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RESEARCH ARTICLE
Updated sustainability status of crystalline silicon-based
photovoltaic systems: Life-cycle energy and environmental
impact reduction trends
Vasilis Fthenakis | Enrica Leccisi
Center for Life Cycle Analysis, Columbia
University, New York, NY, 10027, USA
Correspondence
Enrica Leccisi, Center for Life Cycle Analysis,
Columbia University, New York, NY 10027,
USA.
Email: el2828@columbia.edu
Abstract
This paper provides a comprehensive assessment of the current life-cycle sustainabil-
ity status of crystalline-based photovoltaic (PV) systems. Specifically, single-
crystalline Si (sc-Si) and multicrystalline Si (mc-Si) PV systems are analyzed in terms
of their environmental and energy performance, providing breakdown contributions
and comparisons with estimates published 6 years ago. Results clearly show the sig-
nificant environmental improvement in the sc-Si PV system production—mainly at
the wafer stage—for which the impacts have been reduced by up to 50% in terms of
carbon emissions and 42% in terms of acid gas emissions. The life-cycle cumulative
energy demand is estimated to be approximately 48% lower (for sc-Si) and 24% lower
(for mc-Si) than previously reported estimates. Energy payback times of currently
installed systems range from 1.3 (for c-Si PV) and 1.5 years (mc-Si PV) for fixed-tilt
ground-mounted installations at low irradiation (1000 kWh/m
2
/year), to 0.6 years at
high irradiation (2300 kWh/m
2
/year). The resulting energy returns on investment—
expressed in terms of primary energy—range from 22 (at low irradiation) to
52 (at high irradiation) for sc-Si PV systems and from 21 to 47 for mc-Si PV systems.
Furthermore, we examine the effects of cleaner electricity grids and grid efficiency
improvements on these environmental and energy indicators.
KEYWORDS
environmental impacts, EPBT, EROI, LCA, NEA, crystalline Si
1|INTRODUCTION
A clean energy transition worldwide is being driven by renewable
energy sources. In particular, the solar photovoltaic (PV) market has
been growing rapidly to address this challenge and to meet the
increasing demand for affordable green power worldwide.
1
PVs entail
several technologies, the most mature being single-crystalline silicon
(sc-Si) and multicrystalline silicon (mc-Si), accounting for approxi-
mately 95% of the total production.
2
Over the last 5–7 years, there
has been significant improvement in the material and energy utiliza-
tion in the production of PV wafers, cells, and panels
3–12
; therefore,
updating the energy and environmental impacts of PV technologies is
crucial in considering sustainable energy options and for assessing
future scenarios with large penetration of PV into electric grids.
13–16
This paper describes the energy use and environmental impact
improvements in manufacturing crystalline Si (c-Si) PV systems over
the last 5–7 years, detailing the life-cycle impacts of each stage of
their supply chain. A full range of life-cycle energy investment and
environmental impact metrics is estimated and compared with results
published 6 years ago.
12
In parallel to life-cycle analysis (LCA), net
energy analysis (NEA) is conducted for current Si PV technologies.
NEA metrics include energy payback times (EPBTs) and energy return
on investment (EROI); these are assessed in terms of electricity and
primary energy consumed during their life cycles. In addition, case
Received: 26 March 2021 Revised: 7 May 2021 Accepted: 13 May 2021
DOI: 10.1002/pip.3441
Prog Photovolt Res Appl. 2021;1–10. wileyonlinelibrary.com/journal/pip © 2021 John Wiley & Sons, Ltd. 1
studies and sensitivity analyses were carried out, assessing various
scenarios of shifting from predominantly fossil fuel-based energy grids
to cleaner electricity grid mix compositions.
2|METHODOLOGY
2.1 |Life-cycle analysis
LCA is an analytical methodology widely adopted by the scientific
community for quantifying potential environmental and energy
impacts of a system, service, or product, through its entire life cycle.
LCA is used to quantify all energy and material inputs, outputs, and
emissions in each stage of a product's life cycle from the extraction of
raw materials to the component and product manufacturing, trans-
port, distribution, operation phase, maintenance, reuse, recycling, and
disposal.
17
It has been standardized by the Society of Environmental
Toxicology and Chemistry (SETAC)
18
and the International Organiza-
tion for Standardization (ISO) Standards 14040 and 14044.
19,20
For
LCA of PV systems, the International Energy Agency (IEA) provides
specific guidelines.
