kWh/(m2ÿr)) to 2.8 years for sc-Si PV at low-irradiation (1000 kWh/(m2ÿr)), with corresponding quality-adjusted energy return on investment (EROIPE-eq) values ranging from over 60 to ~10. Global warming potential (GWP) per kWhel averages out at ~30 g (CO2-eq), with lower values (down to ~10 g) for CdTe PV at high irradiation, and up to ~80 g for Chinese sc-Si PV at low irradiation. In general, results point to CdTe PV as the best performing technology from an environmental life-cycle perspective, also showing a remarkable improvement for current production modules in comparison with previous generations. Finally, we determined that one-axis tracking installations can improve the environmental profile of PV systems by approximately 10% for most impact metrics.

Keywords: photovoltaic (PV); crystalline Si (c-Si); cadmium telluride (CdTe); copper indium gallium diselenide (CIGS); life cycle assessment (LCA); net energy analysis (NEA); energy return on investment (EROI); energy pay-back time (EPBT); environmental performance

1. Introduction Nowadays, one of the most important environmental challenges is to reduce the use of fossil fuels, such as coal, oil, and natural gas, and the associated greenhouse gas (GHG) emissions into the atmosphere. In particular, electricity and heat production accounts for one quarter of the world’s GHG emissions [1]; in parallel with this, United Nations projections show that world population is growing signiﬁcantly, as are the related rates of per capita consumption [2]. Meanwhile, the global solar photovoltaic (PV) market has been growing rapidly to address this issue and to meet the increasing demand for green power; PV’s cumulative installed capacity at the end of 2015 was 227 GWp [3], resulting from 100-fold growth over 14 years of development. The compound annual growth rate (CAGR) of PV installations was 44% between 2000 and 2014. The market in Europe has progressed from 7 GWp in 2014 to around 8 GWp in 2015, while in the US it has grown to 7.3 GWp,

Energies 2016, 9, 622; doi:10.3390/en9080622 www.mdpi.com/journal/energies Energies 2016, 9, 622 2 of 13 with large-scale and third-party ownership dominating. China and Japan have become the biggest PV markets with annual (2014) deployments of 11 GWp and 9.5 GWp respectively, and corresponding cumulative capacities of 28.2 GWp and 23.3 GWp [3]. In addition, several established markets have confirmed their maturity, including Korea with 1.0 GWp, Australia with 0.9 GWp, and Canada with 0.6 GWp [3]. PV systems may be classified into first, second, and third generation technologies—first generation technologies are based on single- and multi-crystalline silicon (c-Si); second generation technologies consist of thin film technologies such as amorphous silicon (a-Si), multi-junction thin silicon film (a-Si/µc-Si), cadmium telluride (CdTe), copper indium (di)selenide/(di)sulphide (CIS), and copper indium gallium (di)selenide/(di)sulphide (CIGS); third generation technologies include concentrator PVs, organics, and others [4]. Within this variety of technologies, Si-wafer based (first generation) technologies account for approximately 92% of total production, while CdTe PV represents the largest contributor to non-silicon based PV systems. Currently, the market for CdTe PV is still virtually dominated by a single producer, First Solar (Springerville, AZ, USA), with over 10 GW installed worldwide [5]. Generally, PV systems can be mounted on roof tops—commonly named building adapted photovoltaic (BAPV) systems, and they can be integrated into building facades or roofs—also referred to as building integrated photovoltaic (BIPV) systems, or they can be mounted on frames directly on the ground. There has been constant improvement in the material and energy efficiency of PV cells and panels [6–14]; therefore, an up-to-date estimate of the energy and environmental performance of PV technologies is of key importance for long-term energy strategy decisions. This paper provides such an update from both the life cycle assessment (LCA) and net energy analysis (NEA) perspectives for the main commercially relevant large-scale PV technologies as of today [3], namely: single-crystalline Si (sc-Si), multi-crystalline Si (mc-Si), CdTe, and CIGS.

2. Methodology

2.1. Life Cycle Assessment LCA is a discipline widely used in the scientific community and it is considered to be the most comprehensive approach to assessing the environmental impact and overall efficiency of a product or a system throughout all stages of its life cycle. LCA takes into account a product’s full life cycle from the extraction of resources and the production of raw materials, to manufacturing, distribution, use and re-use, maintenance, and finally recycling and disposal of the final product—including all transportation and use of energy carriers. Since its inception and first standardization by the society of environmental toxicology and chemistry (SETAC) [15], LCA has become more and more complex, eventually leading to International Organization for Standardization (ISO) Standards 14040 and 14044 [16,17]. The latter are followed here, as well as the more PV-specific guidelines provided by the International Energy Agency (IEA) [18]. Besides addressing a number of environmental impact categories, such as global warming, ozone depletion, and acidification, LCA also allows the calculation of the total primary energy (PE) harvested from the environment in order to produce a given amount of end product (i.e., electricity in the case of PV), commonly named cumulative energy demand (CED)[19]. In the case of a PV system, the CED is thus defined as:

CED “ pPE ` Invq{Outel (1) where PE is the primary energy (sunlight) directly harvested from nature by the PV system and converted into electricity over its entire lifetime; Inv is the additional PE indirectly “invested” in order to produce, deploy, maintain, and decommission the PV system; Outel is the total energy output over the PV system’s lifetime, in units of electricity. Energies 2016, 9, 622 3 of 13

The main indication provided by the CED is related to the system’s efﬁciency in using PE resources. However, consistent with LCA’s long-term focus, the CED makes no differentiation between the energy that is directly extracted, delivered, and transformed (PE) and the energy that needs to be invested in order to do so (Inv).

2.2. Net Energy Analysis NEA offers an alternative point of view on the performance of energy production systems such as PVs: it evaluates how effective (as contrasted to efﬁcient) a system is at exploiting PE resources and converting them into usable energy carriers. In other words, the purpose of NEA is to quantify the extent to which a given system or process is able to provide a positive energy surplus to the end user, also referred to as net energy gain (NEG), after accounting for all the energy losses occurring along process chains (such as extraction, transformation, delivery, and others) as well as for all the additional energy investments that are required in order to carry out the same chain of processes [20–26]. The principle metric of NEA is the energy return on investment (EROI), which is calculated as the ratio of the energy delivered to society to the sum of energy carriers diverted from other societal uses. Speciﬁcally, for a PV system [27], and using the same nomenclature as in Equation (1):

EROIel “ Outel{Inv (2) also:

EROIPE-eq “ OutPE-eq{Inv “ pOutel{ηGq{Inv (3) where OutPE-eq is the energy delivered to society in units of equivalent PE; ηG is the life cycle energy efﬁciency of the electricity grid of the country or region where the analysed PV system is deployed (calculated as the ratio of the yearly electricity output of the entire grid to the total PE harvested from the environment for the operation of the grid in the same year). At the very minimum, the EROIPE-eq of an electricity production system must be higher than 1, i.e., the system must ensure the provision of a positive net energy gain (NEG) to the end user:

NEG “ OutPE-eq ´ Inv (4) In fact, it is actually important that the system has a sufficiently large EROI, beyond unity. In other words, EROIPE-eq > 1 (implying NEG > 0) is a necessary but not sufficient condition, given that the purpose of an electricity production system is to contribute to the support of the entire energy metabolism of a modern society, and not just to provide enough net energy to support itself [28–30]. The accurate quantification of the minimum EROIPE-eq that makes a technology viable depends on a number of factors related to the energy supply mix for each country considered, and is beyond the scope of this paper. In any case, it is important to keep in mind the all-important non-linear relation of EROIPE-eq to the actual ratio of net–to–gross (NTG) energy output:

