Content uploaded by Abdullah Marashli
Author content
All content in this area was uploaded by Abdullah Marashli on May 03, 2023
Content may be subject to copyright.
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
Comparing the Global Warming Impact from Wind,
Solar Energy, and Other Electricity Generating
Systems through Life Cycle Assessment Methods (A
Survey)
Abdullah Marashli * , Al-Mothana Gasaymeh‡, Mohammad Shalby*
*Mechanical Engineering Department, Al-Hussein Bin Talal University, PO box 20, Maan, Jordan
(a.marachli@ahu.edu.jo, mothana777@yahoo.com, mohammad.shalby@ahu.edu.jo)
‡ Corresponding Author; Al-Mothana Gasaymeh, PO box 20, Maan, Jordan, Tel: +962772155238,
Fax: + +962 32179050,mothana777@yahoo.com
Received: 21.04.2022 Accepted: 08.06.2022
Abstract- This study compares Greenhouse Gases (GHGs) emissions as CO2 equivalent per one kilowatt-hour of
two types of renewable power generation technologies (solar and wind) compared to other traditional power generation
technologies through life cycle assessment methods. Related to Global Warming Potential (GWP), the produced quantities
of GHGs of each generation method vary through the lifecycle. For wind and solar power, the release of GHGs reached
between 70 and 98% during manufacturing (including raw materials) and decommissioning. The recycling stage may play a
crucial role in decreasing the impact of GHGs by up to 40%. -Adopting emissions calculated by the Life Cycle Approach
(LCA) with electrical generation from solar and wind ways allows a fair comparison per (CO2) eq/ KWh basis and factors
affecting each LCA stage. For the two studied systems, wind power emits the least amount of (CO2) eq/ KWh, with
average values of 13.91 and 12.7 g CO2eq/kWh for offshore and onshore farms, respectively. While photovoltaic has the
highest contribution to GHGs emissions, with a mean value of 23.39 g for CdTe, it is followed by 33.14, 39.93,
43.84,49.33, 50.76 for a-Si, m-Si, CIGs, CIS and sc-Si g (CO2) eq/ KWh, respectively. Concentrated Solar Power (CSP)
occupied the medium contribution of 35.6 g for the tower and 30.94 g (CO2) eq/ KWh for the trough. Compared to fossil
fuel-fired systems, the average (CO2) eq/ KWh is 936 g for coal-fired, 730 g for oil, and 502 for gas-fired power systems.
Replacing one kilowatt-hour of coal or oil-generated electricity with one kilowatt-hour of wind power can save up to 923 or
716 g (CO2) eq/ kWh.
Keywords Global Warming Impact, Wind, Solar Energy, Life Cycle Assessment, Survey
1. Introduction
The issue of global warming is one of the challenges
facing humanity in the coming decades. Mainly,
conventional energy sources, which constitute 84.3% of
primary energy sources (i.e., 33.1% from oil; 27% from coal;
and 24.3% from gas), are responsible for releasing these
gases into the surrounding environment. Carbon dioxide
produced during fuel combustion is the cause of global
warming, as its quantities increase with the increasing
demand for energy, especially electrical energy, as one of the
final forms of energy use. The amount of electrical energy
generated during 2020 reached approximately 25.85 TWh,
more than 60% of which comes from burning fuel, and it is
responsible for putting more than 70% of CO2 into the
atmosphere [1].
According to the reference [2] about CO2 status, global
energy consumption climbed at over twice the average rate
since 2010, led by natural gas, despite double-digit growth
from solar and wind energy sources. CO2 emissions released
from the energy sector increased by 1.7 percent to a new
level of 33.1 Gt CO2, almost coming from 83.1% of fossil
fuels as primary energy resource [3]. While GWP from all
conventional fuels has grown, approximately two-thirds of
the rise was attributed to the electricity sector. Coal use in
electricity generation alone exceeded 10 Gt CO2, primarily in
Asia. China, India, and the United States are responsible for
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
900
the net increase in emissions, accounting for 85 percent of
the total [2].
As reference [4] noted and confirmed by reference [1]
on the published assessment in the executive summary and is
that, in the first quarter of the year 2020 compared with the
first quarter of year2019, worldwide energy demand was
dropped by 5%, with CO2 emissions related to energy
generation falling by 6-7%, depending on fuel type,
throughout the pandemic Covid-19. Emissions from coal fell
by 8%, oil by 4.5 %, and natural gas emissions by 2.3 %. The
drop in annual CO2 1 rate by 2.1- 2.4 Gt is similar to ten
years ago. In the next decade, CO2 emissions will exceed
2019 levels under the Stated Policies Scenario (STEPS),
reaching 36 Gt, which will cause global warming of 1.65
degrees Celsius. However, the IEA reported in its Global
Energy Review on April 20, 2021 [5] shows that global
carbon emissions will grow by 1.5 billion tones, representing
5 percent, in 2021, to reach more than 33 billion tones due to
the comeback of coal use in the power sector. Such a
percentage of CO2 concentration represents the second-
largest increase in history
To reach a very low GWP by 2050, CO2 emissions-
related energy fields would have to be cut by about 3.5
percent yearly from 2021 until 2050. Such reduction
accounts for 70% compared to current levels [6], [3]. Most
mitigation scenarios until 2050 are based on large-scale and
accelerated deployment of so-called low-carbon energy
technologies, which emit less CO2 than the conventional
fossil-fuel power generating counterparts. Overall, it remains
far below the levels required to reach the Glasgow
Agreement Commitments (COP26) in 2021.
The goal of net-zero emissions by 2050 would require
substantial additional efforts over the next ten years. For
instance, joint to the Paris Climate Action and abide by the
pledges [1] that require replacing coal-fired technologies
with less GHG impact. Reliable and trustworthy outputs are
needed to assist leaders and decision-makers in making the
right energy policies. These data can be obtained by
continually reviewing published research that uses the latest
relevant data and software.
2. Objectives and Methodology
The goal of this study is to collect and analyze data to
compare the life cycle of GHG emissions of wind energy
(onshore and offshore), photovoltaic power (rooftop and
utility), and Concentrated Solar Power (CSP) used for
electricity generation based on a survey of the literature. In
addition, obtained results are compared to some other
traditional energy sources such as Coal, Natural gas, Hydro,
Biomass, Oil, and Nuclear power.
The current literature review seeks to answer the
following research questions:
• Which power generation technology has the most
influence on total GWP?
• Which is the highest and which is the lowest?
• Where do the emissions fall throughout a lifecycle?
• Explain what reasons generate variability in overall
Greenhouse gases in the literature.
The current study is a literature review research study.
This study aimed to present a survey of research related to
the global warming impact of wind, solar energy, and other
electricity-generating systems through life cycle assessment
methods. For the study, a group of research databases in
English languages were selected to be searched for studies
that related to the global warming impact of various
electricity-generating systems. The examined scientific
studies were collected from different sources that include
Organizations such as (IEA), World Energy Council (WEC),
Our World in Data Website, BP, World Nuclear Association
(WNA), IRENA, IPCC, NREL, Ostfold Research, as well as
Science Direct, Wiley Online Library, Taylor and Francis,
Elsevier, and Google Scholar. Furthermore, a snowballing
technique has been used to find additional papers from the
list of references for the identified research papers.
To accomplish the goal of the current study, the
following keywords were used in the searching process in the
previously mentioned sources: Life Cycle Assessment
(LCA), GHG emissions, GWP, carbon dioxide, renewable,
concentrated solar power, the nuclear, wind, offshore,
onshore, photovoltaic, hydropower, geothermal, biomass,
non-renewable, fossil fuel, coal, oil, natural gas, energy,
power, electricity, combined-cycle. The search was bounded
from 2005 until the completion of writing this research in
2022.
The previous studies have been processed and
categorized. Thus, only factual, accurate, and relevant data
were used in this study. On the other hand, some related
studies were excluded due to the lack of recentness,
relevance, completeness, and originality. The reference
evaluation unit used in this study gCO2equivalent per kWh
power generated is equivalent to GWP unit.
3. Literature review
Due to the uniqueness of lifecycle analysis assumptions
for each power generation system, the consequences also
should be different according to input data. The choice of
global warming potential value is important to understand,
for example, which global warming potential coefficient is
used for methane. Depending on the choice of GWP for
CH4, the natural gas LC emissions could result in either 31%
more or 40% less than coal LCI due to the high leakage rate
of CH4. A research study by reference [7] claimed that
greenhouse gas (GHG) emissions from natural gas could be
twice that of coal, mostly due to fugitive emissions by
leakage from hydraulic fracturing. "100-yr value is estimated
to be 25 (times higher than CO2) by IPCC; the 20-yr value is
estimated to be 72". Technology improvements, energy
efficiency (EE), electricity supply mix, and other conditions
should be included more accurately, from the extraction
stage of raw material, including processing, transmission,
storage, and end-use. If the opposite, emissions data are
sparse and uncertain, which means the tremendous need for
improvement to obtain actual values that mimic reality.
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
901
The current study used LCA, a methodology for
analyzing environmental consequences associated with all
phases of the life cycle of the commercial products, to give a
full comparison across power generating systems in terms of
their global warming impact. The examined power
generating systems include wind, photovoltaic, concentrating
solar power, and other power generating systems other
traditional energy sources such as Coal, Natural gas, Hydro,
Biomass, Oil, and Nuclear power.
3.1 Wind power
The literature review includes studies that evaluated
wind turbines from a life cycle perspective, covering onshore
and offshore farms. Furthermore, studies that compiled
average wind power results from earlier research were
considered. The analysis includes 58 studies published
between 2005 and 2020, as given in Table (1). Generally, the
wind power life cycle is divided into four phases: 1) wind
turbine fabrication, which involves mining, processing
materials, and manufacturing; 2) wind turbine construction,
which includes transporting components, constructing
foundations and substations, and assembling structural
supporting; 3) operation and maintenance; and 4)
decommissioning, which includes deconstruction, disposal,
and recycling [8, 9, 10, 11, 12].
Two wind turbine systems, 4.5MW and 250W, were
chosen by reference [13] in south France to evaluate their
GHG emissions for all life cycle phases. The mean values for
the 4.5W and 250W wind turbines were 15.8 g and 46.4 g
CO2eq/kWh, respectively, illustrating that as power
increases, the rate of GHG emission value decreases
significantly. Furthermore, employing trains instead of
vehicles as transportation reduces climate change emissions
for 250 W from 23% to 2% and can minimize the impact on
4.5MW turbines by up to 20%.
Reference [14] conducted a review of 63 LCAs
covering the period between 1990 and 2010 and concluded
that GHG emissions from wind power differed from 4.6 to
55.4 g CO2eq/kWh. The lower value was for a higher
capacity turbine (3 MW) and the maximum for 30 kW. This
average value dropped as turbine capacity increased from
45.0 to 10.4 g CO2eq/kWh. Infrastructure related to steel
production was the main contributor to the overall GHG
emissions. Furthermore, 44 studies analyzed by reference
[15], ranging from large to small turbines, concluded an
average GWP unite of 19 g CO2eq/kWh. Reference [16]
established GHG emissions of 7–10 g CO2eq/kWh,
including end-of-life that contributes around 30%. The
manufacturing stage contributes of 94.7% with foundations
(10 %), tower (25– 30 %), cabling (20 %), nacelle (15 %)
and blades (10–15 %), where the plant setup 1.75% and
operation 3.5% of total global warming potential. The
transportation share of GHG emissions during the total life
cycle was 8%. Reference [17] observed that avoiding the
shipment of some components overseas and substituting
them with locally manufactured components might reduce
transportation GHG emissions by 22%.
The comprehensive review was conducted by reference
[18] for 19 studies covering Wind Energy Technologies
(WETs), including 14 studies for onshore and 5 studies for
offshore turbines. These studies revealed that the lowest
mean values ranged from 5.3–13 g CO2eq/kWh between
minimum and maximum of 8–124 GWP units for both types
of wind turbines. The extraction of raw materials (30 %),
turbine production (25 %), transportation (10 %), and
emissions-related with installation on organic-rich soils (30
%), where these soils were removed and transported, are the
primary contributions to the overall carbon footprint.