21
LCA addresses a number of environmental impact categories—
such as global warming potential (GWP) and acidification potential
(AP). GWP quantifies the global warming impacts of different green-
house gases, and it is expressed in kgCO
2
eq units. AP measures the
acid potential impacts of acidifying contaminants (such as SO
2
,NO
x
,
NO, N
2
O, HCl, NH
3
, and HF) on soil, groundwater, surface waters,
biological organisms, ecosystems, and substances, and it is expressed
in terms of kgSO
2
eq.
Also, LCA allows the calculation of the total primary energy
harvested from the environment—cumulative energy demand (CED)—
normalized per unit of rated electric power output.
22
In the context of LCA, EPBT measures how many years it takes
for the PV system to generate an amount of electricity which is equiv-
alent to the primary energy invested. EPBT strongly depends on geo-
graphical deployment distribution, in terms of irradiation levels and
associated grid mix efficiencies.
21
It is defined as
Energy Payback Time ¼Emat þEmanuf þEtrans þEinst þEEOL
ðÞ=Eagen=ηG
ðÞEO&M
ðÞ,
where Emat is the primary energy demand to produce materials com-
prising PV system; Emanuf is the primary energy demand to manufac-
ture PV system; Etrans is the primary energy demand to transport
materials used during the life cycle; Einst is the primary energy
demand to install the system; E
EOL
is the primary energy demand for
end-of-life management; Eagen is the annual electricity generation;
E
O&M
is the annual primary energy demand for operation and mainte-
nance; and η
G
is the life-cycle grid efficiency, the average primary
energy to electricity conversion efficiency at the demand side
In this paper, the generalized calculations of EPBT (and also EROI
as defined in the next section) are based on an average thermal to elec-
tric energy conversion efficiency of 30%, which represents a common
grid mix predominantly reliant on thermal technologies. This value may
be low in today's transitioning to high-efficiency gas turbines and
renewable energy generation but is used as a reference case that allows
comparisons with most other literature studies.
12,23
These values can
be readily updated for regions of higher grid mix efficiencies.
24
2.2 |Net energy analysis
NEA is a scientific methodology useful to evaluate the performance of
energy production systems because it measures how effective a sys-
tem is at exploiting primary energy resources and converting them
into usable energy carriers. 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, after accounting for all the energy
consumption and losses occurring along process chains (such as
extraction, transformation, and delivery) and any additional energy
investments that are required in order to carry out the chain of pro-
cesses in the life cycle of a system.
25–28
The principle metric of NEA is the EROI, which is calculated as
the ratio of the energy delivered to society to the sum of energy car-
riers diverted from other societal uses. In this paper, EROI has been
calculated both in terms of primary energy (EROI
PE
) and electricity
delivered (EROI
el
). Because EROI
PE
(as EPBT) depends also on the
specific grid efficiency, in this work, a sensitivity analysis of different
grid efficiencies has been provided, considering future scenarios in
which a large penetration of renewables into the electric grids is
achieved, in line with global decarbonized targets.
24,28
EROI
PE
is defined as:
EROIPE ¼lifetime=EPBT ¼EROIel=ηG
3|ANALYZED SYSTEMS AND
ASSUMPTIONS
The analyzed PV systems are composed of PV panels and balance of
system (BOS) (mechanical and electrical components such as inverters,
transformers, and cables, as well as system operation and mainte-
nance). As mentioned in the introduction, the most mature PV module
technologies have been considered, namely, sc-Si and mc-Si.
The associated manufacturing steps described by the life-cycle
inventory (LCI) data are shown in Figure 1.
29
The PV system is com-
pleted by the BOS, that is, mounting and supporting structures, power
electronics, and cables.
The LCA starts by normalizing life-cycle indicators in terms of m
2
of PV module, which is useful to capture directly the material and
energy utilization improvements over the years, it proceeds with using
rated power (kWp) of modules as the functional unit, to capture the
variation in module efficiencies; and subsequently is expressed in
terms of KWh, at the location of deployment, taking into the account
the PV system lifetime, the performance ratio (PR), and the solar irra-
diation conditions.
2FTHENAKIS AND LECCISI
The PV commercial efficiencies and PR are based on the latest
Fraunhofer report 2020.
2
The lifetime of PV systems is fixed at 30 years, according to the
IEA guidelines,
21
and the deployment in regions of low, medium, and
high irradiation (1000, 1700, and 2300 kWh/m
2
/year) has been
included in the analysis.