NTG “ pOutPE-eq ´ Invq{OutPE-eq “ pEROIPE-eq ´ 1q{EROIPE-eq (5)

The energy pay back time (EPBT) is also calculated for each PV technology considered. EPBT measures how many years it takes for the PV system to return an amount of electricity that is considered to be equivalent to the PE invested. In other words, the EPBT is the time after which the system is able to provide a positive NEG. Operationally:

EPBT “ Inv{rpOutel{Tq{ηGqs “ T{EROIPE-eq (6) where T is the lifetime of the PV system, measured in years. In this paper, the calculations of EROIPE-eq and EPBT are based on a generalized average grid mix efficiency (ηG « 0.30), assuming a common grid mix largely reliant on thermal technologies. This is in order to provide sufficiently generic information and to ensure that the comparison of all the analysed Energies 2016, 9, 622 4 of 13 technologies is consistent both internally and externally with most other literature reviews. In other words, this means that the two metrics (EROIPE-eq and EPBT) do not refer to any specific country with its own electricity grid mix, but to a theoretical average representative mix, and that in order to be strictly applicable to a specific country, their values would have to be adapted based on the real life-cycle efficiency of its grid.

2.3. Data Sources and Scope In order to carry out the analysis in the most consistent way possible, all the performance indicators were calculated based on the same underlying inventory data. The main background data source was the Ecoinvent V3.1 Database (Ecoinvent, Zurich, Switzerland) [31]; whenever needed, the data were adapted to the actual production conditions in order to be as accurate and realistic as possible. In particular, the latest electricity generation mixes of the countries of production were used. Regarding the foreground inventory, all the outputs were estimated based on the latest available data. For CdTe PV, the most up-to-date production data were provided directly by First Solar, who also provided information on the balance of system (BOS) for typical ground-mounted installations (this same installation type was extended to apply to all other technologies too). For c-Si PV and CIGS technologies, the inventory data source was the latest IEA-photovoltaic power systems (PVPS) Task 12 Report [32]. In particular, the latter refers to a literature study published in 2014 but reporting data from 2011 [33]. This means that the original inventory database used for our c-Si analysis is ultimately not very recent—but it is still the most up to date reliable source of information available. Also, in our analysis, the efficiencies of all the PV technologies as well as the electric mixtures used in the Si supply chain and for PV module production (Section 3.2) have been updated to reflect the current (2015) situation. End of life (EOL) management and decommissioning of the PV systems were not included in this work because these depend of a number of factors and specific conditions, such as the exact location of the PV plant, the type of PV panel, transport costs, logistic criteria, production quantities, weight per Wp, and others [34]—and making specific assumptions in this regard would not be consistent with the aim of the paper to provide an average worldwide high-level point of view. However, including EOL stages may in fact not result in a worsening of the overall energy and environmental performance, since the recycling of the PV components can often provide environmental and economic benefits, especially for c-Si PV panels, given the high value of recycled aluminium and silicon [35]. The contribution of energy storage is likewise not included in our analyses. First, since the main focus is on a high-level comparison between a range of different PV technologies—not an analysis of specific countries and particular locations—energy storage is beyond the scope of this paper. Secondly, many electricity production technologies, including but not limited to PVs, are unable to single-handedly follow the dynamics of societal electricity demand. Hence, energy storage deployment is required at grid level—rather than for each electricity generation technology taken in isolation [36]. Thirdly, even when performing an analysis at grid level, it is recommended to take into account the smoothing effect produced by the combination of renewable energy sources, such as PV and wind [37]. Finally, from a practical standpoint, the analysis was performed using the LCA software package SimaPro 8 (Pré Consultants, Amersfoort, The Netherlands) [38]—and impact assessment was performed by means of the CML method developed by Leiden University in the Netherlands [39].

3. System Descriptions

3.1. Photovoltaic System Process Stages The PV systems analysed are composed of PV panels and BOS (mechanical and electrical components such as inverters, transformers, and cables, as well as system operation and maintenance). The PV panel technologies considered are: sc-Si, mc-Si, CdTe, and CIGS. In particular, with regard to c-Si manufacturing, there are more steps to arrive at the ﬁnal product in comparison with thin-ﬁlm PVs (CdTe and CIGS), and a comparatively large amount of energy is required for the production of crystalline silicon [10,31]. Energies 2016, 9, 622 5 of 13

Figures1 and2 show the respective flow diagrams for the c-Si and thin film PV systems. In particular, Figure1 illustrates each step of the manufacturing chain for sc-Si and mc-Si PV panels. AfterEnergies the metallurgical 2016, 9, 622 (MG) and solar grade (SoG) Si production stages, mc-Si ingots are5 of cast 13 and sawnEnergies into wafers: 2016, 9, 622 sc-Si PV cells additionally require an intermediate Czochralski (CZ) recrystallization5 of 13 step.sawn Then, into the individualwafers: sc PV‐Si cellsPV arecells encapsulated additionally betweenrequire glassan intermediate panes and assembledCzochralski into (CZ) framed sawnrecrystallization into wafers: step. scThen,‐Si PV the cellsindividual additionally PV cells require are encapsulated an intermediate between Czochralski glass panes (CZ)and PV panels, and finally the PV system is completed by the addition of the BOS. In contrast, Figure2 assembledrecrystallization into framed step. Then, PV panels, the individual and finally PV the cells PV aresystem encapsulated is completed between by the glass addition panes of andthe showsassembledBOS. that In the contrast, simplerinto framed Figure flow PV 2 diagrams shows panels, that and for the finally CdTe simpler andthe flow PV CIGS systemdiagrams technologies. is completedfor CdTe Incidentally, and by theCIGS addition technologies. the thin of the film PV panelsIncidentally,BOS. are In also contrast, glass-glass the thin Figure film sandwiches, 2 PV shows panels that are but the also devoidsimpler glass‐ glass offlow metal sandwiches,diagrams frames. for but CdTe devoid and ofCIGS metal technologies. frames. Incidentally, the thin film PV panels are also glass‐glass sandwiches, but devoid of metal frames.

Figure 1. Flow diagram for single‐crystalline Si (sc‐Si) and multi‐crystalline Si (mc‐Si) photovoltaic Figure 1. Flow diagram for single-crystalline Si (sc-Si) and multi-crystalline Si (mc-Si) photovoltaic Figure(PV) systems. 1. Flow SoG: diagram solar forgrade; single and‐crystalline CZ: Czochralski. Si (sc‐Si) and multi‐crystalline Si (mc‐Si) photovoltaic (PV) systems. SoG: solar grade; and CZ: Czochralski. (PV) systems. SoG: solar grade; and CZ: Czochralski.