A study conducted by reference [8], screening 153
lifecycle studies, found that 22 studies are mainly linked to
and liable for GHG emissions from the wind. The mean
value reported was 34.1 g CO2eq/kWh, for low and high
values was 0.4 & 364.8 g CO2eq/kWh over life span turbine
between 20-30years. The first phase contributed to almost 71
% of GWP, followed by installation (24 %), operation
(slightly less than 24 %), decommissioning, and recycling
(19.1 %). Offshore estimations also revealed a decreased
mean intensity.
Five types of wind systems utilized for generating
electricity, included in 29 studies, represented 74 wind
system cases designated to estimate the life cycle (GHG)
emissions by reference [19]. Three case studies of onshore
horizontal axis machines with a small capacity of fewer than
0.1 megawatts (MW); 4 case studies of onshore horizontal
axis machines with a capacity is between 0.1 and 0.25 MW;
58 case studies of onshore horizontal axis machines with a
large capacity is between 0.25 and 5 MW; 8 case studies of
offshore horizontal axis machine with large capacity; and
finally one case study of onshore vertical axis machine with
small capacity. The mean life cycle GHG emissions resulting
were 38.67, 11.75, 15.98, 12.9, and 46.4 gCO2e/kWh,
respectively. Onshore turbines had higher GHG emissions
(15.98 ±17.12 gCO2eq/kWh) than offshore ones (12.9 ± 7.61
gCO2eq/kWh) for turbines capacity greater than 0.25 MW.
At three different sites, deep-water, shallow-water, and
onshore, in Texas, USA, the proportional sharing of
individual steps to life cycle impacts were studied [20]. The
comparison analysis results show that the extraction of
material and related processes would be the leading phase for
GHG emission, reaching (82 %) for deep-water, 72 % for
onshore, and 58 % for shallow water. The other stage for
onshore was followed by maintenance and operation (13.8
%) and fabrication (9 %). Steel recycling could result in a
20% reduction in average environmental impact. (GHG)
values for the onshore location varied from 5–7
gCO2eq/kWh, 6–9 gCO2eq/kWh for the shallow-water, and
6–8 gCO2eq/kWh for the deep-water location. For the same
categories, 2 MW on offshore and onshore occupied 9.3 and
7 gCO2eq/kWh, respectively. Relative values of the same
class have been obtained by two studies [9, 21].
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
902
Table 1. Summery of the analysis of 58 studies published between 2005 and 2020 realted to the generation power
from wind.
Reference
Total estimate
(g
CO2eq/kWh)
Life
(years)
height (m)
xRotor diameter
(m )
Onshor
e/
offshor
e
System/turbin
e
capacity
Location
Other
assumptions
Reference
[22]
14.8
20
55x 50
On
11 x 660 kW
turbines
Italy
Min/max 8.8
/18.5
Reference
[23]
7.65
20
55x 31
On
24 x 1.25 MW
turbines
Guangxi,
Reference
[24]
15
12
20
On
Off
Global
survey
25% capacity
factor
(44)case
studies
Min/Max
1.7/81
Reference
[25]
3.9
20
On
Enercon E40-
600 kW
Vestas V66-
1.75 MW
Vestas V-47-
660 kW
China
Mailiao,
Jhongtun
,
Chunfon
g
Reference
[26]
39.6
20
On
33x1.5 MW
Mongoli
a
Reference
[27]
29.2
468
20
On
Off
2.0 MW
2.0 MW
China
Fixed-floating
platform
Reference
[28]
2.4-7.0
20
On
2 MW
Spain
Repowering
Reference
[21]
25.5
25
90X116 m
100X126
Off
27x3.6 MW
5MW
China
10 deep 8.5.
m/s. 7.5
Reference
[29]
12.5
20
On
50 MW
China
Reference
[30]
15-29
20
On
1.5 MW
Canada
based hydrogen
production
Reference
[9]
7
20
20
On
2.3 MW
3.2 MW
Denmark
11
25
20
Off
6 MW
4 MW
Denmark
Reference
[31]
10.42
20
On
37x1.65 MW
M. Torres
Libya
Reference
[13]
15.8
46.4
20
124x113
On
On
4.5 MW
250W-micro
France
Min/max (12.1
/ 21.2)
35.8 / 58.8
Reference
[32]
15.35
20
off
All farms
USA
floating wind
energy
Reference
[33]
8.82
20
On
2 MW
Global
(German,
Chinese,
Denmark
manufact
uring)
gearless
turbine
Reference
[34]
13.4
30
Offshor
e
2 MW farm
UK
30%capacity
factor
Reference
[35]
10.69
20
Onshor
e
Ontario,
Canada
Canadian
electricity mix
(210 g CO2-
eq/kWh)
Reference
138–220
20
2x10
Onshor
e
1.5 kW
turbines
New
Zealand
electricity mix
(224 g CO2-
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
903
[36]
roof
eq/kWh),
Reference
[37]
7.1
20
80
Onshor
e
14 x 1.5 MW
turbines
Brazil
electricity mix
(64 g CO2-
eq/kWh)
Reference
38]
7.9-12.5
20
84-
108x80
Onshor
e
2.3 MW
system
Germany
avg. wind
speed 7.5-8.57
Reference
[20]
7.35- 7.09-
5.84
9.49 6.49
8.2 7.28
20
Onshor
e
Offshor
e(sh)
Offshor
e(D
1 MW 2 MW
2.3 MW
2 MW 2.3
MW
2.3 MW 5
MW
USA
Texas
electricity
mixes
Cp 35% for
onshore,
45% for
shallow-water,
and 47% for
deep-water
Reference
[19]
38.67
11.75
15.98
12.9
46.4
20
25 75)x(30-80)
Onshor
e
Onshor
e
Onshor
e
Offshor
e
Onshor
e
less than
0.1MW
0.1 and 0.25
MW
0.25 and 5
MW
0.25 and 5
MW
less than
0.1MW
Global(
Sweden,
Canada,
German,
Italy,
Taiwan
Denmark
, Japan,
Spain
USA,
France
Reference
[10]
7.3
20
155x150
Onshor
e
24x4.2 MW
German
7.0 m/s (low
wind)
Reference
[39]
9.7
9.99
20
Onshor
e
offshor
e
2 2 MW
Global
Wide range
capacity factor
Reference
[11]
4 to 45
7 to 23
20
Onshor
e
offshor
e
0.66-4.5 MW
UK
Cp 19-40%
onshore
26-54%
offshore
Reference
[40]
8.37
11.4
11.1
25
30
30
Onshor
e
Offshor
e
Offshor
e
2.5X60=150
MW
5X70=350
5X70=350
Global
-
Shallow steel
Shallow
gravity
Reference
[41]
14.4
18.4
25
30
Onshor
e
Offshor
e
Survey
(global)
Reference
[8]
3 4
Onshor
e
Offshor
e
Survey
(global)
Reference
[42]
5.27
4.22
3.53
20
25
30
78 x(83 - 87) m
Onshor
e
2x200 =400
MW,
G83 G87
USA
(Texas )
5.3
(average)m/s
(recycling not
including )
Reference
[43]
10-16.6
20
65X 70 m,
Onshor
e
1.5x76 =114
MW,
Enercon E-66
UK
Cp 21-22 %
different
turbine design
variations
Reference
[16]
7 to 10
20
Onshor
e
2x25=50-MW
V100 Grid
Streamer
Denmark
V=7-9.25 m/s ,
electricity
mixes
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
904
Reference [43] concluded that for all scenarios for
Technology Improvement Opportunities (TIO) studied, the
main contribution of all stages of lifecycle were construction
(88.6-95.5) %, operation (6.8-1.8) % and decommissioning
(5-2.7) % according to different turbine design variations.
Reference [44] has estimated an average global warming
value of 8.6 gCO2e/kWh without recycling. 90% due to the
manufacture of turbines and their accessories with the
manufacture of towers (41.0%), cables (30.0%), and rotors
(19. %), while transformers and wiring made up only 9.6%
and 0.4%, respectively.
Reference [41] comprise 54 studies. Their results were
presented by minimum, maximum, and mean values. Mean
in GHG emissions g CO2eq/kWh for onshore was 14.4 and
18.4 for offshore, respectively. Variations in GHG emissions
4.6-40.0 for onshore and 5.2-32 for offshore were found.
Reference [46] concluded that replacing 1.23 GW onshore
and 0.59 GW offshore and new installations 0.61+1.31 GW
(total 3.74GW) to fulfill the capacity objectives between
2017 and 2030 in the Danish system decreases CO2eq/kWh
from 40 to 13 g between 1980 and 2030. In 1980, the
gCO2eq/kWh values of onshore wind turbines ranged from
20 to 90, whereas in 2010, the majority of them had indicator
values ranging from 10 to 30 gCO2eq/kWh. The range of
such indicators for offshore wind turbine fleet is slightly
lower, ranging from 7 to 20 g CO2eq/kWh, which was
referred by another study [8].
Reference [32] studied the GWP impact of floating
offshore in California, United State. The model predicted
~15.35 g CO2eq/kWh with an uncertainty range of 8.58 -
30.17 g CO2eq/kWh. At the same time, the results are in
accordance with other wind energy LCA research (3.0 to 45
CO2eq g/kWh for large-scale wind farms). During life cycle
phases, first stage provides the most 40.6 % (18.3 g
CO2eq/kWh). Meanwhile, the end-of-life phase contributes
the least 20.4 % (-9.2 gCO2eq/kWh). During the fabrication
phase, the turbine and substructure were the most critical
contributors to CO2 emission, accounting for 77 % of
manufacturing stage emissions. Steel was the most important
material and energy contributor (49 %), while diesel and coal
were about (27 %).
In another study, reference [47], a comparison between the
vertical axis and horizontal axis wind turbine for low
capacity (300-500) W in Thailand over 20 years life time
concluded that the mean values of GWP unit are 12
gCO2eq/kWh and 5 gCO2eq/kWh, respectively. Other
studies examined the effect of a location wind farm in
particular countries. In a study conducted by reference
[13], they reported 16 GWP units for a turbine capacity 4.5
MW. Reference [37] found 7.1 GWP unit for 141.5 MW of
power in Brazil, reference [17] observed GHG of 16.9
gCO2-eq/kWh for turbines capacity of 1.8 MW in the United
States. Reference [9] found 7 GWP units for 2.3 MW
onshore in Denmark. Reference [27] obtained 29.2 GWP
unit for 2 MW, reference [43] found 25.5 GWP unit for
5MW offshore in China.
The value of (GWP) from [10] accomplished 7.3
gCO2eq/kWh with recycling. The impact of each main life
cycle phase was: all manufacturing steps 11.3 gCO2eq/kWh
(98.2%), Plant setup 0.1, Operation 0.2 and End-of-life -4.4
(-38%). Whereas manufacturing includes all raw material
extraction from mining to the site; plant set-up includes
onsite assembly components and roads (e.g. cranes,
generators, etc.); maintenance, service, and transportation are
all part of the operating stage; and end of life involves
disassembling recycling, and garbage disposal. The
manufacturing stage commanded the life cycle impact, where
the tower fabrication occupied (42 %), nacelle frame (8 %),
gearbox (7 %), tower foundations (15 %), rotor blades (10
%), and wiring (3 %) being the major determinants
contributing to this phase. The end-of-life phase also
contributes significantly (-38 percent) by offering
environmental credits for avoiding material processing such
as copper and steel and so on.
Reference [39] presented an updated evaluation LCAs
of onshore and offshore wind turbine electricity generation
for 58 case studies relevant to GHG emissions. By new
simplified LCA models, Global Warming Potential (GWP)
was obtained for onshore (0.001–5. MW) and offshore (0. 5–
8. MW). For Onshore and offshore large scale, median
values of GWP are 9.7 and 9.99 gCO2eq/kWh, respectively.
