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

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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/(m2·yr)) to 2.8 years for sc-Si PV at low-irradiation (1000 kWh/(m2·yr)), 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.
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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, *
1Department of Science and Technology, Parthenope University of Naples, Centro Direzionale-Isola C4,
Naples 80143, Italy; enrica.leccisi@uniparthenope.it
2Department of Mechanical Engineering and Mathematical Sciences, Oxford Brookes University,
Wheatley OX33 1HK, UK; marco.raugei@brookes.ac.uk
3Center for Life Cycle Analysis, Columbia University, New York, NY 10027, USA
4Photovoltaic Environmental Research Center, Brookhaven National Laboratory, Upton, NY 11973, USA
*Correspondence: vmf5@columbia.edu; 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/(m
2¨
yr)) to 2.8 years for sc-Si PV at low-irradiation (1000 kWh/(m
2¨
yr)),
with corresponding quality-adjusted energy return on investment (EROI
PE-eq
) values ranging from
over 60 to ~10. Global warming potential (GWP) per kWh
el
averages out at ~30 g (CO
2
-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 GW
p
[
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 GW
p
in 2014 to around 8 GW
p
in 2015, while in the US it has grown to 7.3 GW
p
,
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 GW
p
and 9.5 GW
p
respectively, and corresponding
cumulative capacities of 28.2 GW
p
and 23.3 GW
p
[
3
]. In addition, several established markets have
confirmed their maturity, including Korea with 1.0 GW
p
, Australia with 0.9 GW
p
, 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/
µ
c-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; Out
el
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 [2026].
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 Out
PE-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 EROI
PE-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, EROI
PE-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 [2830].
The accurate quantification of the minimum EROI
PE-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 Tis the lifetime of the PV system, measured in years.
In this paper, the calculations of EROI
PE-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 (EROI
PE-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
Figures 1and 2show the respective flow diagrams for the c-Si and thin film PV systems.
In particular, Figure 1illustrates each step of the manufacturing chain for sc-Si and mc-Si PV panels.
After the metallurgical (MG) and solar grade (SoG) Si production stages, mc-Si ingots are cast and
sawn into wafers: sc-Si PV cells additionally require an intermediate Czochralski (CZ) recrystallization
step. Then, the individual PV cells are encapsulated between glass panes and assembled into framed
PV panels, and finally the PV system is completed by the addition of the BOS. In contrast, Figure 2
shows that the simpler flow diagrams for CdTe and CIGS technologies. Incidentally, the thin film PV
panels are also glass-glass sandwiches, but devoid of metal frames.
Energies2016,9,6225of13
sawnintowafers:scSiPVcellsadditionallyrequireanintermediateCzochralski(CZ)
recrystallizationstep.Then,theindividualPVcellsareencapsulatedbetweenglasspanesand
assembledintoframedPVpanels,andfinallythePVsystemiscompletedbytheadditionofthe
BOS.Incontrast,Figure2showsthatthesimplerflowdiagramsforCdTeandCIGStechnologies.
Incidentally,thethinfilmPVpanelsarealsoglassglasssandwiches,butdevoidofmetalframes.
Figure1.FlowdiagramforsinglecrystallineSi(scSi)andmulticrystallineSi(mcSi)photovoltaic
(PV)systems.SoG:solargrade;andCZ:Czochralski.
Figure2.Flowdiagramforcadmiumtelluride(CdTe)andcopperindiumgalliumdiselenide(CIGS)
PVsystems.BOS:balanceofsystem
3.2.ProductionSitesandElectricityMixes
EachanalysedPVsystemisalsoclassifiedbycountryofproduction.ThecSiPVproduction
chainisclassifiedintothreemainproducingregions:Europe,China,andtheUSA,accordingtothe
datasourceused[32].ThescSiandmcSiwafersusedinChinesePVmanufacturingareentirely
sourceddomestically;ofthoseusedinUSPVmanufacturing,66%areproducedinChinaand34%
domestically;andforthoseusedinEuropeanPVmanufacturing,89%isproducedlocallyand11%in
China.RegardingCdTePVpanels,thetwoproductioncountriesasof2016areMalaysiaandthe
USA,inaccordancewiththedataprovidedbytheleadingcompanyinthissector(FirstSolar).The
mainproductioncountriesforCIGSPVareJapan(SolarFrontier)[40],towhichouranalysisrefers,
andChina(Hanergy).AllfurtherupstreamstepsintheSisupplychainareanalysedconsidering
theiractualgeographicallocation—forinstance,theproductionofMGSiisdividedamongthemain
globalproducers,i.e.,China,Russia,NorwayandtheUnitedStates[41].