Figure 2. Flow diagram for cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS) FigurePV systems. 2. Flow BOS: diagram balance for of cadmium system telluride (CdTe) and copper indium gallium diselenide (CIGS) Figure 2. Flow diagram for cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS) PV systems. BOS: balance of system PV systems. BOS: balance of system. 3.2. Production Sites and Electricity Mixes 3.2. Production Sites and Electricity Mixes 3.2. ProductionEach analysed Sites and PV Electricity system is Mixes also classified by country of production. The c‐Si PV production chainEach is classified analysed into PV three system main is alsoproducing classified regions: by country Europe, of China, production. and the The USA, c‐Si according PV production to the Eachdatachain source analysedis classified used PV [32].into system threeThe sc main is‐Si also and producing classifiedmc‐Si wafers regions: by used country Europe, in Chinese of China, production. PV and manufacturing the USA, The according c-Si are PV entirely production to the chaindatasourced is classified source domestically; used into [32]. three ofThe those main sc‐Si used producing and in mc US‐Si PV wafers regions: manufacturing, used Europe, in Chinese 66% China, are PV produced and manufacturing the USA, in China according are and entirely 34% to the datasourceddomestically; source useddomestically; and [32 ].for The those of those sc-Si used used and in European mc-Siin US PV wafers PV manufacturing, manufacturing, used in Chinese 66% 89% are is PV produced manufacturing locallyin China and and are 11% 34% entirely in sourceddomestically;China. domestically; Regarding and forCdTe of those those PV used panels, used in European in the US two PV productionPV manufacturing, manufacturing, countries 66%89% as is areof produced 2016 produced are locallyMalaysia in Chinaand and 11% andthe in 34% domestically;USA,China. in Regarding accordance and for CdTe those with PV the used panels, data in provided European the two byproduction PV the manufacturing, leading countries company as 89% inof this 2016 is producedsector are Malaysia (First locally Solar). and andThethe 11% in China.USA,main productionin Regarding accordance countries CdTe with the PV for data panels, CIGS provided PV the are two Japanby the production (Solar leading Frontier) company countries [40], in to this aswhich sector of 2016 our (First analysis are Solar). Malaysia refers, The and main production countries for CIGS PV are Japan (Solar Frontier) [40], to which our analysis refers, the USA,and China in accordance (Hanergy). with All further the data upstream provided steps by in the the leading Si supply company chain are in analysed this sector considering (First Solar). andtheir China actual (Hanergy).geographical All location—for further upstream instance, steps the in production the Si supply of MG chain‐Si is are divided analysed among considering the main The main production countries for CIGS PV are Japan (Solar Frontier) [40], to which our analysis refers, globaltheir actual producers, geographical i.e., China, location—for Russia, Norway instance, and the the production United States of MG [41].‐Si is divided among the main and ChinaglobalThe (Hanergy).producers, individual i.e., All local China, further updated Russia, upstream electricity Norway steps mixesand in the the used United Si for supply Statesall PV chain [41].module are analysedmanufacturing considering and for their actualthe geographical SiThe supplying individual location—forcountries local updated are also instance, consideredelectricity the productionmixes in our used analysis, for of MG-Siall since PV theymodule is divided influence manufacturing among the amount the and main of forPE global producers,theultimately Si supplying i.e., required China, countries Russia, for each are Norway production also considered and process, the in United our as analysis,well States as the [since41 ].associated they influence environmental the amount impacts of PE Theultimately(Norwegian individual required and localJapanese for updated each data production from electricity the process, IEA mixes [42]; as usedChinesewell as for theand all associated PVUSA module data environmental from manufacturing the U.S. impactsEnergy and for the Si(NorwegianInformation supplying Administrationand countries Japanese are data (EIA) also from [43]; considered the Russian IEA [42]; inand ourChinese European analysis, and data USA since from data they the from World influence the BankU.S. the Energy(world amount of PEInformationultimately Administration required for (EIA) each production[43]; Russian process,and European as well data as from the the associated World Bank environmental (world impacts (Norwegian and Japanese data from the IEA [42]; Chinese and USA data from the U.S.

Energies 2016, 9, 622 6 of 13

EnergyEnergies Information 2016, 9, 622 Administration (EIA) [43]; Russian and European data from the World6 of 13 Bank (worldEnergies development 2016, 9, 622 indicators) [44]; Malaysian data from the Peninsular Malaysia electricity6 of supply 13 industrydevelopment outlook indicators) [45].) [44]; Malaysian data from the Peninsular Malaysia electricity supply industrydevelopment outlook indicators) [45].) [44]; Malaysian data from the Peninsular Malaysia electricity supply 4. Resultsindustry and outlook Discussion [45].) 4. Results and Discussion 4.1.4. Fixed-Tilt Results Ground-Mountedand Discussion Photovoltaic Systems 4.1. Fixed‐Tilt Ground‐Mounted Photovoltaic Systems 4.1.Figure Fixed3‐ Tiltshows Ground the‐ CEDMounted of thePhotovoltaic analysed Systems PV systems, while Figures4–6 illustrate the respective LCA impactFigure indicators, 3 shows the namelyCED of the global analysed warming PV systems, potential while (GWP), Figures 4–6 acidification illustrate the potential respective (AP), LCA Figureimpact 3 indicators,shows the CEDnamely of theglobal analysed warming PV systems,potential while (GWP), Figures acidification 4–6 illustrate potential the respective(AP), and and ozone depletion potential (ODP), all expressed per kWp—the stacked bars show the individual ozoneLCA impact depletion indicators, potential namely (ODP), global all expressedwarming potentialper kWp —the(GWP), stacked acidification bars show potential the individual (AP), and contributions of the main life cycle stages. Each PV technology is also shown separately according contributionsozone depletion of the potential main life (ODP), cycle stages.all expressed Each PV per technology kWp—the is alsostacked shown bars separately show the according individual to to the country or region in which it was manufactured. The average efficiency for each technology is thecontributions country or of region the main in which life cycle it was stages. manufactured. Each PV technology The average is also efficiency shown separately for each technology according tois assumedassumedthe country in accordance in oraccordance region with in whichwith the latest itthe was reportlatest manufactured. report by the Fraunhoferby Thethe averageFraunhofer Institute efficiency Institute for Solar for eachfor Energy Solartechnology Systems Energy is [ 40], specifically:Systemsassumed [40], 17%in specifically:accordance for sc-Si PV, 17%with 16% for the for sc ‐ mc-Si,Silatest PV, 16%report 15.6% for for bymc ‐ CdTetheSi, 15.6% Fraunhofer PV, for and CdTe 14% Institute PV, for and CIGS for14% PV. Solar for CIGS Energy PV. Systems [40], specifically: 17% for sc‐Si PV, 16% for mc‐Si, 15.6% for CdTe PV, and 14% for CIGS PV. EUUS CN EU US CN MY US JP 30,000 EUUS CN EU US CN MY US JP 30,000 BOS 25,000 BOS 25,000 p 20,000

p PV panel /kW 20,000 PE PV panel /kW

MJ PE 15,000 MJ 15,000 PV cell PV cell 10,000 10,000 SoG‐Si 5,000 SoG‐Si 5,000

0 0 sc‐Si PV multi‐Si PV CdTe PV CIGS PV sc‐Si PV multi‐Si PV CdTe PV CIGS PV Figure 3. Cumulative energy demand (CED) per kWp of the analysed PV systems. Figure 3. Cumulative energy demand (CED) per kWp of the analysed PV systems. Figure 3. Cumulative energy demand (CED) per kWp of the analysed PV systems. EUUS CN EU US CN MY US JP 2,000 EUUS CN EU US CN MY US JP 2,000 1,800 BOS 1,800 1,600 BOS 1,600 1,400 kWp

PV panel /

1,400

kWp 1,200

PV panel eq) /

‐

2 1,200 eq)

‐ 1,000

(CO 2

kg 1,000 PV cell (CO 800

kg PV cell 800 600 600 400 SoG‐Si 400 SoG‐Si 200 200 0 0 sc‐Si PV multi‐Si PV CdTe PV CIGS PV sc‐Si PV multi‐Si PV CdTe PV CIGS PV Figure 4. Global warming potential (GWP) per kWp of the analysed PV systems. Figure 4. Global warming potential (GWP) per kWp of the analysed PV systems. Figure 4. Global warming potential (GWP) per kWp of the analysed PV systems.