End of life (EOL) management and recycling were not included
in the current analysis because we lacked data on optimized
recycling scenarios to represent realistic collection rates and material
recovery fractions in large scales of recycling. However, including
the recycling of the PV components may result in improving the
overall energy and environmental performance as well as economic
benefits due to the high value of recycled aluminum, silicon, and
copper.
30,31
Also, the contribution of energy storage is not included
in our analyses because it is best assessed at the grid level.
32–34
However, it has been estimated that the benefits of PV when dis-
placing conventional thermal electricity (in terms of carbon emis-
sions and energy renewability) are not materially affected by the
addition of lithium-ion battery (LIB) storage.
35
Specifically, a compre-
hensive life-cycle assessment of a 100-MW ground-mounted PV
system with 60 MW of lithium manganese oxide (LIB)—under a
range of irradiation (1000, 1700, and 2300 kWh/m
2
/year) and stor-
age scenarios (2, 4, and 8 h)—shows that EPBT and life-cycle GWP
are marginally affected (increasing from 7% to 30%) with respect to
those of PV without storage. Hence, in terms of carbon emissions,
energy renewability, and net energy performance, PV's significant
advantages over all conventional thermal power generators are esti-
mated to remain unaffected by the deployment of even substantial
amounts of LIB storage.
35
The analysis was performed using the LCA software package
SimaPro 9 (Pré Consultants, Amersfoort, The Netherlands), and impact
assessment was performed by means of the Centrum voor
Milieukunde Leiden (CML) method
36
developed by Leiden University
in the Netherlands.
37
4|LIFE-CYCLE INVENTORIES AND DATA
SOURCES
The LCI collection is a fundamental stage in LCA because the accuracy
of each analysis strictly depends on the data representativeness. In
order to be as accurate as possible, all the performance indicators
were calculated based on the same underlying inventory data. The
main background data source was the Ecoinvent V3 Database
(Ecoinvent, Zurich, Switzerland),
38
and whenever needed, the data
were adapted to the actual production conditions. Specifically, the
Chinese electric mixture was used in the Si supply chain and for PV
module production because the Chinese production represents the
higher share of the current market.
2
Also, the latest available data in
terms of electricity production have been assumed according to the
US Energy Information Administration
39
and have been implemented
in the calculations because they influence the amount of primary
energy ultimately required for each production process, as well as the
associated environmental impacts.
Regarding the foreground inventory, all the impacts were esti-
mated based on the latest available data—the IEA-Photovoltaic Power
Systems (PVPS) Task 12 Report,
40
which have been compared with
the previous data sources released by the same entity.
41
As typical, BOS data represent ground-mounted
installations.
12–42
5|RESULTS AND DISCUSSION
Figure 2 shows the CED reduction expressed per m
2
of PV panels for
the two c-Si-based technologies, according to production in China.
The stacked bars show the individual breakdown for each life-cycle
stage; these are (1) solar-grade and metallurgical-grade silicon,
FIGURE 1 Flow diagram for manufacturing single-crystalline Si
(sc-Si) and multicrystalline Si (mc-Si) photovoltaic (PV) systems. BOS,
balance of system; Cz, Czochralski; mg-Si, metallurgical-grade silicon;
SoG-Si, solar-grade silicon
FIGURE 2 Cumulative energy demand (MJ/m
2
) reduction in the
single-crystalline Si (sc-Si) and multicrystalline Si (mc-Si) photovoltaic
(PV) panel manufacturing with the breakdown of each life-cycle
stages. Chinese electricity grid is assumed for all stages. Thicknesses
are listed for all PV panel production [Colour figure can be viewed at
wileyonlinelibrary.com]
FTHENAKIS AND LECCISI 3
(2) Czochralski ingot or multi-Si ingot, (3) sc-Si or mc-Si wafer, (4) PV
cell, and (5) PV panel.
Overall, results show approximately a 46% and 20% CED reduc-
tion (per m
2
) in the current sc-Si and mc-Si PV panel manufacturing,
respectively, compared to 2015 data. In particular, for sc-Si panels,
significant improvements are shown in the Czochralski crystal growth
process and single-Si wafer, which currently require about 260 (80%
reduction) and 112 MJ/m
2
(61% reduction), respectively. For mc-Si
panels, the main benefits arise from the multi-Si and multi-Si wafer
production stages, which have approximately 69% and 81% lower
CED than previously reported estimates.