TheindividuallocalupdatedelectricitymixesusedforallPVmodulemanufacturingandfor
theSisupplyingcountriesarealsoconsideredinouranalysis,sincetheyinfluencetheamountofPE
ultimatelyrequiredforeachproductionprocess,aswellastheassociatedenvironmentalimpacts
(NorwegianandJapanesedatafromtheIEA[42];ChineseandUSAdatafromtheU.S.Energy
InformationAdministration(EIA)[43];RussianandEuropeandatafromtheWorldBank(world
Figure 1.
Flow diagram for single-crystalline Si (sc-Si) and multi-crystalline Si (mc-Si) photovoltaic
(PV) systems. SoG: solar grade; and CZ: Czochralski.
Energies2016,9,6225of13
sawnintowafers:scSiPVcellsadditionallyrequireanintermediateCzochralski(CZ)
recrystallizationstep.Then,theindividualPVcellsareencapsulatedbetweenglasspanesand
assembledintoframedPVpanels,andfinallythePVsystemiscompletedbytheadditionofthe
BOS.Incontrast,Figure2showsthatthesimplerflowdiagramsforCdTeandCIGStechnologies.
Incidentally,thethinfilmPVpanelsarealsoglassglasssandwiches,butdevoidofmetalframes.
Figure1.FlowdiagramforsinglecrystallineSi(scSi)andmulticrystallineSi(mcSi)photovoltaic
(PV)systems.SoG:solargrade;andCZ:Czochralski.
Figure2.Flowdiagramforcadmiumtelluride(CdTe)andcopperindiumgalliumdiselenide(CIGS)
PVsystems.BOS:balanceofsystem
3.2.ProductionSitesandElectricityMixes
EachanalysedPVsystemisalsoclassifiedbycountryofproduction.ThecSiPVproduction
chainisclassifiedintothreemainproducingregions:Europe,China,andtheUSA,accordingtothe
datasourceused[32].ThescSiandmcSiwafersusedinChinesePVmanufacturingareentirely
sourceddomestically;ofthoseusedinUSPVmanufacturing,66%areproducedinChinaand34%
domestically;andforthoseusedinEuropeanPVmanufacturing,89%isproducedlocallyand11%in
China.RegardingCdTePVpanels,thetwoproductioncountriesasof2016areMalaysiaandthe
USA,inaccordancewiththedataprovidedbytheleadingcompanyinthissector(FirstSolar).The
mainproductioncountriesforCIGSPVareJapan(SolarFrontier)[40],towhichouranalysisrefers,
andChina(Hanergy).AllfurtherupstreamstepsintheSisupplychainareanalysedconsidering
theiractualgeographicallocation—forinstance,theproductionofMGSiisdividedamongthemain
globalproducers,i.e.,China,Russia,NorwayandtheUnitedStates[41].
TheindividuallocalupdatedelectricitymixesusedforallPVmodulemanufacturingandfor
theSisupplyingcountriesarealsoconsideredinouranalysis,sincetheyinfluencetheamountofPE
ultimatelyrequiredforeachproductionprocess,aswellastheassociatedenvironmentalimpacts
(NorwegianandJapanesedatafromtheIEA[42];ChineseandUSAdatafromtheU.S.Energy
InformationAdministration(EIA)[43];RussianandEuropeandatafromtheWorldBank(world
Figure 2.
Flow diagram for cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS)
PV systems. BOS: balance of system.