Energies 2016, 9, 622 7 of 13 Energies 2016, 9, 622 7 of 13 Energies 2016, 9, 622 7 of 13 EUUS CN EU US CN MY US JP 20 EUUS CN EU US CN MY US JP 20 18 BOS 18 BOS 16 16 14 kWp PV panel / 14

kWp 12 PV panel / eq)

‐

2 12 eq) ‐ 10 2 (SO

kg 10 (SO

PV cell 8 kg PV cell 8 6 6 4 SoG‐Si 4 SoG‐Si 2 2 0 0 sc‐Si PV multi‐Si PV CdTe PV CIGS PV sc‐Si PV multi‐Si PV CdTe PV CIGS PV Figure 5. Acidification potential (AP) per kWp of the analysed PV systems. Figure 5. Acidiﬁcation potential (AP) per kW of the analysed PV systems. Figure 5. Acidification potential (AP) per kWpp of the analysed PV systems. EUUS CN EU US CN MY US JP 3.5E‐04 EUUS CN EU US CN MY US JP 3.5E‐04 BOS 3.0E‐04 BOS 3.0E‐04

2.5E‐04 2.5E‐04 PV panel eq

PV panel 2.0E‐04 11 eq ‐ 2.0E‐04 11 ‐ CFC

CFC 1.5E‐04 PV cell

kg 1.5E‐04 PV cell

1.0E‐04 1.0E‐04 SoG‐Si 5.0E‐05 SoG‐Si 5.0E‐05

0.0E+00 0.0E+00 sc‐Si PV multi‐Si PV CdTe PV CIGS PV sc‐Si PV multi‐Si PV CdTe PV CIGS PV Figure 6. Ozone depletion potential (ODP) per kWp of the analysed PV systems. Figure 6. Ozone depletion potential (ODP) per kWp of the analysed PV systems. Figure 6. Ozone depletion potential (ODP) per kWp of the analysed PV systems. The results clearly show that the most impacting step for c‐Si technologies is from SoG‐Si supply to finishedThe results PV cells, clearly which show includes that the ingot/crystal most impacting growth step and for wafer c‐Si technologiesand cell production, is from andSoG ‐especiallySi supply The results clearly show that the most impacting step for c-Si technologies is from SoG-Si supply soto finishedin the case PV of cells, sc‐Si which PV systems includes (because ingot/crystal of the energygrowth intensive and wafer CZ and crystal cell production, growth process). and especially to ﬁnished PV cells, which includes ingot/crystal growth and wafer and cell production, and especially so inFigure the case 3 ofhighlights sc‐Si PV systemsthat, per (because kWp, c‐ ofSi thePV energysystems intensive are overall CZ crystaltwice asgrowth energy process).‐demanding to p so inproduce the caseFigure as of CdTe3 sc-Si highlights PVPV systemssystems. that, per (becauseFigure kW ,4 c ‐illustrates ofSi thePV systems energy the resulting intensiveare overall GWP CZ twice crystalindicator as energy growth per‐ demandingkW process).p: c‐Si PV to Figuretechnologiesproduce3 highlightsas CdTe generally PV that, systems.have per higher kW Figurep values, c-Si 4 PVillustrates in systemscomparison the are resulting overallwith thin twice GWP film asPV indicator energy-demanding panels, perand kWin particular,p: c‐ toSi producePV technologies generally have higher values in comparison with thin film PV panels, and in particular, as CdTethe lowest PV systems. GWP values Figure are4 illustrates for CdTe PV, the especially resulting GWPwhen indicatorproduction per takes kW placep: c-Si in Malaysia. PV technologies A the lowest GWP values are for CdTe PV, especially when production takes place in Malaysia. A generallysimilar have trend higher is shown values in Figure in comparison 5, in which with the thin lower film values PV panels, of AP per and kW inp particular,are those for the CdTe lowest PV, GWP similar trend is shown in Figure 5, in which the lower values of AP per kWp are those for CdTe PV, valuesand are secondly for CdTe for PV, CIGS especially PV; conversely, when productionsc‐Si PV shows takes the place highest in AP Malaysia. values, followed A similar by trend mc‐Si is PV. shown Alsoand secondlyin terms forof ODPCIGS results PV; conversely, (Figure 6), sc CdTe‐Si PV PV shows is still the the highest best performer,AP values, followedfollowed by CIGSmc‐Si PV,PV. in Figure5, in which the lower values of AP per kW p are those for CdTe PV, and secondly for CIGS PV; andAlso then in terms mc‐Si of and ODP sc‐ Siresults PV. (Figure 6), CdTe PV is still the best performer, followed by CIGS PV, conversely, sc-Si PV shows the highest AP values, followed by mc-Si PV. Also in terms of ODP results and thenThese mc new‐Si andresults sc‐Si show PV. a remarkable improvement for current production CdTe PV modules (Figure6), CdTe PV is still the best performer, followed by CIGS PV, and then mc-Si and sc-Si PV. whenThese compared new resultsto similar show modules a remarkable produced improvement in 2005 (the for most current recent production production CdTe year PV for modules which TheseCdTewhen PVcompared new inventory results to datasimilar show are a modulesdirectly remarkable available produced improvement in in the 2005 Ecoinvent (the for most V3.1 current recent Database). production production Over one CdTeyear decade, for PV which modules the whenCEDCdTe compared per PV kW inventory top for similar the data CdTe modules are PV directly modules produced available manufactured in in 2005 the Ecoinvent (the in the most US V3.1 recent has Database).been production reduced Over by year one approximately decade, for which the CdTe PV inventory62%,CED whileper kW data thep for areGWP, the directly CdTe ODP, PV and available modules AP results in manufactured the are Ecoinvent also down in the V3.1 by US respectively Database). has been reduced 63%, Over 65%, oneby approximatelyand decade, 71%. The the CED 62%, while the GWP, ODP, and AP results are also down by respectively 63%, 65%, and 71%. The per kW p for the CdTe PV modules manufactured in the US has been reduced by approximately 62%, while the GWP, ODP, and AP results are also down by respectively 63%, 65%, and 71%. The current CdTe PV systems also show improvements when compared to previously published results [46] referring to more recent (2010–2011) production data; in this case the CED is down by approximately 30%, and the GWP is down by 37%. Energies 2016, 9, 622 8 of 13