Reduced thicknesses and reduced kerf losses (i.e., silicon
manufacturing waste) over the years are taken into account in this
comparative assessment. As shown in Table 1, this significant
improvement in the c-Si production is mainly due to a combination of
1. reduced thickness, from 200 μm in 2015 to 170 (sc-Si) and 180 μm
(mc-Si) in the 2020 productions;
2. reduced kerf losses, from 145 μm for slurry-based sawing to
65 μm in 2020, using industrial diamond manufacturing (2020 data
included also additional losses that are 20.5 μm); and
3. reduced electricity demand in the sc-Si and mc-Si wafer stages,
which it is currently 4.76 (for sc-Si) and 5.56 kWh/m
2
(for mc-Si).
This new life-cycle assessment also includes a correction in the
2015 IEA PVPS LCI data in the solar-grade Si to wafer allocation
stages, in which the accounting of recycled silicon was inconsistent.
The 2015 LCI database assigned 1580 g of Cz-Si per m
2
of sc-Si
wafer, whereas the allocation of mc-Si was 1020 g/m
2
; recycling was
accounted in mc-Si but not in sc-Si wafering.
41
It appears that the
underlying assumption in these previous results was that the balance
of silicon feed would be recycled material for which, incorrectly, there
were assigned zero energy and environmental impacts. The effect of
this inconsistency was aggregated in the wafer production stage.
These allocations have been corrected in the 2020 IEA PVPS LCI
report
40
and are used in the current analysis. As listed in Table 1, the
current reported silicon demand is 595 and 634 g/m
2
for sc-Si and
mc-Si PV panels, respectively.
43
As shown in this table, electricity utili-
zation in the solar silicon and wafer production has been reduced over
the last 6 years by 50% or more, whereas electricity utilization in cell
and module production has increased over the same period. However,
the sum of electricity requirements for wafer, cell, and module pro-
duction has not changed as much; it declined from 43.8 to 36.5 kWh/
m
2
and from 39 to 37.3 kWh/m
2
for sc-Si and mc-Si PV correspond-
ingly. Thus, it becomes apparent that there has been a difference in
the stage-by-stage electricity allocation between the 2015 and 2020
databases.
43,44
Figure 3 shows the CED comparison expressed per kWp of PV
modules for 2015 and 2020 production of crystalline-based technol-
ogy. The average efficiency of PV and modules in the market—which
needs to be included when the impacts are expressed per kWp—is
based on the reports published by the Fraunhofer Institute for Solar
TABLE 1 Comparison between key parameters of crystalline silicon manufacturing in China
Unit
Single-crystalline Si
(2015)
Single-crystalline Si
(2020)
Multicrystalline Si
(2015)
Multicrystalline Si
(2020)
Thickness μm 200 170 200 180
Kerf loss μm 145 65 145 65
Silicon demand for wafering g/m
2
1580 595 1020 635
Electricity for MG-silicon kWh/kg 11 11 11 11
Electricity for SoG-Si kWh/kg 110 49 110 49
Electricity for Cz ingot kWh/kg 68.2 32 - -
Electricity for mc-Si ingot kWh/kg - - 15.5 7
Electricity for wafering kWh/m
2
25.7 4.76 20.8 5.56
Electricity for cell production kWh/m
2
14.4 17.7 14.4 17.7
Electricity for panel production kWh/m
2
3.73 14 3.73 14
FIGURE 3 Cumulative energy demand (MJ/kWp) reductions in
the single-crystalline Si (sc-Si) and multicrystalline Si (mc-Si)
photovoltaic (PV) systems with the breakdown of each life-cycle
stages. Chinese electricity grid is assumed for all stages. Module
efficiencies are listed for each PV technology [Colour figure can be
viewed at wileyonlinelibrary.com]
4FTHENAKIS AND LECCISI
Energy Systems.
2
They are as follows: 20.5% and 18% for sc-Si and
mc-Si modules, respectively, in 2020, up from 17% and 16% in 2015.
The resulting CED of PV system (modules plus BOS) per rated power
is 13,615 and 14,797 MJ/kWp for sc-Si and mc-Si PV system, respec-
tively, which represent a reduction of approximately 48% and 24% of
previous life-cycle energy consumptions. It is noted that the mounting
and support structure data have not been changed and the reduction
is due solely due to the increased module efficiencies.