3.2. Production Sites and Electricity Mixes
Each analysed PV system is also classified by country of production. The c-Si PV production
chain is classified into three main producing regions: Europe, China, and the USA, according to the
data source used [
32
]. The sc-Si and mc-Si wafers used in Chinese PV manufacturing are entirely
sourced domestically; of those used in US PV manufacturing, 66% are produced in China and 34%
domestically; and for those used in European PV manufacturing, 89% is produced locally and 11%
in China. Regarding CdTe PV panels, the two production countries as of 2016 are Malaysia and
the USA, in accordance with the data provided by the leading company in this sector (First Solar).
The main production countries for CIGS PV are Japan (Solar Frontier) [
40
], to which our analysis refers,
and China (Hanergy). All further upstream steps in the Si supply chain are analysed considering their
actual geographical location—for instance, the production of MG-Si is divided among the main global
producers, i.e., China, Russia, Norway and the United States [41].
The individual local updated electricity mixes used for all PV module manufacturing and for
the Si supplying countries are also considered in our analysis, since they influence the amount
of PE ultimately required for each production process, as well as the associated environmental
impacts (Norwegian and Japanese data from the IEA [
42
]; Chinese and USA data from the U.S.
Energies 2016,9, 622 6 of 13
Energy Information Administration (EIA) [
43
]; Russian and European data from the World Bank
(world development indicators) [44]; Malaysian data from the Peninsular Malaysia electricity supply
industry outlook [45].)
4. Results and Discussion
4.1. Fixed-Tilt Ground-Mounted Photovoltaic Systems
Figure 3shows the CED of the analysed PV systems, while Figures 46illustrate the respective
LCA impact indicators, namely global warming potential (GWP), acidification potential (AP),
and ozone depletion potential (ODP), all expressed per kW
p
—the stacked bars show the individual
contributions of the main life cycle stages. Each PV technology is also shown separately according
to the country or region in which it was manufactured. The average efficiency for each technology is
assumed in accordance with the latest report by the Fraunhofer Institute for Solar Energy Systems [
40
],
specifically: 17% for sc-Si PV, 16% for mc-Si, 15.6% for CdTe PV, and 14% for CIGS PV.
Energies2016,9,6226of13
developmentindicators)[44];MalaysiandatafromthePeninsularMalaysiaelectricitysupply
industryoutlook[45].)
4.ResultsandDiscussion
4.1.FixedTiltGroundMountedPhotovoltaicSystems
Figure3showstheCEDoftheanalysedPVsystems,whileFigures4–6illustratetherespective
LCAimpactindicators,namelyglobalwarmingpotential(GWP),acidificationpotential(AP),and
ozonedepletionpotential(ODP),allexpressedperkWp—thestackedbarsshowtheindividual
contributionsofthemainlifecyclestages.EachPVtechnologyisalsoshownseparatelyaccordingto
thecountryorregioninwhichitwasmanufactured.Theaverageefficiencyforeachtechnologyis
assumedinaccordancewiththelatestreportbytheFraunhoferInstituteforSolarEnergy
Systems[40],specifically:17%forscSiPV,16%formcSi,15.6%forCdTePV,and14%forCIGSPV.
0
5,000
10,000
15,000
20,000
25,000
30,000
BOS
PVpanel
PVcell
SoGSi
MJPE/kW
p
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure3.Cumulativeenergydemand(CED)perkWpoftheanalysedPVsystems.
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
BOS
PVpanel
PVcell
SoGSi
kg(CO
2
eq)/kWp
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure4.Globalwarmingpotential(GWP)perkWpoftheanalysedPVsystems.
Figure 3. Cumulative energy demand (CED) per kWpof the analysed PV systems.
Energies2016,9,6226of13
developmentindicators)[44];MalaysiandatafromthePeninsularMalaysiaelectricitysupply
industryoutlook[45].)