It is noted, however, that the CED of complete ground-mounted CdTe PV systems are not much lower than previously reported values, because the new inventory data for the ground-mounted BOS provided by First Solar led to a higher energy demand (831 MJ/m2) than the previously used data from the c-Si PV BOS (542 MJ/m2, First Solar) [47]. The same also applies to the calculated EPBT values (Table1). Energies 2016, 9, 622 8 of 13 Table 1. Energy pay-back time (EPBT) of the analysed PV systems (mean values for the various currentproduction CdTe sites), PV systems corresponding also show to the improvements three considered when irradiation compared levels. to previously published results [46] referring to more recent (2010–2011) production data; in this case the CED is down by approximatelyIrradiation 30%, and and Grid the GWP Efficiency is down (η) by sc-Si37%. PV mc-Si PV CdTe PV CIGS PV It is noted,1000 however, kWh/(m that2ÿr); theη = CED 0.3 of complete2.8 ground‐mounted 2.1 CdTe 1.1 PV systems 1.9 are not much lower than previously1700 kWh/(m reported2ÿr); η =values, 0.3 because1.6 the new inventory 1.2 data 0.6 for the ground 1.1 ‐mounted 2 BOS provided2300 by kWh/(m First Solarÿr); ledη =to 0.3 a higher energy1.2 demand 0.9(831 MJ/m2) 0.5 than the previously 0.8 used data from the c‐Si PV BOS (542 MJ/m2, First Solar) [47]. The same also applies to the calculated EPBT valuesFrom (Table a geographical 1). perspective, it is also clear from the results that the considered impact indicatorsFrom (GWP, a geographical AP, ODP) perspective, are generally it loweris also whenclear from the manufacturing the results that takesthe considered place in Europe impact in comparisonindicators with(GWP, the AP, USA ODP) and are China, generally and lower in particular when the the manufacturing Chinese production takes place chain in consistentlyEurope in showscomparison the highest with indicatorthe USA and values. China, This and is despitein particular the fact the thatChinese the CEDproduction associated chain to consistently the Chinese c-Sishows PV production the highest isindicator actually values. slightly This lower is despite than thatthe fact for that the Europeanthe CED associated and USA to manufacturing the Chinese chains—thisc‐Si PV production seeming is incongruence actually slightly depends lower onthan the that large for reliancethe European of the and Chinese USA manufacturing electric grid on coalchains [43]. – The this input seeming grid incongruence mix composition depends is also on the responsible large reliance for aof significant the Chinese share electric of the grid impacts on coal in the[43]. case The of CIGS input PV grid produced mix composition in Japan (ais also country responsible where, afterfor a thesignificant 2011 nuclear share incidentof the impacts in Fukushima, in the overcase 90% of CIGS of the PV energy produced resources in Japan used (a for country electricity where, generation after the 2011 are fossil nuclear fuels incident [42]). in Fukushima, over 90% of the energy resources used for electricity generation are fossil fuels [42]). The BOS contribution is generally fairly low, with the partial exception of the AP results, which are The BOS contribution is generally fairly low, with the partial exception of the AP results, which negatively affected by the comparatively large amounts of copper and aluminium required. are negatively affected by the comparatively large amounts of copper and aluminium required. Figures7–10 then illustrate the same results (CED, GWP, AP and ODP) expressed per kWh el. Figures 7–10 then illustrate the same results (CED, GWP, AP and ODP) expressed per kWhel. These results are computed assuming a performance ratio of 0.8 and a lifetime of 30 years [18]. These results are computed assuming a performance ratio of 0.8 and a lifetime of 30 years [18]. Also, Also, in order to provide results applicable to different contexts, three different irradiation levels are in order to provide results applicable to different contexts, three different irradiation levels are used, used,which which are arerespectively respectively representative representative of irradiation of irradiation on ona south a south-facing,‐facing, latitude latitude-tilted‐tilted plane plane in in 2 2 Central-NorthernCentral‐Northern Europe Europe (1000 (1000 kWh/(m kWh/(m2¨∙yr)),yr)), Central-SouthernCentral‐Southern Europe Europe (1700 (1700 kWh/(m kWh/(m2∙yr)),ÿr)), and and the the 2 SouthwesternSouthwestern United United States States (2300 (2300 kWh/(m kWh/(mÿr)).2∙yr)). In theIn figures,the figures, different different symbol symbol sizes (small,sizes (small, medium, andmedium, large, respectively) and large, respectively) are used to are refer used to theseto refer three to these specific three irradiation specific irradiation levels. levels.

EU US CN EU US CN MY US JP 5.0

el 4.5 /kWh

PE MJ

4.0

3.5

sc‐Si PV mc‐Si PV CdTe PV CIGS PV

Figure 7. CED per kWhel of the analysed PV systems, under three irradiation levels. Small symbols: Figure 7. CED per kWhel of the analysed PV systems, under three irradiation levels. Small symbols: 1000 kWh/(m2∙yr); medium symbols: 1700 kWh/(m2∙yr); and large symbols: 2300 kWh/(m2∙yr). 1000 kWh/(m2ÿr); medium symbols: 1700 kWh/(m2ÿr); and large symbols: 2300 kWh/(m2ÿr). Unsurprisingly, the best energy and environmental performance as measured by all considered metricsUnsurprisingly, is that of CdTe the PV best systems energy installed and environmental in the Southwestern performance US, with as measuredCIGS PV as by a close all considered second. metricsAt the is other that ofend CdTe of the PV scale, systems the highest installed impact in the in Southwestern terms of GWP US, and with AP CIGSare those PV asfor a the close Chinese second. produced sc‐Si PV, mainly due to this technology’s higher demand for input electricity, coupled with the prominence of coal in the Chinese electricity grid mix.

Energies 2016, 9, 622 9 of 13

At the other end of the scale, the highest impact in terms of GWP and AP are those for the Chinese produced sc-Si PV, mainly due to this technology’s higher demand for input electricity, coupled with the prominence of coal in the Chinese electricity grid mix. Energies 2016, 9, 622 9 of 13 Energies 2016, 9, 622 9 of 13 EU US CN EU US CN MY US JP Energies 2016, 9, 622 100 9 of 13 EU US CN EU US CN MY US JP 10090 EU US CN EU US CN MY US JP 100 8090 90 el 7080 kWh el 8070 /

60 kWh

el eq) ‐ / 70

2 50 kWh eq)

‐ (CO

2 6050 g 40 eq) (CO ‐

g 50 3040 (CO

g 40 2030 30 1020 20 100

100 sc‐Si PV mc‐Si PV CdTe PV CIGS PV 0 sc‐Si PV mc‐Si PV CdTe PV CIGS PV Figure 8. GWP per kWhel of the analysed PV systems, under three irradiation levels. Small symbols: Figure 8. GWP per kWhel of the analysedsc‐Si PV PV systems, mc‐Si PVunder threeCdTe irradiation PV CIGS PV levels. Small symbols: Figure 8. GWP2 per kWhel of the analysed PV systems,2 under three irradiation levels. Small2 symbols: 1000 kWh/(m2 ∙yr); medium symbols: 1700 kWh/(m ∙yr);2 and large symbols: 2300 kWh/(m ∙yr). 2 1000 kWh/(m ÿr);2 medium symbols: 1700 kWh/(m2 ÿr); and large symbols: 2300 kWh/(m2 ÿr). Figure1000 kWh/(m 8. GWP∙yr); per medium kWhel of symbols: the analysed 1700 PVkWh/(m systems,∙yr); under and large three symbols: irradiation 2300 levels. kWh/(m Small∙yr). symbols: 2 EU US CN EU2 US CN MY US JP 2 1000 kWh/(m ∙yr); medium1.0 symbols: 1700 kWh/(m ∙yr); and large symbols: 2300 kWh/(m ∙yr). EU US CN EU US CN MY US JP 1.0 EU US CN EU US CN MY US JP 1.0 0.8

el 0.8 kWh el

0.8

/ 0.6

kWh

el eq) ‐ /

0.6

2 kWh eq)

