Conceptual Life Cycle Process Description
The life cycle of a c-Si PV system has upstream, operation, and downstream phases (figure 1). The upstream phase starts with the acquisition of raw materials, such as silica sand and iron ore. After these raw materials are acquired, energy is required to process them into other materials, such as crystalline silicon and steel. Energy is then required to manufacture the components for the solar module and the PV system as a whole. The building block of a PV system is a PV cell. A PV cell is a semiconductor device that converts solar energy into electricity. A module is a panel of electrically connected solar PV cells, and in addition to the cells, includes the frame and glass. A PV array consists of several connected modules. The PV system consists of the array plus balance-of-system (BOS) components, which are needed to provide structural support and to deliver electricity to a facility or the grid. The BOS includes wiring, mounting hardware, and inverters. Batteries are normally part of the BOS, but none of the studies in the final harmonization pool nor the final harmonized scenario included battery storage. For an illustration of PV cell, module, and array, see figure S1 in the supporting information available on the journal's Web site. All components are then transported to the site and installed. Prior to operation, most GHGs in the life cycle of c-Si PVs have been emitted (e.g., Frankl et al. 2005). After the solar PV system has been installed, the operation life cycle phase includes activities such as module washing, preventive maintenance (e.g., replacement of inverters), and replacement of any components that break. PV systems have minimal operation and maintenance requirements, and, as such, the GHG emissions from this stage are small (e.g., estimated to be close to zero (Frankl et al. 2005; Uchiyama 1997)]. After the PV system reaches the end of its life, the downstream life cycle phase includes system decommissioning, with parts disposed of or recycled.
Collection of Literature and Initial Screening
The study began with a literature search, amassing 397 journal articles, reports, theses, conference papers, technical reports, trade publications, and presentations relating to LCAs of PVs, including c-Si, thin-film, and other PV technologies. Multiple GHG emission estimates from a single study were possible if alternative PV generation scenarios or technologies were analyzed. Each estimate of life cycle GHG emissions was independently subjected to two rounds of review, consistent with the screening methodology of the umbrella LCA harmonization study conducted by the National Renewable Energy Laboratory (NREL).2 (Several articles reporting harmonized results for other electricity generation technologies appear in this special issue, including Burkhardt and Heath , Dolan et al. , Kim et al. , Warner and Heath , and Whitaker et al. .) Although an entire reference was not necessarily eliminated if only one of its estimates was screened out, most screening criteria applied to the study as a whole, thereby likely eliminating all estimates in a study.
An initial screen removed studies lacking sufficient documentation necessary for harmonization: conference papers less than or equal to five double-spaced pages; trade journal articles less than or equal to three published pages; and presentations, posters, and conference abstracts. In addition, studies published prior to 1980 were filtered out due to obsolete technology and data inventories. References not available in English were also removed. Although a life cycle, by definition, includes several stages of a product's life from manufacture to end of life, PV LCAs do not need to focus on all life cycle stages because the GHG emissions of solar PVs are heavily weighted toward upstream operation, such as material production and component manufacturing (e.g., Frankl et al. 2005). Thus studies that did not account for downstream life cycle phases were not removed from consideration in this analysis. This initial screen yielded 241 studies, of which 129 studies evaluated c-Si PVs.
The second screen consisted of three main criteria:
- 1Quality: The study had to employ a currently accepted LCA methodology (e.g., following ISO 14040 series standards [ISO 2006]). The study also had to have at least considered life cycle impacts from the materials extraction and component manufacturing stages, which have been found to be the largest contributors to total GHG emissions for c-Si PV systems (e.g., Frankl et al. 2005).
- 2Transparency: The study must have at a minimum described its methods, sources, and values of input data (life cycle inventory [LCI] data, performance characteristics, etc.) and the LCA results.
- 3Modern relevance: The evaluated technology must be relevant to current or near future c-Si PVs.
The last criterion eliminated many estimates that used outdated LCI data or made assumptions not applicable to current technologies. For example, Kannan and colleagues (2007) cite a report by Knapp and Jester (2001) as a source of data for the materials and energy required in manufacturing; the Knapp and Jester report describes early production by Siemens in California, which utilized now-obsolete production methods.
The second screen reduced the number of studies to 77, 58 of which assessed c-SI PVs.
Selection of the Harmonization Pool
After gathering the pool of articles that passed the second screen, we selected our group for harmonization on the basis of usability, nonduplication, and consistency of application.