4.ResultsandDiscussion
4.1.FixedTiltGroundMountedPhotovoltaicSystems
Figure3showstheCEDoftheanalysedPVsystems,whileFigures4–6illustratetherespective
LCAimpactindicators,namelyglobalwarmingpotential(GWP),acidificationpotential(AP),and
ozonedepletionpotential(ODP),allexpressedperkWp—thestackedbarsshowtheindividual
contributionsofthemainlifecyclestages.EachPVtechnologyisalsoshownseparatelyaccordingto
thecountryorregioninwhichitwasmanufactured.Theaverageefficiencyforeachtechnologyis
assumedinaccordancewiththelatestreportbytheFraunhoferInstituteforSolarEnergy
Systems[40],specifically:17%forscSiPV,16%formcSi,15.6%forCdTePV,and14%forCIGSPV.
0
5,000
10,000
15,000
20,000
25,000
30,000
BOS
PVpanel
PVcell
SoGSi
MJPE/kW
p
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure3.Cumulativeenergydemand(CED)perkWpoftheanalysedPVsystems.
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
BOS
PVpanel
PVcell
SoGSi
kg(CO
2
eq)/kWp
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure4.Globalwarmingpotential(GWP)perkWpoftheanalysedPVsystems.
Figure 4. Global warming potential (GWP) per kWpof the analysed PV systems.
Energies 2016,9, 622 7 of 13
Figure 5. Acidification potential (AP) per kWpof the analysed PV systems.
Energies2016,9,6227of13
0
2
4
6
8
10
12
14
16
18
20
BOS
PVpanel
PVcell
SoGSi
kg(SO
2
eq)/kWp
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure5.Acidificationpotential(AP)perkWpoftheanalysedPVsystems.
0.0E+00
5.0E05
1.0E04
1.5E04
2.0E04
2.5E04
3.0E04
3.5E04
BOS
PVpanel
PVcell
SoGSi
kgCFC11eq
scSi PV multiSi PV CIGS PV
CdTePV
EU EU USUS CN CN MY US JP
Figure6.Ozonedepletionpotential(ODP)perkWpoftheanalysedPVsystems.
TheresultsclearlyshowthatthemostimpactingstepforcSitechnologiesisfromSoGSisupply
tofinishedPVcells,whichincludesingot/crystalgrowthandwaferandcellproduction,andespecially
sointhecaseofscSiPVsystems(becauseoftheenergyintensiveCZcrystalgrowthprocess).
Figure3highlightsthat,perkWp,cSiPVsystemsareoveralltwiceasenergydemandingto
produceasCdTePVsystems.Figure4illustratestheresultingGWPindicatorperkWp:cSiPV
technologiesgenerallyhavehighervaluesincomparisonwiththinfilmPVpanels,andinparticular,
thelowestGWPvaluesareforCdTePV,especiallywhenproductiontakesplaceinMalaysia.A
similartrendisshowninFigure5,inwhichthelowervaluesofAPperkWparethoseforCdTePV,
andsecondlyforCIGSPV;conversely,scSiPVshowsthehighestAPvalues,followedbymcSiPV.
AlsointermsofODPresults(Figure6),CdTePVisstillthebestperformer,followedbyCIGSPV,
andthenmcSiandscSiPV.
ThesenewresultsshowaremarkableimprovementforcurrentproductionCdTePVmodules
whencomparedtosimilarmodulesproducedin2005(themostrecentproductionyearforwhich
CdTePVinventorydataaredirectlyavailableintheEcoinventV3.1Database).Overonedecade,the
CEDperkWpfortheCdTePVmodulesmanufacturedintheUShasbeenreducedbyapproximately
62%,whiletheGWP,ODP,andAPresultsarealsodownbyrespectively63%,65%,and71%.The
Figure 6. Ozone depletion potential (ODP) per kWpof the analysed PV systems.
The results clearly show that the most impacting step for c-Si technologies is from SoG-Si supply
to finished PV cells, which includes ingot/crystal growth and wafer and cell production, and especially
so in the case of sc-Si PV systems (because of the energy intensive CZ crystal growth process).