Figures 4 and 5 show, respectively, the GWP and AP impacts, all
expressed per kWp. Comparisons between the 2015 and 2020 PV
systems are shown along with the contributions of each life-cycle
stage.
These new results show that the current carbon emissions of sc-
Si and mc-Si PV systems range from 1010 to 1087 kgCO
2
eq/kWp,
whereas the AP impacts vary from 11 to 12 kgSO
2
eq/kWp. Results
clearly show the environmental improvement in the single-crystalline
PV system production, for which the impacts have been reduced from
49% (in terms of GWP) and 42% in terms of AP impacts. Regarding
the mc-Si PV systems, GWP impacts are down by approximately 32%,
whereas AP impacts are reduced by 14%. As shown, this significant
environmental impact reduction is mainly attributed to material utili-
zation improvements at the solar silicon and wafer production stages.
Regarding the BOS contribution, it is generally low in terms of
carbon emissions, but relatively higher in acid emissions, mainly due
to the amount of copper and aluminum required.
Figures 6 and 7 provide GWP and AP impacts of current silicon
PV systems, expressed per kWh, assuming a PR of 0.85, and a lifetime
of 30 years. This PR represents the ratio of actual to rated module
efficiencies, in ground-mount, fixed latitude-tilt installations. These
figures show results in regions of low, moderate, and high irradiation
levels, namely, 1000, 1700, and 2300 kWh/(m
2
* year).
It is shown that the GWP caused by crystalline-based PV systems
ranges from 17 to 18 gCO
2
eq/kWh when installed at high irradia-
tions, 23 to 25 gCO
2
eq/kWh at moderate irradiations, and 40 to
43 gCO
2
eq/kWh at low irradiations. The lowest AP impact
(0.19 gSO
2
eq/kWh) is that of sc-Si PV installed at 2300 kWh/
(m
2
* year), whereas the highest (0.47 gSO
2
eq/kWh) is mc-Si PV
located at 1000 kWh/(m
2
* year).
FIGURE 4 Global warming potential (kgCO
2
eq/kWp) reduction in
the single-crystalline Si (sc-Si) and multicrystalline Si (mc-Si)
photovoltaic (PV) systems with the breakdown of each life-cycle
stage. Chinese electricity grid is assumed for all stages. Module-rated
efficiencies are listed for each PV technology [Colour figure can be
viewed at wileyonlinelibrary.com]
FIGURE 5 Acidification potential (kgSO
2
eq/kWp) reductions in
the single-crystalline Si (sc-Si) and multicrystalline Si (mc-Si)
photovoltaic (PV) panel manufacturing with the breakdown of each
life-cycle stages. Chinese electricity grid is assumed for all stages.
Ground-mounted balance of system (BOS) data source is unchanged.
Efficiencies are listed for each PV technology [Colour figure can be
viewed at wileyonlinelibrary.com]
FIGURE 6 Photovoltaic (PV) power plant global warming
potential (GWP) (kgCO
2
eq/kWh), under three irradiation levels. Small
symbols: 1000 kWh/(m
2
* year), medium symbols: 1700 kWh/
(m
2
* year), and large symbols: 2300 kWh/(m
2
* year). Performance
ratio: 0.85. Lifetime: 30 years. Module efficiencies: 20.5% for single-
crystalline Si (sc-Si) and 18% for multicrystalline Si (mc-Si) [Colour
figure can be viewed at wileyonlinelibrary.com]
FTHENAKIS AND LECCISI 5
As discussed in Section 2.1, the EPBT is estimated from the
energy consumed and the electricity generated over the system's life
cycle. Figure 8 shows a most significant EPBT improvement,
corresponding to almost halving estimates based on the 2015 data.
Currently, for sc-Si PV systems, it takes from 0.6 months to 1.3 years
(depending on the assumed irradiation) to return an amount of elec-
tricity that is equivalent to the primary energy invested, whereas for
mc-Si PVs, it takes from approximately 0.6 months to 1.5 years. It
should be noted that these values assumed a conventional fuel to
electric grid efficiency (30%) that is representative of a generic electric
mix mostly based on thermoelectric technologies. For assessing indi-
vidual PV installations, one should calculate the specific grid efficiency
based on the up-to-date regional grid mix composition.
FIGURE 7 Photovoltaic (PV) power plant acidification potential
(AP) (kgSO
2
eq/kWh), under three irradiation levels. Small symbols:
1000 kWh/(m
2
* year), medium symbols: 1700 kWh/(m
2
* year), and
large symbols: 2300 kWh/(m
2
* year). Performance ratio: 0.85.