‐ (SO

/ 0.6

g 0.4 eq) (SO ‐

2 g 0.4 (SO

g 0.4 0.2

0.2

0.2 0.0

0.0 sc‐Si PV mc‐Si PV CdTe PV CIGS PV 0.0 sc‐Si PV mc‐Si PV CdTe PV CIGS PV Figure 9. AP per kWhel of the analysed PV systems, under three irradiation levels. Small symbols: sc‐Si PV mc‐Si PV CdTe PV CIGS PV 1000Figure kWh/(m 9. AP 2per∙yr); kWh mediumel of thesymbols: analysed 1700 PV kWh/(m systems,2∙yr); under and largethree symbols: irradiation 2300 levels. kWh/(m Small2∙yr). symbols: Figure 9. AP per2 kWhel of the analysed PV systems,2 under three irradiation levels. Small2 symbols: 1000 kWh/(m ∙yr); mediumel symbols: 1700 kWh/(m ∙yr); and large symbols: 2300 kWh/(m ∙yr). Figure 9. AP2 per kWh of the analysed PV systems,2 under three irradiation levels. Small symbols:2 1000 kWh/(m ÿr); mediumEU symbols: US 1700 CN kWh/(m EU USÿr); and CN large MY symbols: US 2300 JP kWh/(m ÿr). 1000 kWh/(m2∙yr); medium symbols: 1700 kWh/(m2∙yr); and large symbols: 2300 kWh/(m2∙yr). 8 EU US CN EU US CN MY US JP 8 7 EU US CN EU US CN MY US JP 8 7 6 7 6 eq 5 11 ‐

eq 6 5 CFC 11

‐ 4 eq

µg 5 CFC

11 4 ‐ 3 µg CFC

4 3 µg 2 3 2 1 2 1 0 1 0 sc‐Si PV mc‐Si PV CdTe PV CIGS PV 0 sc‐Si PV mc‐Si PV CdTe PV CIGS PV Figure 10. ODP per kWhel of the analysed PV systems, under three irradiation levels. Small symbols: sc‐Si PV mc‐Si PV CdTe PV CIGS PV 1000Figure kWh/(m 10. ODP2∙yr); per medium kWhel of symbols: the analysed 1700 kWh/(mPV systems,2∙yr); under and large three symbols: irradiation 2300 levels. kWh/(m Small2∙yr). symbols: 2 2 2 Figure1000 kWh/(m 10. ODP∙yr); per medium kWhel of symbols: the analysed 1700 PVkWh/(m systems,∙yr); under and large three symbols: irradiation 2300 levels. kWh/(m Small∙yr). symbols: Figure 10. ODP per kWh of the analysed PV systems, under three irradiation levels. Small symbols: 1000As illustrated kWh/(m2∙yr); in Tablemediumel 1, thesymbols: energy 1700 pay kWh/(m‐back 2times∙yr); and of thelarge analysed symbols: PV 2300 technologies kWh/(m2∙yr). were found 2¨ 2¨ 2¨ to1000 rangeAs kWh/(m illustrated from 6 monthsyr); in medium Table (for 1,CdTe symbols: the energy PV installed 1700 pay kWh/(m‐back in the times USyr); Southof and the large‐ analysedWest) symbols: to approximately PV technologies 2300 kWh/(m 2–3 were yearsyr). found (for cto‐Si range PVAs installedillustrated from 6 months in in Central Table (for ‐1, NorthernCdTe the energy PV installedEurope). pay‐back in the times US Southof the ‐analysedWest) to approximatelyPV technologies 2–3 were years found (for to c‐Si range PV installed from 6 months in Central (for‐ NorthernCdTe PV installedEurope). in the US South‐West) to approximately 2–3 years (for c ‐Si PV installed in Central‐Northern Europe).

Energies 2016, 9, 622 10 of 13

Table 1. Energy pay‐back time (EPBT) of the analysed PV systems (mean values for the various

Energiesproduction2016, 9, 622 sites), corresponding to the three considered irradiation levels. 10 of 13 Irradiation and Grid Efficiency (η) sc‐Si PV mc‐Si PV CdTe PV CIGS PV 1000 kWh/(m2∙yr); η = 0.3 2.8 2.1 1.1 1.9 As illustrated in Table1, the energy pay-back times of the analysed PV technologies were found to 1700 kWh/(m2∙yr); η = 0.3 1.6 1.2 0.6 1.1 range from 62300 months kWh/(m (for2∙yr); CdTe η = PV 0.3 installed in the1.2 US South-West)0.9 to approximately0.5 2–3 years0.8 (for c-Si PV installed in Central-Northern Europe). Figure 11 illustrates the the positioning of the the analysed PV systems along the the curve defined defined by the non-linear relation of EROI to NTG (often referred to as the “net energy cliff” [48]). This figure non‐linear relation of EROIPE‐eq-eq to NTG (often referred to as the “net energy cliff” [48]). This figure makes it abundantly clear that, while the individual EROI values for the different PV systems makes it abundantly clear that, while the individual EROIPEPE‐-eqeq values for the different PV systems over the three consideredconsidered irradiationirradiation levels levels span span a a comparatively comparatively large large range—from range—from ~10 ~10 for for sc-Si sc‐Si PV PV at 2 2 at1000 1000 kWh/(m kWh/(mÿr)2∙yr) to to ~60 ~60 for for CdTe CdTe PV PV at at 2300 2300 kWh/(m kWh/(m2¨∙yr)—in fact, all data points sit on what may may be consideredconsidered thethe “safe”, “safe”, quasi-horizontal quasi‐horizontal portion portion of theof the “cliff”. “cliff”. In other In other words, words, all PV all systems PV systems afford affordthe benefit the benefit of over of 90% over of 90% their of grosstheir gross energy energy output output being being available available as net as usable net usable energy energy to the to endthe enduser user (NTG (NTG> 0.9). > 0.9).

1.0

0.9

0.8

0.7

0.6

0.5 NTG

0.4

0.3

0.2

0.1

0.0 70 60 50 40 30 20 10 0

EROIPE‐eq Net Energy Cliff sc‐Si PV mc‐Si PV CdTe PV CIGS PV

Figure 11.11. PositioningPositioning of of the the analysed analysed PV systemsPV systems on the on “net the energy “net cliff”energy (illustrating cliff” (illustrating the non-linear the non‐linear relation of the net‐to‐gross energy output ratio to the energy return on investment relation of the net-to-gross energy output ratio to the energy return on investment (EROIPE-eq)), 2 (underEROIPE three‐eq)), irradiationunder three levels. irradiation Small symbols:levels. Small 1000 symbols: kWh/(m 10002ÿr); kWh/(m medium∙ symbols:yr); medium 1700 symbols: kWh/(m 21700ÿr); 2 2 kWh/(mand large∙yr); symbols: and large 2300 symbols: kWh/(m 23002ÿr). kWh/(m ∙yr).