Figure 3highlights that, per kW
p
, c-Si PV systems are overall twice as energy-demanding to produce
as CdTe PV systems. Figure 4illustrates the resulting GWP indicator per kW
p
: c-Si PV technologies
generally have higher values in comparison with thin film PV panels, and in particular, the lowest GWP
values are for CdTe PV, especially when production takes place in Malaysia. A similar trend is shown
in Figure 5, in which the lower values of AP per kW
p
are those for CdTe PV, and secondly for CIGS PV;
conversely, sc-Si PV shows the highest AP values, followed by mc-Si PV. Also in terms of ODP results
(Figure 6), CdTe PV is still the best performer, followed by CIGS PV, and then mc-Si and sc-Si PV.
These new results show a remarkable improvement for current production CdTe PV modules
when compared to similar modules produced in 2005 (the most recent production year for which CdTe
PV inventory data are directly available in the Ecoinvent V3.1 Database). Over one decade, the CED
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/m
2
) than the previously used data
from the c-Si PV BOS (542 MJ/m
2
, First Solar) [
47
]. The same also applies to the calculated EPBT
values (Table 1).
Table 1.
Energy pay-back time (EPBT) of the analysed PV systems (mean values for the various
production sites), corresponding to the three considered irradiation levels.
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
1700 kWh/(m2¨yr); η= 0.3 1.6 1.2 0.6 1.1
2300 kWh/(m2¨yr); η= 0.3 1.2 0.9 0.5 0.8
From a geographical perspective, it is also clear from the results that the considered impact
indicators (GWP, AP, ODP) are generally lower when the manufacturing takes place in Europe in
comparison with the USA and China, and in particular the Chinese production chain consistently
shows the highest indicator values. This is despite the fact that the CED associated to the Chinese
c-Si PV production is actually slightly lower than that for the European and USA manufacturing
chains—this seeming incongruence depends on the large reliance of the Chinese electric grid on
coal [
43
]. The input grid mix composition is also responsible for a significant share of the impacts in
the case of CIGS PV produced in Japan (a country where, after the 2011 nuclear incident 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
negatively affected by the comparatively large amounts of copper and aluminium required.
Figures 710 then illustrate the same results (CED, GWP, AP and ODP) expressed per kWh
el
.
These results are computed assuming a performance ratio of 0.8 and a lifetime of 30 years [
18
].
Also, in order to provide results applicable to different contexts, three different irradiation levels are
used, which are respectively representative of irradiation on a south-facing, latitude-tilted plane in
Central-Northern Europe (1000 kWh/(m
2¨
yr)), Central-Southern Europe (1700 kWh/(m
2¨
yr)), and the
Southwestern United States (2300 kWh/(m
2¨
yr)). In the figures, different symbol sizes (small, medium,
and large, respectively) are used to refer to these three specific irradiation levels.
Energies2016,9,6228of13
currentCdTePVsystemsalsoshowimprovementswhencomparedtopreviouslypublishedresults
[46]referringtomorerecent(2010–2011)productiondata;inthiscasetheCEDisdownby
approximately30%,andtheGWPisdownby37%.
Itisnoted,however,thattheCEDofcompletegroundmountedCdTePVsystemsarenotmuch
lowerthanpreviouslyreportedvalues,becausethenewinventorydataforthegroundmounted
BOSprovidedbyFirstSolarledtoahigherenergydemand(831MJ/m2)thanthepreviouslyused
datafromthecSiPVBOS(542MJ/m2,FirstSolar)[47].ThesamealsoappliestothecalculatedEPBT
values(Table1).
Fromageographicalperspective,itisalsoclearfromtheresultsthattheconsideredimpact
indicators(GWP,AP,ODP)aregenerallylowerwhenthemanufacturingtakesplaceinEuropein
comparisonwiththeUSAandChina,andinparticulartheChineseproductionchainconsistently
showsthehighestindicatorvalues.ThisisdespitethefactthattheCEDassociatedtotheChinese
cSiPVproductionisactuallyslightlylowerthanthatfortheEuropeanandUSAmanufacturing
chainsthisseemingincongruencedependsonthelargerelianceoftheChineseelectricgridoncoal
[43].Theinputgridmixcompositionisalsoresponsibleforasignificantshareoftheimpactsinthe
caseofCIGSPVproducedinJapan(acountrywhere,afterthe2011nuclearincidentinFukushima,
over90%oftheenergyresourcesusedforelectricitygenerationarefossilfuels[42]).