- 1Usability: Articles must report life cycle GHG emissions; many articles that passed the second screen, although rigorous studies, did not report life cycle GHG emissions. Also, to limit transcription error, the results had to be reported numerically, not just graphically. Finally, values of several key parameters had to have been reported to be considered for harmonization. If the studies did not report the specific parameter value for each scenario evaluated, but those parameters could be calculated from information in the study using no exogenous assumptions, the scenario estimate was included. We also contacted authors for additional information, and if they provided the information, the scenario estimate was included even if the published version did not include all the necessary parameters. The required parameters were
- a. module conversion efficiency (the percentage of the solar energy converted to direct current [DC] electricity by the module [unitless]),
- b. performance ratio (the ratio of the alternating current [AC] electricity actually produced by the PV system, after accounting for system losses, to the electricity calculated based on the DC-rated module efficiency and irradiation [unitless]),
- c. irradiation (the average energy flux from the sun, in kilowatt-hours per square meter per year [kWh/m2/yr]),3 and
- d. system lifetime (the years that a PV system operates, with routine maintenance and repairs, before severe degradation in its ability to produce electricity).
- 2Nonduplication: Only original LCA results passed. Many studies cite results from other articles but do not contain any improvements or reinterpretations to the LCA of GHG emissions; we eliminated these articles from our analysis. For example, review papers that did not generate original emissions estimates were excluded. In cases where the same research group published serially on the same technology, when two studies did not report significantly different LCIs or results, we only included the latest or most complete reference; including multiple studies from the same research groups could artificially tighten the distribution.
- 3Consistency of application: We eliminated the work of Hayami and colleagues (2005) because that study looked at applications in space and thus was not included in the pool of our studies, which is limited to terrestrial applications. We also excluded the work of Nawaz and Tiwari (2006), as we could not separate the contribution of battery storage from that for the PV system.
The final screening of the harmonization pool resulted in 13 studies and 41 estimates. The studies used in our meta-analysis are listed with the key performance characteristics of each estimate in tables 1 and 2.
Table 1. Monocrystalline PV LCA studies that passed final screening, with parameter values and characteristics from those studies.
|Alsema and de Wild-Scholten||2006|| 45||1,700||14||0.75||30||Rooftop||Southern Europe|
|Frankl et al.||2005|| 68|| 900||14||0.93||25||Rooftop||Central Europe|
| || || 36||1,800||14||0.87||25||Rooftop||Southern Europe|
| || || 76|| 900||14||0.86||25||Rooftop||Central Europe|
| || || 41||1,800||14||0.79||25||Rooftop||Southern Europe|
| || || 73|| 900||14||0.92||25||Rooftop||Central Europe|
| || || 39||1,800||14||0.86||25||Rooftop||Southern Europe|
| || || 69|| 900||14||0.88||25||Ground-mounted||Central Europe|
| || || 37||1,800||14||0.83||25||Ground-mounted||Southern Europe|
|Jungbluth et al.||2009|| 64||1,117||14||0.75||30||Rooftop||Switzerland|
| || || 69||1,117||14||0.75||30||Rooftop|| |
|Pacca||2003|| 30||2,143||12.7||1||20||Ground-mounted||Arizona, USA|
| || ||100||1,752||12.7||1||20||Ground-mounted||Brazil|
Table 2. Multicrystalline PV LCA studies that passed final screening, with parameter values and characteristics from those studies.
|Alsema and de Wild-Scholten||2000||60||1,700||13||0.75||30||Ground-mounted||Western Europe|
| || ||30||1,700||15||0.75||30||Ground-mounted|| |
| || ||20||1,700||17||0.75||30||Ground-mounted|| |
|Frankl et al.||2005||82|| 900||13||0.93||25||Ground-mounted||Central Europe|
| || ||44||1,800||13||0.87||25||Ground-mounted||Southern Europe|
| || ||93|| 900||13||0.86||25||Rooftop||Central Europe|
| || ||50||1,800||13||0.79||25||Rooftop||Southern Europe|
| || ||88|| 900||13||0.92||25||Rooftop||Central Europe|
| || ||47||1,800||13||0.86||25||Rooftop||Southern Europe|
| || ||85|| 900||13||0.88||25||Rooftop||Central Europe|
| || ||46||1,800||13||0.83||25||Rooftop||Southern Europe|
|Fthenakis and Alsema||2006||36||1,700||13.2||0.75||30||Rooftop||Europe|
| || ||44||1,314||14||0.77||30||Rooftop|| |
|Jungbluth et al.||2009||57||1,117||13.2||0.75||30||Rooftop||Switzerland|
| || ||62||1,117||13.2||0.75||30||Rooftop|| |
|Lenzen et al.||2006||106||2,060||13||0.85||25||Rooftop||Australia|
| || ||217||2,060||12||0.8||20||Rooftop|| |
| || ||53||2,060||14||0.9||30||Rooftop|| |
|Pacca et al.||2006||72||1,359||12.92||0.95||30||Rooftop||Michigan, USA|
|Pehnt et al.||2002||102||950||13.4||0.85||25||Rooftop||Central Europe|
| || ||57||1,700||13.4||0.85||25||Rooftop||North Africa|
|Tripanagno-stopoulos et al.||2006||55||1,644||12.4||0.85||30||Rooftop||Greece|
| || ||51||1,644||12.4||0.85||30||Rooftop|| |
| || ||62||1,644||12.4||0.85||30||Rooftop|| |
Unlike a similar meta-analysis on thin-film LCAs (Kim et al. 2012), the literature used in this study by necessity was not based on real-world manufacturing data. Silicon PV processing technology is fairly mature and much process information is publicly available. Thin-film processes, such as amorphous silicon, cadmium telluride, and copper indium gallium selenide, are less prevalent, and information on those processes is often only available through the manufacturers. Because the c-Si analysis is not based exclusively on empirical manufacturing data, the results of this article do not represent the current state of c-Si manufacturing.