Furthermore, the median values decline as the nominal WT
capacity and capacity factors increase. The GWP has a broad
range of variability for onshore applications, ranging from
4.8 to 560.0 GWP units with a wide range (between 0.02 and
0.56) for onshore applications. This fact is particularly for
micro turbine applications where various basic assumptions
lead to widely disparate estimates, what means that turbine
capacity between 0.2 -1000 KW still requires further
investigation.
The role of each life cycle stage on CO2eq was done by
reference [42], they showed that the mean value was 5.27
gCO2eq/KWh for 20 years life span, distributed as follows,
90.1% for raw material acquisition/manufacturing, 1.9%
transportation 7.1% installation, and 0.9%o operation and
V90
V80
Recycling
included
Reference
[44]
8.65
20
20
65x77 m
50x50m
Onshor
e
Onshor
e
1.5x18 =27
MW GW77
0.75x30= 22.5
MW Gold
wind S50
China
8.3 m/s
CF = 30%
Reference
[45]
13.4
30
Onshor
e
20 MW
Italy
-
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
905
maintenance. The most significant maintenance effects are
created by replacing some control system components,
followed by the replacement of the lubricant. If the end-of-
life were included, the mean value would be declined by -
65.8% to still equal to 1.82 g CO2eq/kWh. Extending the life
cycle to 30 years, the overall GHG impact would be
decreased by 33% to 3.53 g CO2eq/kWh. The highest
impacts of each major component of the turbine come from
the manufacturing of the tower contributing > 40% of the
overall impact. The processing of steel needed for
manufacturing the tower contributed to 95% of the
greenhouse gases. Replacing the steel tower with a steel-
reinforced concrete tower reduces CO2 emissions by 6.4%
overall.
According to reference [25], the average CO2 emission
factor of the three systems investigated was 3.9 g
CO2eq/kWh over the life span. All raw materials had an
average intensity of 1.35 kgCO2/kg. Manufacturing
accounted for 44% of CO2 emissions, decommissioning for
40%, and construction for 16%. The overall CO2 emission
rate was 1.98 kg CO2/kg for all steel materials.
Reference [48] studied the GWP impact of tall towers
onshore turbine (76.16-m hub height): a lattice and a tubular
one over a 20-year lifetime. As the results show, the 82 %
responsibility of the manufacturing phase of the overall
equivalent CO2 emissions of the tubular tower, whereas the
lattice one accounted for 75 %. The second contribution
comes from the transportation step, accounting for 9% for
tubular and 14% for lattice. Related to CO2 emissions per
structural component, it was 62% for the tubular tower,
27%foundation, 9% nacelle, and 2% rotor.
3.2 Solar Energy
One of the most common methods for generating
electricity directly from solar energy is to use Photovoltaic
Cells (PVs). Another way to generate electricity indirectly
from solar energy involves focusing the sun rays through a
Concentrated Solar Power (CSP) system to convert it into
thermal energy and electrical energy. Furthermore,
Concentrated Photovoltaic (CPV) can be used to generate
electricity. The design of Photovoltaic Cells (PVs) is varied
and these cells can be affected by several variables [49, 50,
51, 52, 53]In (CPV), where sunlight is focused on as hybrid
technology, it was developed to overcome weaknesses and
highlight the advantages of PV systems [54]. CPVs are still
in their adolescence compared to conventional PV systems.
Consequently, they play a limited role in solar electricity
generation, with a relatively small number of research studies
related to operation and installations [55]. In 2021 meantime,
conventional PV and CSP systems represent the main part of
the renewable energy market. Therefore, the scope of the
current study is limited to the most widespread technology,
but sometime the data related to the third generation may be
used for comparison purposes [56, 57, 58].
3.2.1 Photovoltaic (PV)
PV system produced electricity consists mainly of three
parts a) multiple modules connected to create an array, b)
Balance Of System (BOS), c) storage system typically used
for stand-alone systems. Communally BOS includes
inverters that the device usually replaced at least once during
the life span of a PV array, and support systems fabricated
from stable and durable materials such as aluminium alloys,
combiner boxes, cables, and connectors. Additional
equipment and facilities such as land and grid connections
should be needed for large-scale ground-mounted PV
construction [58, 59].
PV systems are distinguished by fabrication techniques,
shapes, sizes, and used materials. Various semi-conductive
materials were used in manufacturing PV: about 85–90% of
the solar cells are composed of single-crystalline silicon (sc-
Si) or multi-crystalline silicon (mc-Si). The single-crystalline
silicon (sc-Si) and multi-crystalline silicon (mc-Si) are called
first-generation PV cells. The scope research areas for PV
technologies are the first-generation and second generation
of PV cells, based on the thin-film solar cells, which include
(a-Si, lc-Si, GaAs, C.I.S., CdTe, CdS, CIGS). PV systems are
categorized as grid-connected, stand-alone systems. In
addition, PV systems can be categorized according to their
configurations: fixed PV or tracking systems that include
single and double axis tracking.
The third-generation PV cells include organic or semi-
Organic PV panels (OPV), Perovskite cells (PC), Dye-
Sensitized Solar Cells (DSSC), and Quantum Dot (QD) cells,
as well as CSP systems, which are considered: still under
development [58, 60]. Photovoltaic (PV) power facilities, as
mentioned by reference [61], have carbon footprints that
can range from 12g per kWh for a facility employing First
Solar's thin-film modules to as high as 24g per kWh for one
using multi-crystalline silicon panels over its entire lifecycle.
The reviewed literature regarding the Photovoltaic (PV)
includes 78 studies published after 2005 related to most used
PV technologies and covered its LCA, as follows: 22, 23, 15,
8, 7,3 studies for sc-Si, mc-Si, CdTe, CIGS, a-Si, CIS
respectively. The reviewed studies are presented in Table (2).
The life cycle of a PV power system may divide into
four stages [8, 31, 62, 63, 64]: 1) acquisition of raw
materials, processing of materials, and manufacturing; 2)
installation and construction of electrical and electronic parts,
wiring, and land-used and structural support; 3) operational
and maintenance phase; and 4) PV component end-of-life
(decommissioning, recovery, disposal, or recycling).
According to reference [65], all parts of the BOS
components' analyzed system should be characterized. The
End-Of-Life (EoL) should be integrated into the study and
thoroughly specified, given their significant impact on the
results. A more thorough impact assessment technique
should be employed when updating data due to new
parameter upgrades to avoid such a negative effect.
Reference [66] estimated GHG emissions in 15.6– 50, 44–
280, and 9.4–104 for amorphous, mono-crystalline, and poly-
crystalline solar PV systems.
The median value of GHG emissions from 42 case
studies obtained by reference [67] was between 40-47
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
906
GWP units for ground or roof mount related to all types of
PVs cells studied. Results presented by reference [68] were
less twice than the results in reference [67]. It is close to
the results of reference [69], as the life span was considered
17 instead of 30 years
Reference [70] examined five types of photovoltaic
(PV) systems-based electricity generation: sc-Si, mc-Si, a-Si,
CdTe, and CIS thin film (CIS). The mean GHG emission
rates were 37, 33.5, 34.5, 25.5, and 28.25 GWP units. For its
high conversion efficiency and low energy consumption
across the lifecycle, the CdTe PV system has the lowest
greenhouse gas (GHG) emission rate value. In contrast, the
mono-Si PV system has the highest value due to the high
energy intensity during the PV cell production process.
Table 2. Summery of the analysis of 20 studies published between 2005 and 2020 related to the generation power from
Photovoltaic (PV)
Source
(20) studies
Total
(g CO2
eq/kWh)
Life
(years)
Irradianc
e
(kWh/m2
)
Technolo
gy
Mounting
Location
Other
assumption
s
Reference [71]
53.5
30
1700
ms-Si
30o tilt, fixed aluminum
mount
Virtual
5 MWp,
module
=0.14
42.8
30o tilt, dual-axis
tracking
38
30o tilt, fixed wood
mount
37.5
30o tilt, single-axis
tracking
Reference [70]
23
22.9
32
33
17
17
17
17
2096
1834
1228
1834
mc-Si
mc-Si
CdTe
CdTe
Calculated per
produced kWh without
recycling
Brazil
China
Germany
China
=0.141
=0.129
=0.09
=009
Reference [72]
32
62
142
20
1700
CdTe
CIS
mc-Si
actual production
systems
Europe
= 0.08
=0. 10
=0.14
Reference [73]
44
30
1000
sc-Si
tilt of 35o, fixed
125m2,wall mounted
32 rows
UK
14.4
kWp
=0.115
Reference [74]
61
13
29
30
30
1700
sc-Si
CdTe
mc-(Si)
sc-Si
153.5m2 Solaire
building integrated
photovoltaic
Without integration
USA
11.3kWDC
=0.14
=0.109
=0.132
=0.142
Reference [57]
10.7
24.6
15
30
1600
Perovskit
e-silicon
tandem
Mono-
(SI)
simulation
USA
=0.252
0.231
0.276
Reference [75]
29.2
25
Poly-(SI)
315-
320Wp
(cell)
246MWp
3.64x106m2
Chile
0.165-
0.162
Reference [60]
47.9
30
1600–
sc-Si
30O tilt, ground
Italy
=0.1385
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
907
1800
mounted
single-axis tracking
2 MWp
Reference [76]
37
21
30
45
30
1700
mc-si
CdTe
Ribbon-
Si
sc-Si
On-roof mount
Europe
european
electricity
mix
=0.132
european
electricity
mix
=0.08
Reference [77]
12.75
30
1700
CdTe
-
USA
=0.109
electricity
mix
(750 g
CO2-
eq/kWh)
Reference [67]
45
40
47
48
44
30
1700
c-Si
sc-Si
mc Si
c-Si
c-Si
-
-
-
Ground mount
Roof mount
Global
-
=0.14
=0.132
-
-
Reference [68]
20
16
26
21
14
27
30
2400
a-Si
CdTe
CIGs
a-Si
CdTe
CIGs
Ground mount
Ground mount
Ground mount
On-roof mount
On-roof mount
On-roof mount
Global
=0.063
=0.109
=0.115
=0.063
=0.109
=0.115
Reference [78]
92
30
1204
sc-Si
45 degree fixed mount
Global
-
Reference [79]
5
30
1700
CdSe
QDPV
Ground mount
Europe
=0.14
Reference [41]
52.5
61.5
35.5
25-30
mc-si
(sc-si)
Thin
Film
(CdTe)(
CIS)((CI
GS)
Survey
Global
Reference [8]
49.9
-25-30
1204-
2400
a-Si
GIS
ms-Si
sc-Si
Survey
Global
=0.06-
0.14%
17.5 to 110
g
Reference [80]
43.5
39.5
44.3
52.4
30
1700
a-Si
(amorph
ous)
GIS
ms-Si
sc-Si
3 kW On-roof mount
area 49.2 m2
28.2m2
24.5m2
17.7m2
Greece
=0.061
CF
=21.8%
=0.106
CF
=20.2%
=0.123
CF
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
908
=20.6%
=0.17
CF
=20.6%
Reference [82]
41.8
31.5
27.5
25.2
30
1700
sc-Si;
mc-Si
sc-Si
mc-Si.
100 kWp
Ground fixed mounted
1,59 m2 panel area
Korea
sc-Si
=0.159;
mc-Si
=0.149
sc-Si
=0.276
mc-Si=0.
204
Reference [83]
30.2
29.2
20.9
25
25
30
1580
multi-Si
PV
technolo
gies (cell
or
module)
Roof-integrated
one 60-cell silicon PV
module.