Lifetime: 30 years. Module efficiencies: 20.5% for single-crystalline Si
(sc-Si) and 18% for multicrystalline Si (mc-Si) [Colour figure can be
viewed at wileyonlinelibrary.com]
FIGURE 8 Energy payback times (years) reductions from 2015 to
2020, under three irradiation levels: 1000 kWh/(m
2
* year), medium
symbols: 1700 kWh/(m
2
* year), and large symbols: 2300 kWh/
(m
2
* year). Efficiencies: 17% and 20.5% for 2015 and 2020 single-
crystalline Si (sc-Si) photovoltaic (PV), respectively, and 16% and 18%
for 2015 and 2020 multicrystalline Si (mc-Si) PV, respectively.
Performance ratio: 0.85. η
grid
=0.30 [Colour figure can be viewed at
wileyonlinelibrary.com]
FIGURE 9 Energy return on investment (in terms of electricity)
reductions from 2015 to 2020, under three irradiation levels:
1000 kWh/(m
2
* year), medium symbols: 1700 kWh/(m
2
* year), and
large symbols: 2300 kWh/(m
2
* year). Efficiencies: 17% and 20.5% for
2015 and 2020 single-crystalline Si (sc-Si) photovoltaic (PV),
respectively, and 16% and 18% for 2015 and 2020 multicrystalline Si
(mc-Si) PV, respectively. Performance ratio: 0.85. Lifetime: 30 years
[Colour figure can be viewed at wileyonlinelibrary.com]
FIGURE 10 Energy return on investment (in terms of primary
energy) reductions from 2015 to 2020, under three irradiation levels:
1000 kWh/(m
2
* year), medium symbols: 1700 kWh/(m
2
* year), and
large symbols: 2300 kWh/(m
2
* year). Efficiencies: 17% and 20.5% for
2015 and 2020 single-crystalline Si (sc-Si) photovoltaic (PV),
respectively, and 16% and 18% for 2015 and 2020 multicrystalline Si
(mc-Si) PV, respectively. Performance ratio: 0.85. η
grid
=0.30.
Lifetime: 30 years [Colour figure can be viewed at wileyonlinelibrary.
com]
6FTHENAKIS AND LECCISI
Figure 9 shows the EROI—expressed in terms of electricity—
improvement over the years. At 2300 kWh/m
2
/year, the resulting
EROI
el
ranges from 16 to 14 for sc-Si and mc-Si PV systems, respec-
tively, showing in both cases significant improvements compared with
previous values. When the EROI is calculated in terms of primary
energy—assuming a conventional grid efficiency—it ranges from
52 (for sc-Si PV systems) to 47 (for mc-Si PV systems), as shown in
Figure 10.
6|SENSITIVITY ANALYSIS ON GRID
EFFICIENCY IMPROVEMENTS AND
MANUFACTURING ELECTRICITY GRID MIX
CHANGES
As nations are embarking on a transition to clean renewable energy,
we herein examine the impact on EROI
PE
of improved grid mix com-
positions. A case in point is California where the grid is projected to
include 80% of renewable energy by 2030. Thus, we conducted a sen-
sitivity analysis comparing EROIs under a conventional grid with those
at current and projected California grid efficiencies. The results are
FIGURE 11 Sensitivity analysis on energy return on investment
in terms of primary energy (EROI
PE
), considering the variability of grid
efficiency (η
grid
), which is assumed to be 0.30 (conventional grid
efficiency), 0.48 (calculated 2019 California's grid efficiency), and 0.7
(projected California's grid efficiency with 80% of renewable
electricity). Assumed irradiation is 2300 kWh/(m
2
* year) [Colour
figure can be viewed at wileyonlinelibrary.com]
FIGURE 12 Sensitivity analysis on grid mix compositions: (A) 2014 and 2019 Chinese electricity mixes and (B) global warming potential
(GWP) reductions—expressed as kgCO
2
eq/kWp—due to electricity grid mix changes from 2014 to 2019. Efficiencies are assumed as follows:
single-crystalline silicon (sc-Si): 20.5% and multicrystalline Si (mc-Si) 18% [Colour figure can be viewed at wileyonlinelibrary.com]
FTHENAKIS AND LECCISI 7
shown in Figure 11. Specifically, PV EROI
PE
results calculated with
η
grid
=0.3 have been compared with the following:
1. η
grid
=0.48, which represent a 2019 grid efficiency in California,
and
2. η
grid
=0.7, which is the projected 2030 grid efficiency in
California, assuming 80% of renewable electricity.