TheBOScontributionisgenerallyfairlylow,withthepartialexceptionoftheAPresults,which
arenegativelyaffectedbythecomparativelylargeamountsofcopperandaluminiumrequired.
Figures7–10thenillustratethesameresults(CED,GWP,APandODP)expressedperkWhel.
Theseresultsarecomputedassumingaperformanceratioof0.8andalifetimeof30years[18].Also,
inordertoprovideresultsapplicabletodifferentcontexts,threedifferentirradiationlevelsareused,
whicharerespectivelyrepresentativeofirradiationonasouthfacing,latitudetiltedplanein
CentralNorthernEurope(1000kWh/(m2yr)),CentralSouthernEurope(1700kWh/(m2yr)),andthe
SouthwesternUnitedStates(2300kWh/(m2yr)).Inthefigures,differentsymbolsizes(small,
medium,andlarge,respectively)areusedtorefertothesethreespecificirradiationlevels.
3.5
4.0
4.5
5.0
MJ
PE
/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure7.CEDperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
Unsurprisingly,thebestenergyandenvironmentalperformanceasmeasuredbyallconsidered
metricsisthatofCdTePVsystemsinstalledintheSouthwesternUS,withCIGSPVasaclosesecond.
Attheotherendofthescale,thehighestimpactintermsofGWPandAParethosefortheChinese
producedscSiPV,mainlyduetothistechnology’shigherdemandforinputelectricity,coupled
withtheprominenceofcoalintheChineseelectricitygridmix.
Figure 7.
CED per kWh
el
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).
Unsurprisingly, the best energy and environmental performance as measured by all considered
metrics is that of CdTe PV systems installed in the Southwestern US, with CIGS PV as a close second.
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.
Energies2016,9,6229of13
0
10
20
30
40
50
60
70
80
90
100
g(CO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure8.GWPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0.0
0.2
0.4
0.6
0.8
1.0
g(SO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure9.APperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0
1
2
3
4
5
6
7
8
µgCFC11eq
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure10.ODPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
AsillustratedinTable1,theenergypaybacktimesoftheanalysedPVtechnologieswerefound
torangefrom6months(forCdTePVinstalledintheUSSouthWest)toapproximately2–3years(for
cSiPVinstalledinCentralNorthernEurope).
Figure 8.
GWP per kWh
el
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).
Energies2016,9,6229of13
0
10
20
30
40
50
60
70
80
90
100
g(CO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU U S CN MY US JP
Figure8.GWPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0.0
0.2
0.4
0.6
0.8
1.0
g(SO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure9.APperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0
1
2
3
4
5
6
7
8
µgCFC11eq
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure10.ODPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
AsillustratedinTable1,theenergypaybacktimesoftheanalysedPVtechnologieswerefound
torangefrom6months(forCdTePVinstalledintheUSSouthWest)toapproximately2–3years(for
cSiPVinstalledinCentralNorthernEurope).
Figure 9.
AP per kWh
el
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).
Energies2016,9,6229of13
0
10
20
30
40
50
60
70
80
90
100
g(CO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU U S CN MY US JP
Figure8.GWPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0.0
0.2
0.4
0.6
0.8
1.0
g(SO
2
eq)/kWh
el
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure9.APperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
0
1
2
3
4
5
6
7
8
µgCFC11eq
scSi PV mcSi PV CdTe PV CIGS PV
EU US CN EU US CN MY US JP
Figure10.ODPperkWheloftheanalysedPVsystems,underthreeirradiationlevels.Smallsymbols:
1000kWh/(m2yr);mediumsymbols:1700kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
AsillustratedinTable1,theenergypaybacktimesoftheanalysedPVtechnologieswerefound
torangefrom6months(forCdTePVinstalledintheUSSouthWest)toapproximately2–3years(for
cSiPVinstalledinCentralNorthernEurope).