Singapor
e
Aluminum
back
surface
field
=0.159
Passivated
emitter and
rear
cell=0.16
7
Solar cells
with the
frameless
double-
glass
module
structure
=0.162
Reference [84]
60.1
80.5
65
87.3
25
1600
1200
1600
1200
LS-PV
ms-Si
Distribut
ed ms-Si
LS-PV
sc-Si
Distribut
ed sc-Si
performance ratio 0.75
1.12 m2 1kWh
0.7
0.75
0. 70
China
sc-Si cell
=0.17
mc-Si cell
=0.15
grid-
connected
photovoltai
c
Reference [45]
26.6
30
1600
sc-Si
Ground mount
Italy
Reference [85]
85.33
73.67
23.22
50.5
39.2
57.49
30
sc-Si
ms-Si
CdTe
CIS
CIGs
a-Si
Survey
Global
The GWP includes recycling for two types of c-Si panels (sc-
Si and mc-Si) evaluated by reference [82]. This evaluation
was built according to two scenarios related to the PV
efficiency: a base one with efficiency: of 15.9% for sc-Si and
14.9% for mc-Si and the other scenario with higher
efficiency: of 27.6% for sc-Si and 20.4 for mc-Si. As a result,
the sc-Si and mc-Si panels release 41.8 and 31.5 g
CO2eq/kWh in the base case, and with the higher efficiency
case, those values are reduced by 34.3% and 20.0%,
respectively. Further analyses of the lifecycle lineal on the
basic case for both the sc-Si and mc-Si module show that
pre-manufacturing, manufacturing processes, and end life
contributed 12%,88%,-20%, and 19%,81%,-12% for sc-Si,
mc-Si modules of total respectively. The highest share comes
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
909
from ingot (38% for the sc-Si base scenario and the lowest
11% for the mc-Si module in both scenarios). Reference
[86] evaluated the carbon footprint of a large-scale grid-
connected PV system over its entire life cycle, including
extraction of raw material, module fabrication, and operation,
excluding the end-of-life stage. GHG emissions ranged from
12.28 to 58.81 g COeq/kWh, with cell efficiency ranging
from 14 to 20% considering four alternative manufacturing
scenarios of a multi-crystalline panel. Reference [8]
examined 21 studies that were directly related to GHG
emissions from PVs. The mean value reported was 17.5 -
110 g CO2eq/kWh, with an average of 49.9 g CO2eq/kWh.
The majority of the footprint CO2 has been related to the
first stage, which was expected to contribute about 71% of
the lifetime GWP. For construction 19%, operational stage
about 13% (6.15 g CO2eq/kWh), decommissioning and
recycling -3.3 % for PVs.
In China, reference [87] conducted an LCA for mc-Si
modules PVs. The cells had a life span of 25 years and a cell
efficiency of 16 percent. A PV system's GWP was 50.9
gCO2eq/kWh, with CO2 (83.6%) and CH4 (13.6%)
dominating (11.2 %). Solar-grade multi-Si (SoG-Si)
production, ingot casting, wafer slicing, cell processing, and
module assembly were all part of the manufacturing process
for PV modules in China. Because of its high energy use, the
manufacture of SoG-Si was a significant stage, accounting
for around half of the GHG. Because of its high electricity
use, cell manufacturing contributed significantly to GWP
(20.5 %). This factor is related to the that electricity was
mainly generated in china by coal-fired power plants.
Data adopted by reference [64] related to installation
rooftop-mounted under Southern European irradiation of
1700 kWh/m2/yr and performance ratio of 0.75, indicated
that the mean values of GHG emissions were 29, 28, and 18
g CO2eq/kWh with an efficiency of 10.9,13.2, 14% and life
span 30 years for sc-Si, mc-Si and CdTe respectively. The
contribution of GWP unit of BOS, frame, laminate, and cell
is about 60% for c-Si technology, while 3% and 67% for
BOS and laminate related to CdTe type.
Reference [84] examined the environmental effects of
grid-connected c-Si PV generation. Depending on the
installation methods, GHG emissions range from 60.1 for
LS-PV ms-Si to 87.3 gCO2eq/kWh for distributed sc-Si
systems. Approximately 84 percent or possibly more of total
GHG emissions occur during the PV manufacturing process,
with SoG-Si creation accounting for 36 % of total Carbon
footprint over the lifecycle. Reference [88] investigated the
LCA implications of an mc-Si panel system in China, with
an operational life of 25 years and a cell efficiency of 16%.
The study did not include the transportation or use phases in
its research, instead focused on the decommissioning and
recycling stage. 90% of the climate change impact was due
to the share production process. When comparing landfill
and recycling scenarios, the most important GHG impact
processes were mc-Si fabrication, processing of cells, and
panel assembly. The recycling scenario of the end-of-life
(EoL) stage showed fewer consequences on the environment
than the disposal scenario.
Reference [85] reviewed 31 LCA studies connected to
PV electrical generating systems. They concluded that the
calculated mean values of GWP impact for sc-Si (24 case
studies), mc-Si (35 case studies), CdTe (21case studies), a-Si
(16 case studies), CIS (3case studies), and CIGS (one case
study) were to be 85.33, 73.68, 23.22, 57.49, 50.5, 39.2
gCO2eq/kWh respectively. It should be noted here that these
high values of CO2 rates came as a result of the authors'
reliance on almost references before 2010, where the end-of-
life excluded. In addition, the following should be noted
from all previous studies that CdTe cells are the least
effective in global warming than other photovoltaic cells.
Report by reference [89] described energy intensities
needed for recycling of crystalline silicon (c-Si) and
cadmium telluride (CdTe) PV modules over a 30year
lifespan. Compared to the impacts created by the
manufacture of a 3 kWp, the climate change impacts of
recycling efforts of c-Si PV modules are quite minimal,
accounting for a maximum of 1.1 percent. In contrast, it is
about 4.8% for CdTe PV module recycling, but still the
minor GHG impact. Recycling resources like silicon, copper,
aluminum, and glass has a constructive effect on climate
change. Global warming may have contributed -15 % of the
total impact by using an advanced recycling approach for
1000 kg waste (c-Si) panels [90].
CdTe technology uses less energy and material
resources than Si technology, according to reference [63],
resulting in a reduction in all gaseous emissions
repercussions. They also highlight the importance of the end-
of-life recycling process, which involves raw material
recovery. Adoption recycling innovation methods can cut the
GWP by 24.14 % in multi- silicon and 4,71 %t in CdTe
technologies. When a 1 m2 polycrystalline panel is recycled,
0.889 m2 (89%) are produced due to this procedure. In
contrast, if a 1 m2 CdTe solar panel is reprocessed, 0.0412
kilogram CdTe (94.9 %) is obtained instead of the 0.0434 kg
required for a new solar panel.
A comparative LCA of various p-type multi-crystalline
silicon (multi-Si) photovoltaics investigated by reference
[83] installed for electricity generation in Singapore (Table
2) starts with the extraction of silica sand and ends with the
installation phase. The GHG emissions were 30.2
gCO2eq/kWh for the aluminum back surface field =0.159;
29.2 for passivated emitter and rear cell =0.167 and finally
20.9 gCO2eq/kWh for cells with the frameless double-glass
module structure. This study shows that shifting from the
conventional first to the third case reduced the GHG
emission by 50%. The relative contribution of the carbon
footprint from various manufacturing stages was roughly
41.5 percent for wafer products (including casting and
wafering); 26.1 percent for silicon feedstock production
(solar grade); and 15.7 percent for the balance of system
BOS including installation, etc. 0.9% for cell processing and
7.5% for module assembly for all modules. It should be
noticed here that share module assembly for 1&2 cases
reached 16.5%, while a share of silicon feedstock slightly
increased.
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
910
The survey results carried out by reference [41] of 45
case studies showed the average value of CO2 footprint in
the range of 50.9 5 g CO2eq/kWh. The maximum value was
126, and the minimum was 12.5 g CO2eq/kWh. The average
value for sc-Si, mc-Si, and thin-film was 61.8, 52.2, and 35.5
g CO2eq/kWh, respectively. The principal reason for such
fluctuation is cell and module manufacturing energy
requirements. Thin-film technology, on the other hand, offers
substantially reduced energy requirements. GWP range from
12.5 to 95.0 g CO2eq / kWh, with thin-film a-Si technology
releasing the lowest and CIGS emitting the most. The
location of large-scale constructions may also play an
animated role in CO2 quantities related to land use or
electricity production mixes in the production phase [45].
Four types of PV cells (a-Si, GIS, mc-Si, and sc-Si)
were investigated by reference [80]. They found that the
mean higher carbon footprint value was 52.4 for sc-Si and
the lower 39.5 g CO2eq/kWh for GIS. This contradicts the
survey results the results of the previous study [41].
Reference [91] showed that more than 75 % of GWP is due
to multi-crystalline cell processing and module assembly. It
also noticed the direct relation between consumption of
energy and climate change impact, where it two steps have
the highest consumption rate and non-positive environmental
impacts. On the contrary, the second generation is less
energy-intensive than first-generation models through
manufacturing processes (purification and crystallization).
This should lead to a lower GWP impact [58, 82].
Using varied evaluation approaches, a lack of or missing
data at some stages of LCAs, and selecting different
functional units result in a wide range of outcomes,
complicating the comparison between studies [58, 65]. The
low number of panels that reached the decommissioning
phase is the key reason for the end-of-life stage [90].
Table 2 summarizes the research's significant parameters
that studied GHG emissions based on panel energy
generation capacity, type of solar panel, orientation, and
angle. Other criteria such as durability, irradiance (kWh/m2),
mounting, efficiency, location, technology, system, and the
electricity mix of that country and year of study are all
considered as possible. Another cause for the gap in data for
major greenhouse gas emissions could be one of the factors
outlined above [66, 70].
3.2.2 Concentrating Solar Power (CSP.)
Concentrated Solar Power Plants (CSPs) are thermal
systems using a thermodynamic cycle such as the Rankin
cycle to generate electricity. This technique can function at
two temperature levels either high temperatures (about 1000
oC) or intermediate temperatures (about 400–500 oC). Solar
arrays must be focused on tiny surfaces using reflecting
mirrors of various shapes to achieve such high temperatures.
Its primary characteristics are high efficiencies, the
utilization of mainly the direct component of solar energy,
and the requirement of high Direct Normal Irradiation (DNI),
which makes the implementation of small plants
problematic. A central tower can capture the concentrated
solar radiation, parabolic trough, dish, or linear fresnel
reflectors. The life cycle phases of CSP technologies also
include the four stages mentioned earlier for PV cells and
wind systems, taking into account the specifics of each
technology [41, 89, 92, 93].
According to reference [94], following the full
harmonization of 125 research studies, 10 generated 36 case
studies with independent GWP estimates that passed quality
and relevance screening: 19 for trough and 17 for tower
systems. The Inter Quartile Range (IQR) of published
estimates for troughs and towers was 83 and 20 g
CO2eq/kWh, respectively, whereas the median values were
26 and 38 (g CO2eq/kWh).
Reference [93] assessed the life cycle for a dry-cooled,
106 MWnet power tower facility in the USA. The estimated
GWP was 37 g CO2eq/kWh. The highest contribution of
GHG through life span was for O&M 17 g CO2eq/kWh
(46%), whereas 14 (37.8%) ,4(10.8%), 2.4(6.48%), 0.38, for
manufacturing, disposal, construction, dismantling
respectively. Using synthetic salts as storage agents,
estimated GHG emissions increased by 12%.
A comparison of CSP cells and PV cells was made by
reference [60]. In this work, the obtained GWP was 29.9
gCO2eq/kWh for the CSP plant and 47.9 g CO2eq/kWh for a
PV power plant. Decommissioning of the plants was
considered but did not involve component transportation. A
commercial wet-cooled 50 MWe CSP plant with thermal
efficiency (30-35% based on parabolic troughs operating
with different Natural Gas (NG) inputs (from 0 to 35 % of
mix generation of electricity) was investigated [95]. Using
solar energy, only produced GWP 26.6 g CO2eq/KWh.
Higher impact values were observed for GWP that accounted
for 311 g CO2eq/KWh when using 35 % NG.