24
In all the above cases, the assumed irradiation is 2300 kWh/
(m
2
* year) (south California).
Results of these simulations show a declining EROI with increas-
ing grid efficiency as solar electricity replaces less dirty grid electricity.
However, even with 80% penetration of renewable electricity into the
California's grid (52% of which is generated by PV), the EROI
PE
of c-Si
PV systems is still above 20, whereas in a current Californian grid mix,
it is approximately 30.
We also examine the impact of changing grid mixture in China
where most of the c-Si PV production is taken place. As shown in
Figure 12A, the Chinese electricity grid mix composition has been
slightly changed over the 5 years (2014–2019). More specifically, PV
and wind's electricity generation shares have been increased from
1% to 3% and from 3% to 6% respectively, whereas the electricity
produced by coal power plants has been reduced from 73% in 2014
to 65% in 2019. Overall, the total Chinese electricity production has
increased from 5388 billion to 7136 billion kWh. Because all these
changes affect the amount of primary energy ultimately required for
the manufacturing production process and the associated
environmental impacts, Figure 12B provides the resulting GWP
variations. Results show a reduction of approximately 1% in the
resulting carbon emissions. The corresponding life-cycle η
grid
in China
in 2019 is 0.35.
7|CONCLUSION AND FUTURE
RESEARCH NEEDS
This paper describes the sustainability improvements over the last
5–7 years in the life cycles of c-Si PV systems which currently
comprise about 95% of the PV market. The most significant
achievements are observed in single-crystalline PV where life-cycle
energy consumption and carbon and acidic emissions were reduced
by approximately 49%. Also, significant improvements are assessed
in the life cycle of multicrystalline PV where life-cycle CED was
reduced by 24%, carbon emissions by 32%, and acid gas emissions
by 14%. Contribution analysis shows that the major improvement
was obtained at the wafer production, due to reduced wafer thick-
ness and kerf loss. From a NEA perspective, EROI
PE
for PV installed
at 2300 kWh/m
2
/year ranges from 52 to 47, respectively, for sc-Si
and mc-Si PVs, whereas PV systems deployed in low irradiation
locations (i.e., 1000 kWh/m
2
/year) correspond to EROI
PE
in the
range of 21 to 22.
Sensitivity analysis on the electricity grid mix composition shows
that any increase of renewable penetration into the manufacturing
grid corresponds to a reduction of carbon emissions, while accompa-
nied by reduction of the EROI. More specifically, for installations in
California (where 80% penetration of renewable electricity is
expected by 2030), the EROI
PE
of c-Si-based PV systems is reduced
to about 21, which still reflects a large net energy return on energy
invested.
Future research will address ongoing PV material utilization and
efficiency improvements that result in life-cycle impact improve-
ments. In addition, future research should entail examination of
metal resource availability in scenarios with ultrahigh penetration
of renewables and associated life-cycle human and eco-toxicity
impacts.
AUTHOR CONTRIBUTIONS
Vasilis Fthenakis conceived and designed the study. Enrica Leccisi per-
formed the analysis and produced the results and graphics. Enrica Lec-
cisi and Vasilis Fthenakis analyzed the data. Enrica Leccisi wrote the
first draft of this manuscript. Vasilis Fthenakis probed into the details
and refined the manuscript.
NOMENCLATURE
BOS balance of system
CED cumulative energy demand
EPBT energy payback time
EROI energy return on investment
EROI
el
energy return on investment in terms of electricity
EROI
PE
energy return on investment in terms of primary energy
GWP global warming potential
LCA life-cycle analysis
LCI life-cycle inventory
mc-Si multicrystalline silicon
NEA net energy analysis
PR performance ratio
sc-Si single-crystalline silicon
η
G
grid efficiency
ORCID
Enrica Leccisi https://orcid.org/0000-0002-4166-8555
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How to cite this article: Fthenakis V, Leccisi E. Updated
sustainability status of crystalline silicon-based photovoltaic
systems: Life-cycle energy and environmental impact
reduction trends. Prog Photovolt Res Appl. 2021;1–10. https://
doi.org/10.1002/pip.3441
10 FTHENAKIS AND LECCISI