Figure 10.
ODP per kWh
el
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).
Energies 2016,9, 622 10 of 13
As illustrated in Table 1, the energy pay-back times of the analysed PV technologies were found to
range from 6 months (for CdTe PV installed in the US South-West) to approximately 2–3 years (for c-Si
PV installed in Central-Northern Europe).
Figure 11 illustrates the positioning of the analysed PV systems along the curve defined by the
non-linear relation of EROI
PE-eq
to NTG (often referred to as the “net energy cliff” [
48
]). This figure
makes it abundantly clear that, while the individual EROI
PE-eq
values for the different PV systems
over the three considered irradiation levels span a comparatively large range—from ~10 for sc-Si PV at
1000 kWh/(m
2¨
yr) to ~60 for CdTe PV at 2300 kWh/(m
2¨
yr)—in fact, all data points sit on what may
be considered the “safe”, quasi-horizontal portion of the “cliff”. In other words, all PV systems afford
the benefit of over 90% of their gross energy output being available as net usable energy to the end
user (NTG > 0.9).
Energies2016,9,62210of13
Table1.Energypaybacktime(EPBT)oftheanalysedPVsystems(meanvaluesforthevarious
productionsites),correspondingtothethreeconsideredirradiationlevels.
IrradiationandGridEfficiency(η)scSiPV mcSiPV CdTePVCIGSPV
1000kWh/(m2yr);η=0.32.82.11.11.9
1700kWh/(m2yr);η=0.31.61.20.61.1
2300kWh/(m2yr);η=0.31.20.90.50.8
Figure11illustratesthepositioningoftheanalysedPVsystemsalongthecurvedefinedbythe
nonlinearrelationofEROIPEeqtoNTG(oftenreferredtoasthe“netenergycliff”[48]).Thisfigure
makesitabundantlyclearthat,whiletheindividualEROIPEeqvaluesforthedifferentPVsystems
overthethreeconsideredirradiationlevelsspanacomparativelylargerange—from~10forscSiPV
at1000kWh/(m2yr)to~60forCdTePVat2300kWh/(m2yr)—infact,alldatapointssitonwhatmay
beconsideredthe“safe”,quasihorizontalportionofthe“cliff”.Inotherwords,allPVsystems
affordthebenefitofover90%oftheirgrossenergyoutputbeingavailableasnetusableenergytothe
enduser(NTG>0.9).
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
010203040506070
NTG
EROI
PEeq
NetEnergyCliff scSiPV mcSiPV CdTePV CIGSPV
Figure11.PositioningoftheanalysedPVsystemsonthe“netenergycliff”(illustratingthe
nonlinearrelationofthenettogrossenergyoutputratiototheenergyreturnoninvestment
(EROIPEeq)),underthreeirradiationlevels.Smallsymbols:1000kWh/(m2yr);mediumsymbols:1700
kWh/(m2yr);andlargesymbols:2300kWh/(m2yr).
4.2.AComparisonto1AxisTrackingInstallations
Generally,trackingPVsystemsprovidethebenefitofboostingtheenergyyieldincomparison
withfixedtiltinstallationsbecausethepanelsaremountedonastructurethatfollowsthe
movementofthesun.Inparticular,oneaxistrackershaveonedegreeoffreedom(themovement
occursalongasingleaxisofrotation).Theresultsshownbelowcorrespondtoahorizontalrotational
axisintheNorthSouth(NS)directionwiththepanelsfacingEastinthemorningandfacingWestin
thelateafternoon.Trackingcouldbefurtheroptimizedwiththehorizontalrotationalaxistilted
southifthetopographyallows,whichwouldgivethebenefitofaflatterprofilethroughouttheday.