More than 100 reviewed case studies engaging with life
cycle assessment of renewable energy systems are included
in reference [96], such as (C.S.P.s, P.V.s), wind, hydro, and
geothermal energies. The results obtained after
harmonization of 15 case studies for CSPs (9 for parabolic
trough and 6 for tower) between the lowest and highest
values for GWP were respectively equal to 10 and 71 g
CO2eq/kWh, for a mean value equal to 33 while for wind
11.84 and for PV 31.6 g CO2eq/ kWh. Previous research
[97] indicated that GHG emissions from PV plants are 34.4
gCO2eq/kWh, while trough and tower CSPs emit 20.6
gCO2eq/kWh and 14.2 gCO2eq/kWh, respectively. Values
related to other technologies are listed in Table 3.
Reference [40] Supporting Information (SI) obtained
other 95-33g CO2eq/kWh results. The midpoint values were
22.7 and 33 g CO2eq/kWh for troughs and towers,
respectively. Another survey comparing three types of CSP
systems used for producing electrical power was done by
reference [85]. This study reviewed 10 case studies for
trough receivers, 9 case studies for central towers, and 2 case
studies for the parabolic dish. The highest contribution had
tower systems with average GHG emissions of 85.67
gCO2eq/kWh and the lowest average of 41 gCO2e/kWh for
the parabolic dish, whereas 79.8 gCO2e/kWh for the
parabolic trough.
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
911
Reference [41] surveyed two types of concentrated
systems (troughs and towers) within three capacity ranges:
less than 50 MW, Between 50 MW and100 MW, and more
than 100 MW. For CSP technologies, a minimum value of
10.0 g CO2eq/kWh and a maximum value of 56.0 g
CO2eq/kWh displayed a considerable variance. The mean
values were 33.2, 30.3, and 24 g CO2eq/kWh. It was also
discovered that power tower receivers contribute more than
31.9 g to GHG emissions than parabolic trough receivers
23.6 gCO2eq/kWh.
Three case studies considered by reference [45]
represented three geothermal power plant scenarios, one
wind farm, and one CSP plant in Italy. The assessment
employed the ReCiPe 2016 and the ILCD 2011 Midpoint+
LCIA methods widely used in Europe to perform comparing
potential impact at the midpoint level. The investigated
plants had similar nominal capacity (about 20 MWe),
assuming a lifetime of 30 years. The system boundaries
consisted of the whole life cycle of the system (including the
replacement of main parts). The impact of climate change at
the mid-point was 13.4, 26.6, 415, and 484 GWP units for
wind, solar, geothermal, and national energy mix),
respectively.
Table 3. Summery of the analysis of 11 studies published between 2005 and 2020 related to the generated power from
Concentrating Solar Power (CSP)
Source
Total
estimate
(g
CO2eq/kWh).
Type
Life
(year
s)
Capacity
Location
Tower height or
aperture area
Other assumptions
Reference
92]
31 tower
20
110 MW
Global
140m x0. .457 km2
manufacturing + operational,
without storage
9.8 tower
20
110 MW
240 m1.469 km2
with storage
Reference
[95]
26.6 troughs
25
50 MW
Spain
510.12km2
parabolic troughs
desert land
Reference
[98]
24.3 tower
30
101 MW
South
Africa
1.4375 km2
Heliostat size 25 m²
Tower height 230
M
DNI kWh/m²/a
2,900
Tower with heliostats
12 hour heat storage and no
supplementary fuel electricity
grid mix
Reference
[94]
26 trough
38 tower
38 parabolic
30
1-400 kW
Survey
utility-scale CSP
Reference
[40]
22.7 trough
33 tower
30
net
103MW
106 MW
(lca)
4.1 km2
6.3km2
CF=0.47
CF=0.42
Reference
(2019) [41]
23.6 trough
31.9 tower
25-40
< 50 MW
to > 100
MW
Survey
Reference
[99]
6.5HCPV
53.7
107.7
30
25
FULLSU
M
1.008MWp
7.5 kW
CPV
Chile
Moroco
Japan
0.27 m2, CR=625X
3600 m2 CR=520x
34.56 m2 CR=476x
DNI 3322,=0.34
1834 = 0.282
909 =0.3
Reference
[100]
13.6
Paraboloidal
dish
30
1MW
Italy
Reference
[101]
202 Central
tower
196 Parabolic
trough
25
25
1.7 MW
50 MW
Spain
Spain
Reference
[93]
37 tower
30
a dry-
cooled,
106
MWnet
USA
No of heliostats
6,682
total aperture area
964,712 m2
tower height 172
total land area
DNI 2600 kWh/m2
capacity factor 41.7%
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
912
6,345,471 m2
Reference
[85]
85.87 tower
79.8 trough
41.24
parabolic dish
30
Survey
Reference [99] reviewed issues related to CPV with High
Concentration Photovoltaics (HCPV) and Low Concentration
Photovoltaics (LCPV). GWP impact of the system could be
decreased by 23–31% by extending the life span of the
HCPV plants 10 years from 20 to 30 years. Reference [102]
explored HCPV prototypes based on LCA analysis of
modules: mirror-based, Fresnel lens, and Achromalens. GHG
emissions for the mirror-based optical design module were
roughly 10% less than the Achromalens modules. Moreover,
a contribution in the carbon footprint of 50% comes from
optics, tracking systems, and metals of the frame.
Reference [92] carried out and compared CO2eq/MWh
of a tower-type CSP utilizing molten salts as a storage agent
with a reference CSP plant without storage in a baseload
pattern. Without storage, the impact was 67% (31
gCO2eq/kWh) larger than with storage (9.8 gCO2eq/kWh).
The GWP was presented by reference [98] linked to CSP
plant-generated electricity shows that the GHG impact of the
assessed plant is 24.3 g CO2eq /kWh. The plant's
construction phase releases 12.0 g CO2eq/kWh (44 %),
while the other produces 15.2 g CO2eq/kWh (55 percent).
By recovering and replacing virgin material at the end of life,
2.9 g CO2eq/kWh (10 %) of CO2 emissions are prevented.
The solar field contributes 30% of the GWP, followed by
molten salt storage and transportation expenditures, which
contribute 25%, and building on site, which contributes 9%.
Table 3 summarizes the results of the survey for CSP
technologies
4. Compression GWP of Wind and Solar Technologies
Versus Other Electricity Generation Systems.
The finding of GWP impact studies linked to electricity
generation systems are tabulated in Table (4). The GWP of
traditional power systems conducted only fossil fuel
combustion and related activities and is based on the IPCC's
'Default CO2 Emissions Factors for Combustion' listed in its
Guidelines for National Greenhouse Gas Inventories (IPCC)
[103] and AR 5 Climate Change 2014: Mitigation of Climate
Change 2014.
Table 4. The findings of studies related to the GWP impact linked to electricity generation systems
Options
Min/Mea
n/Max
Silva and
Raadal,
(2019)
[41]
Min/Mean
/Max
Referenc
e [104]
Min/M
edian/
Max
Refere
nce
[105]
Min/mea
n/Max
Referen
ce [8]
Min/
/Max
Referen
ce
[106]
Mean
Refere
nce
[104]
Mean
Refere
nce
[107]
Min/Med
ian/Max
Referen
ce [96]
Lignite
1054/790/
1372(6)
800/1300
(7)
1133
1504
Coal—PC
692/948.9
/1250(42)
756/888/1
310(10)
740/82
0/910
960-1050
1005
600/1050
(36)
825
921
888
Oil
547/733/9
35(5)
530/900(
10)
731
733
Gas—Combined Cycle
410/49
0/650
Natural Gas
259.6/446
.7/539.3
(20)
362/499/8
91 (12)
443 for
conv,492
fracking
611 LNG
380/1000
(23)
545
506
499
Geothermal
flash steam and binary
cycle power plants
15/38.1/5
6(13)
6.0/38/
79
38
38
16.9/33.6
/142(20)
Hydropower
2.4/21.4/9
0 for
reservoir
1.2/19.1/4
2/26/237(7
)
1.0/24/
2200
10(resv)
and 13
run river
2/20(12)
27
26
2.2/11.6/
74.8(15)
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
913
Table 4 continoued. The findings of studies related to the GWP impact linked to electricity generation systems
Note: the number in the () refers to the number of studies.
Conventional power plants are mainly responsible for
emitting the most significant amounts of carbon dioxide,
while more than 75% are released through fuel combustion
and related activities. The average value of a GWP unit for a
coal-fired system is 936 g CO2eq/ kWh, 730 g CO2eq/ kWh
for oil, and 502 g CO2eq/ kWh for gas-fired power systems.
Figure 1 shows the concentration of GWP units for
investigated renewable and non-renewable energy systems.
8.2 for
run Run-
of-
river,(94)
Nuclear
2/29/130(1
4)
3.7/12/
110
66
3/35(10)
14
Biomass
10/45/101(
5)
14/41
8.5/130(2
5)
52
26
Concentrated Solar Power
10/27.9/5
6 (29)
8.8/27/
63
13
14.2/30.9
/203(15)
Solar PV—rooftop
1.5/50.9/1
26 (45)
13/85/731(
13) (both)
26/41/6
0
97
23
9.4/29.2/
46(36)
Solar PV—utility
18/48/1
80
17.5/50/1
10
13/190(2
2)
Wind onshore
4.6/14.4/4
0 (54)
6/26/124(1
1)(both)
7.0/11/
56
34
3/41(22)
30
10
6.2/9.4/4
6(20)
Wind offshore
5.2/18.4/3
2 (54)
8.0/12/
35
Note: The number in the () refers to number of studies.
Options
Mean value
Reference
[18]
Reference
[108]
Reference
[45]
Referen
ce [101]
Reference [63]
The current
study
Lignite
790-1372
Coal—PC
675-1639
1157
975
936
Oil
742
730
Gas—Combined
Cycle
245-930
587
484
607
478
Natural Gas
502
Geothermal
flash steam and
binary cycle
power plants
11–78 (4)40
6.-76
36
415 mid
37.4
Hydropower
2–75 (11)
3-12 run ri
0.-165 resv
3.7-237
22.7
Nuclear
1-220
24.2
18.5
26.9
Biomass
25-550(14)
75-635
35-178
62.4
Concentrated
Solar Power
30–150 (6)
7-89
13.6-202
28
Solar PV—rooftop
9–300 (19)
5-217
53.6-250
48
Solar PV—utility
26.6
Wind onshore
8–124 (14)
2-81
13.4
9.7-123.7
10.5
13.2
Wind offshore
5–24(5)
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
914
Fig. 1: The concentration of GWP units for investigated
renewable and nonrenewable energy systems.
According to IRENA 2019, the total renewable
energy installed capacity until 2020 was 2799. 094 GW
distributed as Hydropower 1331. 9 GW; Pure pumped-
storage 121.273 GW, Marine energy 527 MW, Wind energy
733. 276 GW (Onshore 698. 909 GW, Offshore 34 .367
GW.) Solar energy 713. 970 GW (photovoltaic 707. 495
GW, Concentrated solar power 6. 475 GW); Bioenergy 126.
557 GW; Solid biofuels and renewable waste 102. 852 GW;
Bagasse 19. 908 GW; Renewable municipal waste 15. 355
GW; Other solid biofuels 67. 588 GW; Liquid biofuels 3.
555 GW; Biogas 20. 150 GW; Geothermal energy 14. 050
GW. Renewable energy share of electricity capacity reached
36% of global electricity generation in 2020. As predicted by
bp Statistical Review may climb to 45 percent by 2040.
The overall electricity made up 25,850 TWh by the end
of 2020 share each sector in detail is 15,757 fossil fuel (8,736
TWh from coal. 5,892 gas. oil 1,128) 10,109 low carbon
sources (hydro 4,355 TWh nuclear 2,616 wind 1,59. solar
0.844 other renewable 0.702 TWh. It is responsible for
releasing around 12 Gt of carbon dioxide (67.7 % are coming
from coal, 24 % from gas, and 6.7% from oil), whereas less
than 2% from low carbon sources. Replacing one kilowatt-
hour of coal or oil-generated electricity with one kilowatt-
hour of wind can save 923 or 717 of gram carbon dioxide
equivalent
According to the BLUE Map (IEA) scenario, the
combined contribution of renewable energy resources such
as solar, wind, and hydropower should rise from 16.5 percent
of total electricity output in 2010 to 39 percent in 2050.