4.2. A Comparison to 1‐Axis Tracking Installations 4.2. A Comparison to 1-Axis Tracking Installations Generally, tracking PV systems provide the benefit of boosting the energy yield in comparison Generally, tracking PV systems provide the benefit of boosting the energy yield in comparison with fixed‐tilt installations because the panels are mounted on a structure that follows the with fixed-tilt installations because the panels are mounted on a structure that follows the movement movement of the sun. In particular, one‐axis trackers have one degree of freedom (the movement of the sun. In particular, one-axis trackers have one degree of freedom (the movement occurs along occurs along a single axis of rotation). The results shown below correspond to a horizontal rotational a single axis of rotation). The results shown below correspond to a horizontal rotational axis in the axis in the North‐South (N‐S) direction with the panels facing East in the morning and facing West in North-South (N-S) direction with the panels facing East in the morning and facing West in the late the late afternoon. Tracking could be further optimized with the horizontal rotational axis tilted afternoon. Tracking could be further optimized with the horizontal rotational axis tilted south if the south if the topography allows, which would give the benefit of a flatter profile throughout the day. topography allows, which would give the benefit of a flatter profile throughout the day. On one hand, the invested energy (and associated environmental impacts) for building the On one hand, the invested energy (and associated environmental impacts) for building the tracking BOS are higher than for conventional fixed‐tilt PV systems, since tracking installations tracking BOS are higher than for conventional fixed-tilt PV systems, since tracking installations require require larger amounts of structural steel and copper cabling; also, they use electricity during the larger amounts of structural steel and copper cabling; also, they use electricity during the usage phase usage phase for tracking actuators. On the other hand, the key advantage of tracking systems is the for tracking actuators. On the other hand, the key advantage of tracking systems is the ability to ability to harvest more direct beam irradiance, thereby requiring fewer PV modules per kWh harvest more direct beam irradiance, thereby requiring fewer PV modules per kWh produced in produced in comparison with fixed‐tilt installations. comparison with fixed-tilt installations. The energy and environmental performance of tracking systems are highly influenced by site The energy and environmental performance of tracking systems are highly influenced by site latitude and diffused light conditions; in particular, sites with lower (<40%) diffused light benefit latitude and diffused light conditions; in particular, sites with lower (<40%) diffused light benefit more

Energies 2016, 9, 622 11 of 13 from tracking systems. Also, the gain in PV yield is reported to range from +10% to +24% over tropical and subtropical latitudes (0˝–40˝)[49]. Table2 shows the maximum achievable variations in LCA impact assessment results (GWP, AP, OPD) and EPBTs for a range of one-axis tracking PV systems, expressed as relative to the corresponding values for fixed-tilt PV installations, assuming a best-case scenario of 2300 kWh/(m2ÿr) irradiation, and +24% enhanced capture efficiency with respect to latitude tilt fixed installations.

Table 2. Life cycle impact assessment (LCIA) and EPBT results for one-axis tracking PV system 2 installations, per kWhel and relative to ﬁxed-tilt installations. Assumed irradiation: 2300 kWh/(m ¨yr); assumed energy harvesting gain due to tracking: +24%.

Indicator sc-Si PV mc-Si PV CdTe PV CIGS PV GWP ´14% ´11% ´1% ´6% AP ´12% ´9% ´7% ´16% ODP ´13% ´11% ´4% ´9% EPBT ´13.2% ´10.5% ´2.3% ´7.8%

In general terms, the c-Si PV systems were found to benefit the most from tracking installations (over ´10% impact). Instead, the advantage from tracking for CdTe PV (and also to a lesser extent for CIGS PV) appear to be much smaller, due to the very good performance of these thin film technologies in the first place, and hence the comparatively larger share of their overall impacts are due to the BOS itself.

5. Conclusions Overall, the ongoing improvements in terms of material usage for and energy efficiency of the range of commercially-available PV technologies have been shown to be paralleled by correspondingly better life-cycle energy and environmental performance. The most remarkable achievements have been obtained by CdTe PV, which can boast a two-thirds reduction in environmental impacts over the decade since its introduction to the market. Also importantly, our results definitively put to rest the often voiced concerns about PV not providing large-enough net energy returns per unit of energy invested: all analysed PV technologies have been shown to be able to afford a >90% net-to-gross energy return ratio, even when deployed in less-than-optimal locations (e.g. at Central-Northern latitudes). On the other hand, the additional benefit of employing a tracking BOS is not as clear-cut, and depends on the individual PV technology as well as on specific local conditions (high irradiation, low diffused light).

Acknowledgments: The authors gratefully acknowledge the supply of up-to-date inventory information on CdTe PV production by First Solar, Inc. Author Contributions: Vasilis Fthenakis conceived and designed the study; Enrica Leccisi performed the experimental work; Enrica Leccisi and Marco Raugei analyzed the data; Vasilis Fthenakis contributed materials and analysis insight; Enrica Leccisi and Marco Raugei wrote the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. Intergovernmental Panel on Climate Change (IPCC). Climate Change 2014: Mitigation of Climate Change; Cambridge University Press: New York, NY, USA, 2014. 2. World Population Prospects: The 2015 Revision, Key Findings and Advance Tables; Working Paper No. ESA/P/WP.241; United Nations Department of Economic and Social Affairs, Population Division: New York, NY, USA, 2015. 3. Snapshot of Global Photovoltaic Markets; Report IEA PVPS T1-29:2016; International Energy Agency (IEA): Paris, France, 2015. Energies 2016, 9, 622 12 of 13

4. Global Market Outlook for Solar Power 2015–2019; Solar Power Europe, European Photovoltaic Industry Association: Brussels, Belgium, 2015. 5. First Solar. Taking Energy Forward, Providing Comprehensive Solar Solutions to Diversify Your Energy Portfolio, 2016. Available online: http://www.ﬁrstsolar.com/ (accessed on 10 May 2016). 6. Alsema, E. Energy requirements of thin-ﬁlm solar cell modules—A review. Renew. Sustain. Energy Rev. 1998, 2, 387–415. [CrossRef]