Ononehand,theinvestedenergy(andassociatedenvironmentalimpacts)forbuildingthe
trackingBOSarehigherthanforconventionalfixedtiltPVsystems,sincetrackinginstallations
requirelargeramountsofstructuralsteelandcoppercabling;also,theyuseelectricityduringthe
usagephasefortrackingactuators.Ontheotherhand,thekeyadvantageoftrackingsystemsisthe
abilitytoharvestmoredirectbeamirradiance,therebyrequiringfewerPVmodulesperkWh
producedincomparisonwithfixedtiltinstallations.
Theenergyandenvironmentalperformanceoftrackingsystemsarehighlyinfluencedbysite
latitudeanddiffusedlightconditions;inparticular,siteswithlower(<40%)diffusedlightbenefit
Figure 11.
Positioning of the analysed PV systems on the “net energy cliff” (illustrating the non-linear
relation of the net-to-gross energy output ratio to the energy return on investment (EROI
PE-eq
)),
under three irradiation levels. Small symbols: 1000 kWh/(m
2¨
yr); medium symbols: 1700 kWh/(m
2¨
yr);
and large symbols: 2300 kWh/(m2¨yr).
4.2. A Comparison to 1-Axis Tracking Installations
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 movement
of the sun. In particular, one-axis trackers have one degree of freedom (the movement occurs along
a single axis of rotation). The results shown below correspond to a horizontal rotational axis in the
North-South (N-S) direction with the panels facing East in the morning and facing West in the late
afternoon. Tracking could be further optimized with the horizontal rotational axis tilted south if the
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
tracking BOS are higher than for conventional fixed-tilt PV systems, since tracking installations require
larger amounts of structural steel and copper cabling; also, they use electricity during the usage phase
for tracking actuators. On the other hand, the key advantage of tracking systems is the ability to
harvest more direct beam irradiance, thereby requiring fewer PV modules per kWh produced in
comparison with fixed-tilt installations.
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 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].
Table 2shows 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/(m
2¨
yr) 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
installations, per kWh
el
and relative to fixed-tilt installations. Assumed irradiation: 2300 kWh/(m
2¨
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.
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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/).
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Purpose Environmental life cycle assessment (LCA) is today an important methodology to quantify the life cycle based environmental impacts of products, services or organisations. Since the very first LCA studies, the cumulative energy demand CED (also called ‘primary energy consumption’) has been one of the key indicators being addressed. Despite its popularity, there is no harmonised approach yet and the standards and guidelines define the cumulative energy demand differently. In this paper, an overview of existing and applied life cycle based energy indicators and a unifying approach to establish characterisation factors for the cumulative energy demand indicator are provided. The CED approaches are illustrated in a building’s LCA case study. Methods The five approaches are classified into two main concepts, namely the energy harvested and the energy harvestable concepts. The two concepts differ by the conversion efficiency of the energy collecting facility. A unifying ‘energy harvested’ approach is proposed based on four theses, which ensure consistent accounting among renewable and non renewable energy resources. Results and discussion The indicator proposed is compared to four other CED indicators, differing in the characterisation factors of fossil and biomass resources (upper or lower heating value), the characterisation factor of uranium and the characterisation factors of renewable energy resources (amount harvested or amount harvestable). The comparison of the five approaches is based on the cumulative energy demand of a newly constructed building of the city of Zürich covering the whole life cycle, including manufacturing and construction, replacement and use phase, and end of life. The cumulative energy demand of the life cycle of the building differs between 336 MJ oil-eq/m2a (‘CED uranium low’) and 836 MJ oil-eq/m2a (‘CED energy statistics’). The main differences occur in the use phase. The main reason for the large differences in the results are the different concepts to determine the characterisation factors for renewable and nuclear energy resources. Conclusions The energy harvested approach ‘CED standard’ is a consistent approach, which quantifies the energy content of all different (renewable and non-renewable) energy resources. The ‘CED standard’ approach and the impact category indicator results computed with this approach reflect the safeguard subject ‘energy resources’ but not (no other) environmental impacts. The energy harvested approach proposed in this paper can readily be implemented in different contexts and applied to various data sets.