Reference [40] indicate that the large-scale implementation
of wind, PV, and CSP has the potential to minimize GHG
emissions impacts on power production. Furthermore, it
would have a more minor environmental impact than a
system with a high proportion of CO2 capture systems.
5. The Results
According to the findings of the studies, the
manufacturing stage accounts for between 90 and 98 percent
of the overall GWP of an onshore wind farm not built on
peat lands [10, 11, 13, 14, 16, 47, 25, 22 ,33], while a 70% of
an offshore farm [21, 109, 110], with most of these impact
occurring during material extraction and component
manufacturing. The higher contribution (up to 42%) was
coming from towers, 30% for nacelle and 20% for rotor
blades [10, 16, 44]. Typically, transportation and installation
contribute only about 6% of GWP for an onshore wind farm
if carbon impacts of land-use change, such as construction on
peatlands are not included [44]. For offshore, the ratio would
be higher as a result of extensive use of ships, although there
is no study clearly estimating the division between
fabrication and installation effects [111]. The operational and
maintenance phases account for 1.6 to 6% of the total life
cycle GWP impacts of onshore plants [10, 43] and around
20% of offshore (due to the installation site being more
difficult to access) [20], with decommissioning accounting
for the remaining 6% includes disposal. If the end-of-life
comprised recycling stage is included in the calculation, then
the total GWP declined up to 40% thanks to the recovery of
metals [10, 20, 25, 32, ], The plant setup occupied less than
1% of the total GWP impact. In absolute values, the GHG
emissions corresponding with the operational phase were
estimated at 0.74 gCO2eq/kWh (less than 5% on land) within
[35] and 0.49 gCO2eq/kWh within [63]. The total GHG
impact of onshore wind was 12.7 gCO2eq/kWh, for offshore
13.91gCO2eq/kWh and meanly 13.45gCO2eq/kWh for wind
energy technologies.
Table 5. Summery the analysis of examined studies published between 2005 and 2020 related to the generation power from
wind power, photovoltaic power, and Concentrating Solar Power (CSP)
Parameters
Wind power
Photovoltaic power
CSP
Onshore
Offshore
Sc-Si
m-Si
CdTe
CIGs
a-Si
CIS
Tower
Trough
Number of
studies
45
27
22
23
15
8
7
3
11
7
Variations in
GWP unite
[g
CO2eq/kWh]
3-138
4.6-81
22.5-115
20.9-
80.5
5-48
26-93
12-
57.5
35.5-
62.
9.8-85.7
20.6-79.9
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
915
The obtained mean values from this review were
arranged between 50.76 GWP unit for sc-Si and 23.4 for
CdTe panels, whereas 33.14 for a-Si, 39.9 for mc-Si, 49.3 for
CIS, and 43.8 for CIGs, respectively. In general, the studies
indicate that a major CO2 impact is coming from the
manufacture (structural materials and glazing) (75-90%) as
presented in [8, 64, 87, 84, 88, 89, 90, 83, 91]. The current
silicon technology modules, notwithstanding the
development of thin-film manufacturing, [58, 91]. The
recycling stage can be declined GWP up to 20% depending
on innovative technologies [82, 90] while operational step up
to 13%. The most effective element of GHG impact was
ingot about 38% or SoG-Si about 50% of the manufacturing
stage [87]. The results also showed that with raising the
efficiency of the cell, the value of the GHG emission effect
decreases [67, 68, 82, 69]. Also, the installation effect on the
ground is less affected than those cells were installed on the
roof-mounted [67, 69].
The calculated average GWP impact related to CSP
technologies (11 for the tower, 7 for the trough, 3 for the
parabolic) were 35.6, 30.94, and 25.8 gCO2eq/kWh,
respectively. The overall GHG impact of solar system
technologies was 38.88 gCO2eq/kWh. Figure 2 represents
the average, maximum, and minimum GHG emission values
for solar and wind energy systems.
Fig. 2: The average, maximum, and minimum GHG emission
values for solar and wind energy systems.
These conclusions do not contradict the findings of
other researchers. The overall finding is tabulated in Table
(5).
6. Discussion and Conclusion
1. Comparing the ranking of wind and solar technologies
in terms of overall GWP for this study indicated the
impact of the height sc-Si PV, while the lowest for
onshore wind farms.
2. The findings indicate that raw material
acquisition/manufacturing for wind and solar
technologies has the most significant contribution to
total GWP impacts, accounting for up to 98 % of the
life cycle stage, followed by installation, operation, and
maintenance.
3. The findings show that GWP may demonstrate
considerable differences within the same technology.
As noted throughout this study, such changes may be
related to differences based on "actual variables," such
as regional surroundings (e.g., wind speed and solar
radiation), percent energy mixes used in raw material
acquisition, etc. However, variation may be exacerbated
by changing methodological supposition, which needed
to consider recommendations and suggestions from the
previous practices, involving recycling and
transportation at the end-of-life stage. It is important to
obtain more accurate results for further studies.
4. Imbalances between studies are likely to be explained
by a combination of actual differences in the studied
systems (e.g., turbine size), key assumptions (e.g.,
capacity factors, wind speed life span), and data
contradiction (e.g., material emission rates), and
variations in methodologies and approaches. The causes
of variation in LCA are extensively documented in
previous studies, e.g. [11].
5. Solar and wind farms require more mass of materials
(silicon, cement, steel, copper, and aluminum) than
Average in
GWP unite
[g CO2-
eq./kWh]
13.91
12.7
50.76
39.92
23.39
43.83
33.14
49.3
35.60
30.94
Most
contributing
Stage
Manufacturing +
foundation
Manufacturing
Materials
Variations in
contribution
%
86-98
70-90
75-96
52-70
The majority
of the
contributing
activity %
Tower
(41)% steel
+concrete
Contractual material +glazing
30% for ingot , 50% for SoG-Si
O&M+ solar field
Transport %
10
6
O+M %
1.6-6
13
24
Recycling %
-40
-20
-10
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
916
fossil fuel-powered power plants. However, the
materials share reached 20–50% of the total footprint
for renewables, with CSP tower and offshore wind
technologies exhibiting the highest shares. However,
the impact was still minimal in absolute terms
compared to the impact of fossil fuel from mining to
combustion in power plants. CSP and ground-mounted
PV power facilities have high land-use requirements.
Wind and roof-mounted PV have the lowest land usage
requirements. Because the land is already in use as a
structure, roof-mounted PV is considered to have zero
direct land usage. Analyzed the entire power plant for
ground-mounted solar electricity since the modules or
mirrors are so closely spaced that cultivation and other
uses are unfeasible in the unoccupied areas.
6. The initial need for silicon, copper, and cadmium is
primarily related to PV systems, whereas additional
iron and cement demand is primarily driven by wind
and CSP installations.
7. With increasing efficiency, capacity, power factor,
implement innovation recycling methods, and an
expended lifetime of all systems, footprint declined
significantly.
8. Differences in the electricity mix impact not only the
emissions for each phase but also the total emissions for
a given power generation scenario. Changes in grid
energy may have the largest influence on supply chain
manufacturing and materials and consumables for
power plant construction, including activities linked
with the wind power scenario's construction phase.
9. Analysis data from the literature suggest that the GHG
emissions associated with the life cycle of solar power
systems and wind power systems have decreased
significantly during the past two decades, reaching
38.88 g CO2e/kWh and 13.45 gCO2e/kWh in 2020,
respectively. In terms of other electricity generation
technologies, the total value of GHG emissions is 936
gCO2e/kWh for coal-fired and
730,502,62.4,37.4,26.9,22.7 for oil, gas, bio-energy,
geothermal, nuclear, and hydropower, respectively.
References
[1] BP, Statistical Review of World Energy70th edition,
2021.
[2] IEA, Global Energy and CO2 Status Report, 2018.
[3] IRNA, Renewable capacity statistics 2021, International
Renewable Energy Agency (IRENA), Abu Dhabi, 2021.
[4] IEA, World Energy Outlook 2020 Executive Summary,
2020. www.iea.org/weo.
[5] IEA, Global Energy Review 2021. www.iea.org. Global
Energy Review, 2021.
[6] IRNA, Future of wind: Deployment, investment,
technology, grid integration and socio-economic aspects
(A Global Energy Transformation paper), International
Renewable Energy Agency, Abu Dhabi, 2019.
[7] R. Howarth, R. Santoro, and A. Ingraffea, “Methane and
the greenhouse-gas footprint of natural gas from shale
formations”, Climatic change, Vol. 106, pp.679-690,
2011.
[8] D. Nugent, and B. Sovacool, “Assessing the lifecycle
greenhouse gas emissions from solar PV and wind
energy: A critical meta-survey”, Energy Policy, Vol. 65,
pp. 229-244, 2014.
[9] A. Bonou, A. Laurent, and S. Olsen, “Life cycle
assessment of onshore and offshore wind energy-from
theory to application”, Applied energy, Vol. 180, pp.
327-337, 2016.
[10] P. Razdan, and P. Garrett, “Life Cycle Assessment of
Electricity Production from an Onshore V136-4.2 MW
Wind Plant”. Vestas Wind Systems A/S. https://www.
vestas. com/$\sim
$/media/vestas/about/sustainability/pdfs/lca% 20of%
20electricity% 20production% 20from% 20an%
20onshore% 20v13642mw% 20wind% 20plantfinal. pdf
(accessed October, 2020).Vestas, (2019). Life Cycle
Assessment of Electricity Production from an onshore
V136-4.2 MW Wind Plant .2019
[11] C. Thomson, and G. Harrison, “Life cycle costs and
carbon emissions of wind power: Executive Summary”,
2015.
[12] G. Mello, M. Ferreira Dias, and M. Robaina, “Wind
farms life cycle assessment review: CO2 emissions and
climate change”. Energy Reports, Vol. 6, pp. 214–219,
2020. doi:10.1016/j.egyr.2020.11.104
[13] B.Tremeac, and F. Meunier, “Life cycle analysis of 4.5
MW and 250 W wind turbines”, Renewable and
Sustainable Energy Reviews, Vol. 13, pp. 2104-2110,
2009.
[14] H. Raadal, L. Gagnon, I. Modahl, and O. Hanssen, “Life
cycle greenhouse gas (GHG) emissions from the
generation of wind and hydro power”, Renewable and
Sustainable Energy Reviews, Vol. 15, pp. 3417-3422,
2011.
[15] A. Arvesen, and E. Hertwich, E., “Assessing the life
cycle environmental impacts of wind power: a review of
present knowledge and research needs”, Renew Sustain
Energy Rev, Vol. 16, pp. 5994–6006. 2012.
[16] P. Garrett, and K Rønde, “Life cycle assessment of wind
power: comprehensive results from a state-of-the-art
approach, the international journal of life cycle
assessment, Vol. 18, pp. 37–48,
2016. doi:10.1007/s11367-012-0445-4
[17] M. Rajaei, and J. Tinjum, “Life cycle assessment of
energy balance and emissions of a wind energy plant”,
Geotech Geol Eng, Vol. 31:pp. 1663–1670, 2013.
Doi.org/10.1007/s10706-013-9637-3
[18] N. Amponsah, M. Troldborg, B. Kington, I. Aalders,
and R. Hough, “Greenhouse gas emissions from
renewable energy sources: A review of lifecycle
considerations”, Renewable & Sustainable Energy
Reviews. Vol.39, pp. 461-475, 2014.
DOI:10.1016/J.RSER.2014.07.087475
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
917
[19] A. Kadiyala, R. Kommalapati, and Z.Huque, Z.
“Characterization of the life cycle greenhouse gas
emissions from wind electricity generation systems”, Int.