7. Alsema, E. Energy pay-back time and CO2 emissions of PV systems. Prog. Photovolt. 2000, 8, 17–25. [CrossRef] 8. Alsema, E.; Nieuwlaar, E. Energy viability of photovoltaic systems. Energy Policy 2000, 28, 999–1010. [CrossRef] 9. Fthenakis, V.M. Life cycle impact analysis of cadmium in CdTe PV production. Renew. Sustain. Energy Rev. 2004, 8, 303–334. [CrossRef] 10. De Wild-Sholten, M.; Alsema, E. Towards cleaner solar PV: Environmental and health impacts of crystalline silicon photovoltaics. Refocus 2004, 5, 46–49. [CrossRef] 11. Fthenakis, V.M.; Kim, H.C.; Alsema, E. Emissions from photovoltaic life cycles. Environ. Sci. Technol. 2008, 42, 2168–2174. [CrossRef][PubMed] 12. Fthenakis, V.M.; Held, M.; Kim, H.C.; Raugei, M.; Krones, J. Update of energy payback times and environmental impacts of photovoltaics. In Proceedings of the 24th European Photovoltaic Solar Energy Conference and Exhibition, Hamburg, Germany, 21–25 September 2009. 13. Raugei, M.; Fullana-i-Palmer, P.; Fthenakis, V.M. The energy return on energy investment (EROI) of photovoltaics: Methodology and comparisons with fossil fuel life cycles. Energy Policy 2012, 45, 576–582. [CrossRef] 14. Dale, M.; Benson, S.M. The energy balance of the photovoltaic (PV) industry—Is the PV industry a net energy provider? Environ. Sci. Technol. 2013, 47, 3482–3489. [CrossRef][PubMed] 15. Consoli, F.; Allen, D.; Boustead, I.; De Oude, N.; Fava, J.; Franklin, R.; Jensen, A.A.; Parrish, R.; Perriman, R.; Postlethwaite, D.; et al. Guidelines for Life-Cycle Assessment: A “Code of Practice”; Society of Environmental Toxicology and Chemistry: Sesimbra, Portugal, 1993. 16. Environmental Management—Life Cycle Assessment—Principles and Framework; ISO 14040:2006; International Standardization Organization: Geneva, Switzerland, 2010. 17. Environmental Management—Life Cycle Assessment—Requirements and Guidelines; ISO 14044:2006; International Standardization Organization: Geneva, Switzerland, 2010. 18. Fthenakis, V.; Frischknecht, R.; Raugei, M.; Kim, H.C.; Alsema, E.; Held, M.; De Wild-Scholten, M. Methodology Guidelines on Life Cycle Assessment of Photovoltaic Electricity; Report IEA-PVPS T12-03:2011; International Energy Agency (IEA): Paris, France, 2016. 19. Frischknecht, R.; Wyss, F.; Büsser Knöpfel, S.; Lützkendorf, T.; Balouktsi, M. Cumulative energy demand in LCA: The energy harvested approach. Int. J. Life Cycle Assess. 2015, 20, 957–969. [CrossRef] 20. Leach, G. Net energy-is it any use? Energy Policy 1975, 3, 332–344. [CrossRef] 21. Chambers, R.S.; Herendeen, R.A.; Joyce, J.J.; Penner, P.S. Gasohol: Does it or doesn’t produce positive net energy? Science 1979, 206, 789–795. [CrossRef][PubMed] 22. Herendeen, R. Net energy considerations. In Economic Analysis of Solar Thermal Energy Systems; West, R., Kreith, F., Eds.; MIT Press: Cambridge, MA, USA, 1988; pp. 255–273. 23. Cleveland, C.J.; Costanza, R.; Hall, C.A.S.; Kaufmann, R. Energy and the U.S. economy: A biophysical perspective. Science 1984, 225, 890–897. [CrossRef][PubMed] 24. Cleveland, C.J. Energy quality and energy surplus in the extraction of fossil fuels in the U.S. Ecol. Indic. 1992, 6, 139–162. [CrossRef] 25. Herendeen, R. Net Energy Analysis: Concepts and Methods. In Encyclopedia of Energy; Elsevier: Amsterdam, The Netherlands, 2004; pp. 283–289. 26. Carbajales-Dale, M.; Barnhart, C.; Brandt, A.R.; Benson, S. A better currency for investing in a sustainable future. Nat. Clim. Chang. 2014, 4, 524–527. [CrossRef] 27. Raugei, M.; Frischknecht, R.; Olson, C.; Sinha, P.; Heath, G. Methodological Guidelines on Net Energy Analysis of Photovoltaic Electricity; Report IEA-PVPS T12-071:2016; International Energy Agency (IEA): Paris, France, 2016. Energies 2016, 9, 622 13 of 13

28. Hall, C.A.S.; Balogh, S.; Murphy, D.J.R. What is the minimum EROI that a sustainable society must have? Energies 2009, 2, 25–47. [CrossRef] 29. Lambert, J.C.; Hall, C.A.S.; Balogh, S.; Gupta, A.; Arnold, M. Energy, EROI and quality of life. Energy Policy 2014, 64, 153–167. [CrossRef] 30. Raugei, M.; Leccisi, E. A comprehensive assessment of the energy performance of the full range of electricity generation technologies deployed in the United Kingdom. Energy Policy 2016, 90, 46–59. [CrossRef] 31. Ecoinvent Database, 2016. Available online: http://www.ecoinvent.org/ (accessed on 10 May 2016). 32. Frischknecht, R.; Itten, R.; Sinha, P.; de Wild-Scholten, M.; Zhang, J.; Fthenakis, V.; Kim, H.C.; Raugei, M.; Stucki, M. Life Cycle Inventories and Life Cycle Assessment of Photovoltaic Systems; Report IEA-PVPS T12-04:2015; International Energy Agency (IEA): Paris, France, 2015. 33. De Wild-Scholten, M. Life Cycle Assessment of Photovoltaics Status 2011, Part 1 Data Collection; SmartGreenScans: Groet, The Netherlands, 2014. 34. Sander, K.; Schilling, S.; Reinschmidt, J.; Wambach, K.; Schlenker, S.; Müller, A.; Springer, J.; Fouquet, D.; Jelitte, A.; Stryi-Hipp, G.C. Study on the Development of a Take Back and Recovery System for Photovoltaic Products; Institut für Ökologie und Politik GmbH: Wuppertal, Germany, 2007. 35. Corcelli, F.; Ripa, M.; Leccisi, E.; Cigolotti, V.; Fiandra, V.; Graditi, G.; Sannino, L.; Tammaro, M.; Ulgiati, S. Sustainable urban electricity supply chain—Indicators of material recovery and energy savings from crystalline silicon photovoltaic panels end-of-life. Ecol. Indic. 2016.[CrossRef] 36. Carbajales-Dale, M.; Raugei, M.; Barnhart, C.J.; Fthenakis, V.M. Energy return on investment (EROI) of solar PV: An attempt at reconciliation. Proc. IEEE 2015, 103, 995–999. [CrossRef] 37. Nikolakakis, T.; Fthenakis, V.M. The optimum mix of electricity from wind- and solar-sources in conventional power systems: Evaluating the case for New York State. Energy Policy 2011, 39, 6972–6980. [CrossRef] 38. Pre Consultants 2014. SimaPro 8 LCA Software. Available online: https://www.pre-sustainability.com/ simapro (accessed on 10 May 2016). 39. CML-IA Characterisation Factors, 2016. Available online: http://www.universiteitleiden.nl/en/research/ research-output/science/cml-ia-characterisation-factors (accessed on 10 May 2016). 40. Photovoltaics Report; Fraunhofer Institute for Solar Energy Systems: Freiburg, Germany, 2016. 41. Silicon, 2016. Available online: http://minerals.usgs.gov/minerals/pubs/commodity/silicon/mcs-2016- simet.pdf (accessed on 10 May 2016). 42. Statistics Search, 2016. Available online: http://www.iea.org/statistics/statisticssearch/ (accessed on 10 May 2016). 43. EIA U.S. Energy Information Administration. Today in Energy, 2016. Available online: http://www.eia.gov (accessed on 10 May 2016). 44. Breakdown of Electricity Generation by Energy Source. The Shift Project Data Protal, 2014. Available online: http://www.tsp-data-portal.org/Breakdown-of-Electricity-Generation-by-Energy- Source#tspQvChart (accessed on 10 May 2016). 45. Suruhanjaya Tenaga Energy Commission. Peninsular Malaysia Electricity Supply Industry Outolook 2014. Available online: http://www.st.gov.my/index.php/en/component/k2/item/606-peninsular-malaysia- electricity-supply-industry-outlook-2014.html (accessed on 10 May 2016). 46. De Wild-Scholten, M. Energy payback time and carbon footprint of commercial photovoltaic systems. Sol. Energy Mater. Sol. Cells 2013, 119, 296–305. [CrossRef]

47. Mason, J.; Fthenakis, V.M.; Hansen, T.; Kim, C. Energy pay-back and life cycle CO2 emissions of the BOS in an optimized 3.5 MW PV installation. Prog. Photovolt. Res. Appl. 2006, 14, 179–190. [CrossRef] 48. Murphy, D.; Hall, C.A.S. Year in review—EROI or energy return on (energy) invested. Ann. N. Y. Acad. Sci. 2010, 1185, 102–118. [CrossRef][PubMed] 49. Sinha, P.; Schneider, M.; Dailey, S.; Jepson, C.; De Wild-Scholten, M. Eco-efﬁciency of CdTe photovoltaics with tracking systems. In Proceedings of the 39th IEEE Photovoltaic Specialists Conference (PVSC), Tampa, FL, USA, 16–21 June 2013.

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).