J. Energy Environ. Eng., Vol. 8, pp. 55–64, 2016. DOI
10.1007/s40095-016-0221-5
[20] J. Chipindula, V. Botlaguduru, H. Du, R. Kommalapati,
and Z. Huque, “Life cycle environmental impact of
onshore and offshore wind farms in Texas”,
Sustainability, Vol. 10, pp. 2022,
2018; https://doi.org/10.3390/su10062022
[21] J. Yang, Y. Chang, L. Zhang, Y. Hao, Q. Yan, and C.
Wang, “The life-cycle energy and environmental
emissions of a typical offshore wind farm in China.
Journal of Cleaner
Production, Vol. 180, pp. 316-324, 2018.
[22] F. Ardente, G. Beccali, M. Cellura, V. Brano, “Energy
performances and life cycle assessment of an Italian wind
farm”, Renewable Sustainable Energy Rev. Vol. 12, pp.
200–217, 2008.
[23] G. Chen, Q. Yang, and Y. Zhao, “Renewability of wind
power in China: a case study of nonrenewable energy
cost and greenhouse gas emission by a plant in Guangxi”,
Renewable Sustainable Energy Rev, Vol.15, pp.2322–
2329, 2011.
[24] S. Dolan, and G. Heath, “Life cycle greenhouse gas
emissions of utility-scale wind power”, Journal of
Industrial Ecology, Vol.16, pp.136–154, 2012.
[25] J. Xie, J. Fu, S. Liu, and W. Hwang, “Assessments of
carbon footprint and
energy analysis of three wind farms”, Journal of Cleaner
Production, Vol.254, pp. 120159, 2020.
[26] H. Li, H. Jiang, K. Dong, Y. Wei, and H. Liao, “A
comparative analysis of
the life cycle environmental emissions from wind and
coal power: Evidence from China”, Journal
of Cleaner Production, Vol. 248, pp.119192, 2020.
https://doi.org/10.1016/j.jclepro.2019.119192.
[27] S. Wang, S. Wang, and J. Liu, “Life-cycle green-house
gas emissions of onshore and offshore wind turbines”,
Journal of Cleaner Production, Vol. 210, pp. 804-810,
2019.
[28] E. Martínez, J. Latorre-Biel, E. Jiménez, F. Sanz, and J.
Blanco, “Life cycle assessment of a wind farm
repowering process”, Renewable and Sustainable Energy
Reviews, Vol. 93, pp. 260-271, 2018.
[29] X. Zhao, Q. CAI, S. Zhang, and K. Luo, “The
substitution of wind power for coal-fired power to realize
China's CO2 emissions reduction targets in 2020 and
2030”, Energy, Vol. 120, pp. 164- 178, 2017.
[30] S. Ghandehariun, and A. Kumar, “Life cycle assessment
of wind-based hydrogen production in Western Canada”,
International Journal of Hydrogen Energy, Vol. 41, pp.
9696-9704, 2016.
[31] S. Al-Behadili, and W. El-Osta, “Life cycle assessment
of Dernah (Libya) wind farm. Renewable energy, Vol.83,
pp.1227-1233, 2005.
doi.org/10.1016/j.renene.2015.05.041.
[32] J. Bang, C. Ma, E. Tarantino, A. Vela, and D. Yamane,
“Life Cycle Assessment o f Greenhouse Gas Emissions
for Floating Offshore Wind Energy in
California”. University of California Santa Barbara,
2019.
[33] B. Guezuraga, R. Zauner, and W. Polz, “Life cycle
assessment of two different 2 MW class wind turbines”,
Renewable Energy, Vol. 37, pp. 37–44, 2012.
[34] T. Wiedmann, S. Suh, K. Feng, M. Lenzen, A. Acquaye,
K. Scott, and J.Barrett, “Application of hybrid life cycle
approaches to emerging energy technologies—the case of
wind power in the UK”, Environ. Sci. Technol. 45, 5900–
5907, 2011.
[35] E. Mallia, and G. Lewis, “Life cycle greenhouse gas
emissions of electricity generation in the province of
Ontario, Canada”, Int. J. Life Cycle Assess, Vol. 18,
pp.377–391, 2013.
[36] N. Mithraratne, “Roof-top wind turbines for
microgeneration in urban houses in New Zealand”,
Energy Build, Vol.41, pp.1013–1018, 2009.
[37] K. Oebels, and S. Pacca, “Life cycle assessment of an
onshore wind farm located at the northeastern coast of
Brazil”, Renewable Energy, Vol. 53, pp. 60-70, 2013.
[38] T. Zimmermann, and S. Gößling-Reisemanna,
“Influence of site specific parameters on environmental
performance of wind energy converters”, Energy
Procedia. Vol. 20, pp. 402–413, 2012
[39] B. Mendecka, and L. Lombardi, “Life cycle
environmental impacts of wind energy technologies: A
review of simplified models and harmonization of the
results”, Renewable and Sustainable Energy Reviews,
Vol. 111, pp. 462-480, 2019.
[40] E. Hertwich, T. Gibon, E. Bouman, A. Arvesen, S. Suh,
G. Heath, J, Bergesen, A. Ramirez, M. Vega, and L. Shi,
“Integrated life-cycle assessment of electricity-supply
scenarios confirms global environmental benefit of low-
carbon technologies”, Proceedings of the National
Academy of Sciences, Vol. 112, pp. 6277-6282, 2015.
[41] M. Silva, and H. Raadal, “Life Cycle GHG Emissions of
Renewable and Non-renewable Electricity Generation
Technologies”, Krakeroy: Ostfoldforskning, 2019.
[42] A. Alsaleh, and M. Sattler, “Comprehensive life cycle
assessment of large wind turbines in the US’, Clean
Techn and Environ Policy, Vol. 21, pp. 887–903, 2019.
https://doi.org/10.1007/s10098-019-01678-0
[43] M. Ozoemena, W. Cheung, and R. Hasan, R.
“Comparative LCA of technology improvement
opportunities for a 1.5-MW wind turbine in the context of
an onshore wind farm”. Clean Technologies and
Environmental Policy, Vol. 20, pp. 173-190,2018.
[44] L. Xu, M. Pang, L. Zhang, W. Poganietz, and S.
Marathe, “Life cycle assessment of onshore wind power
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
918
systems in China. Resources”, Conservation and
Recycling, Vol. 132, pp. 361-368, 2018.
[45] R. Basosi, R. Bonciani, D. Frosali, G. Manfrida, M.
Parisi, F. and Sansone, “Life Cycle Analysis of a
Geothermal Power Plant: Comparison of the
Environmental Performance with Other Renewable
Energy Systems”, Sustainability, Vol. 12, pp. 2786, 2020.
doi:10.3390/su12072786
[46] R. Besseau, R. Sacchi, I. Blanc, and P. Perez-Lopez,
“Past, present and future environmental footprint of the
Danish wind turbine fleet with LCA_WIND_DK”, an
online interactive platform. Renewable and Sustainable
Energy Reviews, Vol. 108, pp. 274-288, 2019.
[47] M. Uddin, and S. Kumar, “Energy, emissions and
environmental impact analysis of wind turbine using life
cycle assessment technique”, Journal of cleaner
production, Vol. 69, pp. 153-164, 2014.
[48] N. Stavridou, E. Koltsakis, E., and C. Baniotopoulos,
“A comparative life-cycle analysis of tall onshore steel
wind-turbine towers”, Clean Energy, Vol. 4, pp. 48-57,
2020.
[49] F. Javed, and A. Raza, A. Impact of temperature &
illumination for improvement in photovoltaic system
efficiency. International Journal of Smart Grid –
ijSmartGrid, Vol 6, pp. 4-22, 2022.
[50] S. Kyaligonza, and E. Cetkin, E, Photovoltaic System
Efficiency Enhancement with Thermal Management:
Phase Changing Materials (PCM) with High
Conductivity Inserts. Int. J. Smart Grid-IjSmartGrid,
Vol. 5, pp.138-148, 2021.
[51] S. Jaber, and A. Shakir, Design and simulation of a
boost-microinverter for optimized photovoltaic system
performance. Int. J. Smart Grid, Vol. 5, pp. 94-102, 2021.
[52] F. Ghasemzadeh, M. Esmaeilzadeh, and M. Shayan,
Photovoltaic Temperature Challenges and Bismuthene
Monolayer Properties. Int. J. Smart Grid-ijSmartGrid,
Vol. 4, pp.190-195, 2020.
[53] M. Shayan, and G. Najafi, Energy-economic
optimization of thin layer photovoltaic on domes and
cylindrical towers. International Journal of Smart Grid,
Vol. 3, pp. 84-91, 2019.
[54] M. Benhammane, G. Notton, G. Pichenot, P. Voarino,
D. Ouvrard, “Overview of electrical power models for
concentrated photovoltaic systems and development of a
new operational model with easily accessible inputs.
Renew. Sustain”. Energy Rev, Vol. 135, pp.110221,
2021.
[55] M. Reyes-Belmonte, “Quo Vadis Solar Energy
Research?” Appl. Sci., Vol. 11, pp.3015, 2021.
https://doi.org/10.3390/app11073015
[56] A. Ziemi´nska-Stolarska, M. Pietrzak, and I. Zbici´nski,
“Application of LCA to Determine Environmental Impact
of Concentrated Photovoltaic Solar Panels”, State-of-the-
Art. Energies, Vol. 14, pp. 3143, 2021. https://
doi.org/10.3390/en14113143
[57] X. Tian, S. Stranks, and F. You, “Life cycle energy use
and environmental implications of high-performance
perovskite tandem solar cells”, Science Advance, Vol. 6,
pp. 1-10 2020.
[58] V. Muteri, M. Cellura, D. Curto, V. Franzitta, S. Longo,
M. Mistretta, M. and Parisi, “Review on Life Cycle
Assessment of Solar Photovoltaic Panels”, Energies,
Vol. 13, pp. 252, 2020. DOI: 10.3390/en13010252
[59] K. Hagerty, and J. Cormican, “Components of Your
Solar (Photovoltaic) System”, 2019, https:
//www.altestore.com/.
[60] U. Desideri F. Zepparelli V. Morettini and E. Garroni,
“Comparative analysis of concentrating solar power and
photovoltaic technologies: Technical and environmental
evaluations”, Apple Energy, Vol. 102, pp. 765–84, 2013.
[61] A. Wade, “Carbon footprint of solar panels under
microscope” 2017. https://www.euractiv.com(
2016)section/energy/opinion/ Monday cop22 lower co2-
emissions with -lower-carbon-solar-energy
[62] M. Vellini, M. Gambini, and V. Prattella,
“Environmental impacts of PV technology
throughout the life cycle: importance of the end-of-life
management for Si-panels and CdTe-panels”, Energy,
Vol. 138, pp. 1099–1111, 2017.
doi:10.1016/j.energy.2017.07.031
[63] Ltd., Hatch, “Lifecycle Assessment Literature Review
of Nuclear, Wind and Natural Gas Power
Generation”, Prepared for the Canadian Nuclear
Association. Hatch Ltd. October 9, 2014.
[64] R. Frischknecht, R. Itten, P., Sinha, M. de Wild-
Scholten, J., Zhang, V., Fthenakis, H., Kim, M. Raugei,
and M. Stucki,“Life cycle inventories and life cycle
assessment of photovoltaic systems”, International
Energy Agency (IEA) PVPS Task 12, Report T12, 4,
2015.
[65] S. Gerbinet, S. Belboom, and A. Léonard, “Life Cycle
Analysis (LCA) of photovoltaic panels: A review”,
Renewable and Sustainable Energy Reviews, Vol. 38, pp.
747 753, 2014. doi: 10.1016/j.rser.2014.07.043
[66] A. Sherwani, and J. Usmani, “Life cycle assessment of
solar PV based electricity generation systems: a review”,
Renewable Sustainable Energy Rev, Vol. 14, pp. 540–
544, 2010.
[67] D. Hsu, P. O’Donoughue, V. Fthenakis, G. Heath, H.
Kim, P. Sawyer, J. Choi, and D. Turney, “Life cycle
greenhouse gas emissions of crystalline silicon
photovoltaic electricity generation” J. Ind. Ecol. Vol.16,
pp.122–135, 2012.
[68] H. Kim, V. Fthenakis, J. Choi, and D. Turney, “Life
cycle greenhouse gas emissions of thin-film photovoltaic
Electricity generation”, J. Ind. Ecol. Vol. 16,
pp. 110–121, 2012.
[69] G. Yıldız, B. Çalış, A. And Gürel, and İ. Ceylan,
“Investigation of life cycle CO2 emissions of the
polycrystalline and cadmium telluride PV
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
919
panels”, Environmental Nanotechnology, Monitoring &
Management, Vol. 14, pp. 100343, 2020.
[70] J. Peng, L. Lu, and H. Yang, “Review on life cycle
assessment of energy payback and greenhouse gas
emission of solar photovoltaic systems”, Renewable and
Sustainable Energy Reviews, Vol. 19, pp. 255-274,
2013. doi:10.1016/j.rser.2012.11.035 .
[71] A. Beylot, J. Payet, C. Puech, N. Adra, P. Jacquin, I.
Blanc, and D. Beloin-Saint-Pierre, D.,,“Environmental
impacts of large-scale grid-connected ground-mounted
PV installations”, Renewable Energy, Vol. 61, pp. 2–6,
2014.
[72] M. Raugei, S. Bargigli, and S.Ulgiati, “Life cycle
assessment and energy pay-back time of advanced
photovoltaic modules: CdTe and CIS compared to poly-
Si”, Energy, Vol. 32, pp.1310-1318, 2007.
[73] T. Muneer, S. Younes, N. Lambert, and J. Kubie, “Life
cycle assessment of a medium-sized
photovoltaic facility at a high latitude location”. Proc Inst
Mech Eng Part A Journal of Power and Energy, Vol. 220,
pp.517–24, 2006. DOI: 10.1243/09576509JPE253
[74] M. Perez, V. Fthenakis H. Kim, and APereira, “Façade–
integrated photovoltaics: a life cycle
and performance assessment case study”, Prog
Photovoltaics Res Appl. Wiley-Blackwell, Vol. 20, pp.
975–90, 2012.
[75] Acciona Energía, Environmental Product Declaration of
Electricity Generated in Photovoltaic Power Plant: El
Romero Solar 196 MW, 2017.
[76] V. Fthenakis and E. Alsema, “Photovoltaics Energy
Payback Times, Greenhouse Gas Emissions and External
Costs: 2004–early 2005 Status”, Progress in
Photovoltaics Research and Applications, Vol.14, pp.
275-280, 2006 DOI: 10.1002/pip.706
[77] V. Fthenakis, W. Wang, H. Kim, “Life cycle inventory
analysis of the production of metals used in
photovoltaics”, Renewable Sustainable Energy Rev. Vol.
13, pp. 493–517, 2009.
[78] F. Querini, S. Dagostino, S. Morel, and P. Rousseaux,
“Greenhouse gas emissions
of electric vehicles associated with wind and photovoltaic
electricity”, Energy Procedia Vol. 20, pp. 391–401, 2012.
[79] H. Sengul, and T. Theis, “An environmental impact
assessment of quantum dot
photovoltaics (QDPV) from raw material acquisition
through use”, J. Cleaner Prod, Vol. 19, pp. 21–31, 2011.
[80] M. Milousi, M. Souliotis, G. Arampatzis, and S.
Papaefthimiou, “Evaluating the environmental
performance of solar energy systems through a combined
life cycle assessment and cost
analysis”, Sustainability, Vol.11, pp. 2539, 2019.
[82] B. Kim, J. Lee, K. Kim, and T. Hur, “Evaluation of the
environmental performance of sc-Si and mc-Si PV
systems in Korea”, Sol. Energy, Vol. 99, pp.100–114,
2014.
[83] W. Luo, Y. Khoo, A. Kumar, J. Low, Y. Li, Y. Tan, Y.
Wang, A. Aberle, and S. Ramakrishna, “A comparative
life-cycle assessment of photovoltaic electricity
generation in Singapore by multicrystalline silicon
technologies”, Sol. Energy Mater. Sol. Cells, Vol. 174,
pp. 157–162, 2018.
[84] G. Hou, H. Sun, Z. Jiang, Z. Pan, Y. Wang, X. Zhang,
Y. Zhao, and Q. Yao, “Life cycle assessment of grid-
connected photovoltaic power generation from crystalline
silicon solar modules in China”, Appl. Energy, Vol. 164,
pp.882–890, 2016.
[85] R. Kommalapati, A. Kadiyala, M. Shahriar, Z. Huque,
“Review of the Life Cycle Greenhouse Gas Emissions
from Different Photovoltaic and Concentrating Solar
Power Electricity Generation Systems”, Energies, Vol.
10, pp. 350, 2017. https://doi.org/10.3390/en10030350
[86] N. Stylos, and C. Koroneos, “Carbon footprint of
polycrystalline photovoltaic systems”, J. Clean. Prod,
Vol. 64, pp. 639–645, 2014.
[87] Y. Fu, X. Liu, and Z. Yuan, “Life-cycle assessment of
multi-crystalline photovoltaic (PV) systems in China”, J.
Clean. Prod.,Vol. 86, pp.180–190, 2015.
[88] B, Huang, J. Zhao, J. Chai, B. Xue, F. Zhao, and X.
Wang, “Environmental influence assessment of China’s
multi-crystalline silicon (multi-Si) photovoltaic modules
considering recycling process”, Sol. Energy, Vol. 143,
pp. 132–141, 2017.
[89] P. Stolz, R. Frischknecht, K. Wambach, P. Sinha, and
G. Heath, “Life cycle assessment of current photovoltaic
module recycling”, IEA PVPS Task 12, International
Energy Agency Power Systems Programme, Report IEA-
PVPS T12, 13, 2017.
[90] C. Latunussa, F. Ardente, G. Blengini, and L. Mancini,
“Life Cycle Assessment of an innovative recycling
process for crystalline silicon photovoltaic panels:, Sol.
Energy Mater. Sol. Cells, Vol. 156, pp. 101–111, 2016.
[91] Pal, A., and Kilby, J. “Using Life Cycle Assessment to
Determine the Environmental Impacts Caused by Solar
Photovoltaic Systems”, E3S Web of Conferences, 122,
02005, 2019. doi:10.1051/e3sconf/201912202005
[92] G. Gasa, A. Lopez‐Roman, C. Prieto, and L. Cabeza,
“Life Cycle Assessment (LCA) of a Concentrating Solar
Power (CSP) Plant in Tower Configuration with and
without Thermal Energy Storage (TES)”, Sustainability,
Vol. 13, pp. 3672, 2012. https://doi.org/10.3390/su
13073672
[93] M. Whitaker, G. Heath, J. Burkhardt, and C. Turchi,
“Life Cycle Assessment of a Power Tower Concentrating
Solar Plant and the Impacts of Key Design Alternatives”,
Environmental Science & Technology, Vol. 47, PP.
5896–5903, 2013. doi:10.1021/es400821x
[94] J. Burkhardt, G. Heath, E. Cohen, “Life Cycle
Greenhouse Gas Emissions of Trough and Tower
Concentrating Solar Power Electricity Generation.
Systematic Review and Harmonization”, Journal of
INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH
A. Marashli et al., Vol.12, No.2, June 2022
920
Industrial Ecology”, Vol. 16, pp.93-109, 2012. DOI:
10.1111/j.1530-
9290.2012.00474.x.
[95] B. Corona, G. Miguel, and E. Cerrajero,“Life cycle
assessment of concentrated solar power (CSP) and the
influence of hybridising with natural gas”, The
International Journal of Life Cycle Assessment, Vol, 19,
pp.1264-1275, 2014.
[96] F. Asdrubali, G. Baldinelli, F. D’Alessandro, F.
Scrucca, “Life cycle assessment of electricity production
from renewable energies: Review and results
harmonization”, Renewable and Sustainable Energy
Reviews .Vol. 42, pp. 1113-1122, 2015.
[97] Asdrubali, F., Baldinelli ,G., Presciutti, A, Baldassarri
,C, Scrucca, F, “Comparative Analysis of Solar Power
Technologies Through Life Cycle Assessment
Approach’, 3rd International Exergy, Life Cycle
Assessment, and Sustainability Workshop & Symposium
(ELCAS3), NISYROS – GREECE, 07 -09 July, 2013
[98] N. Ko, M. Lorenz, R. Horn, H. Krieg, M. Baumann,
“Sustainability Assessment of Concentrated Solar Power
(CSP) Tower Plants‐Integrating LCA, LCC and LCWE in
One Framework”,Procedia CIRP, Vol. 69, pp. 395–400,
2018. doi:10.1016/j.procir.2017.11.049.
[99] A. Ziemińska-Stolarska, M. Pietrzak, and I. Zbiciński,
“Application of LCA to Determine Environmental Impact
of Concentrated Photovoltaic Solar Panels—State-of-the-
Art”, Energies, Vol. 14, pp. 1-20, 2021.
[100] F. Cavallaro, and L. Ciraolo, “A Life Cycle
Assessment (LCA) of a Paraboloidal-Dish Solar Thermal
Power Generation System", First International
Symposium on Environment Identities and
Mediterranean Area, pp. 260-265, 2006. doi:
10.1109/ISEIMA.2006.344933.
[101] I. Bhat, and R., Prakash, “LCA of renewable energy
for electricity generation systems—a review”, Renewable
and sustainable energy reviews, Vol. 13(5), pp. 1067-
1073, 2009.
[102] J. Payet, and T. Greffe, “Life Cycle Assessment of
New High Concentration Photovoltaic (HCPV) Modules
and Multi-Junction Cells”, Energies, Vol. 12, pp. 1-24,
2019.
[103] IPCC, Guidelines for National Greenhouse Gas
Inventories, 2006.
[104] www.world-nuclear.org. “Comparison of Lifecycle
Greenhouse Gas Emissions
of Various Electricity Generation Sources”, From
the Nuclear Power Economics and Project Structuring
Report WNA Report, 2011
[105] T. Bruckner, L. Fulton, E. Hertwich, A. McKinnon, D.
Perczyk, J. Roy, R. Schaeffer, S. Schlömer, R. Sims, P.
Smith, and R. Wiser, “Technology-specific cost and
performance parameters [annex III]”, In Climate Change
2014: Mitigation of Climate Change (pp. 1329-1356).
Cambridge University Press. 2014
[106] R. Turconi, A. Boldrin, and T. Astrup, “Life cycle
assessment (LCA) of electricity generation technologies:
Overview, comparability and limitations”, Renewable
and Sustainable Energy Reviews, Vol. 28, pp. 555-565,
2013 DOI: 10.1016/j.rser.2013.08.013.
[107] B, Kurşun, H. Öztaş, H. Kuzgun, “Rüzgar enerjisi ve
çevresel potansiyelinin Keşan
örneği üzerinden incelenmesi”, Int. J. Adv. Eng. Pure Sci.
Vol 1, pp. 41–47, 2019.
[108] E. Masanet, Y. Chang, A. Gopal, P, Larsen, W.
Morrow III, R. Sathre, A. Shehabi, and P. Zhai, “Life-
cycle assessment of electric power systems”, Annual
Review of Environment and Resources, Vol. 38, pp. 107-
136, 2013.
[109] Ecoinvent, Ecoinvent database v2.2. Swiss Centre for
Life Cycle Inventories, 2010
[110] H. Wagner, C. Baack, T. Eickelkamp, A. Epe, J.
Lohmann, and S. Troy, “Life cycle assessment of the
offshore wind farm Alpha Ventus”, Energy, Vol. 36, pp.
2459-2464, 2011.
[111] R. Thomson, and G. Harrison, Life cycle costs and
carbon emissions of offshore wind power: Main report.
Edinburgh, Scotland: ClimateXChange, 2015.