For the LCA harmonization project as a whole, two levels of harmonization were devised. The more resource-intensive level uses a process similar to one employed by Farrell and colleagues (2006) to harmonize the results of LCAs on ethanol, whereby a subset of the available literature estimates of life cycle GHG emissions was carefully disaggregated to produce a detailed meta-model based on adjusted parameter estimates, realigned system boundaries within each life cycle phase, and a review of all data sources. A less intensive approach harmonizes a larger set of literature estimates of life cycle GHG emissions at a more gross level. This is done, for instance, by adjusting several influential performance characteristics to consistent estimates and common system boundaries. The latter, less intensive approach was chosen for c-Si PVs, as will be discussed later. The literature available generally did not provide enough detail to apply the more intensive approach.
We created a spreadsheet-based meta-model to harmonize GHG results based on similar assumptions. The harmonization methodology is described in the context of the equation needed to calculate the GHG emissions for solar PVs:
where GHG is the mass emissions of GHGs weighted by their global warming potential (GWP) per unit of electricity generated (g CO2-eq/kWh), W is the GWP-weighted mass of GHGs emitted over the lifetime of the PV system (g CO2-eq), I is the irradiation (kWh/m2/yr), η is the lifetime average module efficiency (%), PR is the performance ratio, LT is the system lifetime (yr), and A is the total module area (m2). This calculation, used in most PV LCA studies, encompasses two characteristics of the technology. The numerator sums all of the GHG emissions from all components and life cycle phases and weights each GHG by GWP, while the denominator calculates the power output over the lifetime of the PV system. In the harmonization process, several factors affecting the denominator are standardized, and GHG is recalculated based on these new factors, producing a “harmonized” result.
To harmonize, we first selected standard values for power production parameters in the denominator of equation (1). These factors vary over the literature. Irradiation depends on location. Several studies (Alsema 2000; Alsema and de Wild-Scholten 2006; Pehnt et al. 2002; Fthenakis and Alsema 2006) use an irradiation value of 1,700 kWh/m2/yr, corresponding to the average irradiation in southern Europe. We report results based on an irradiation of 1,700 kWh/m2/yr to be aligned with much of the published literature. However, the average irradiation in the United States is higher, at 1,800 kWh/m2/yr for latitude-tilt, south-facing planes. In addition, the southwest United States accounts for a large portion of the current U.S. PV installations and is a targeted region for concentrating solar power, a technology often compared to silicon PVs. Because of the relevance of the southwest United States, we also report in this article and in the supporting information on the Web the harmonized results for 2,400 kWh/m2/yr, based on irradiation in Phoenix, Arizona (Moore et al. 2005). The modules are assumed to be at a latitude-tilt for the location, and the effect of the tilt is assumed to be included in the performance ratio. Even though some of the input LCI data in the studies may be specific to a particular region, the studies were harmonized to one location because PV systems manufactured in one location can be installed and operated in another location.
Module efficiencies are always improving, but in this study we chose an initial efficiency of 14.0% for mono-Si and 13.2% for multi-Si based on the Crystal Clear database, a collection of data representing c-Si PVs production technology in Western Europe in 2005–2006 (de Wild-Scholten 2007). The efficiencies degrade over the system lifetime by 0.5% (relative to the initial efficiency) per year (Granata et al. 2010), resulting in an average efficiency over the 30-year lifetime of 13.0% for mono-Si and 12.3% for multi-Si. The lifetime average efficiency was used in harmonization.
The lifetime of a PV system was set at 30 years, as recommended by guidelines from the International Energy Agency (IEA) (Alsema et al. 2009). Many companies provide a 25-year limited warranty for their solar panels, so 30 years is a realistic working lifetime. Additionally, based on observations of solar modules operating longer than 20 years, one study concluded that the modules were unlikely to reach a definite point of failure, but instead were likely to gradually degrade (Skoczek et al. 2009).
Because we are reporting GHG emissions per unit of electricity generated, a harmonization standard was not needed for the system or module area.
For the performance ratio, rooftop and building-integrated systems were assigned a performance ratio of 0.75 and ground-mounted systems were assigned a performance ratio of 0.80; both of these performance ratios were recommended in the IEA guidelines (Alsema et al. 2009). Table 3 lists all harmonization parameters and their selected values.
Table 3. List of parameters that were harmonized in this study and the standard values used in harmonization.
| Performance ratio |
| Module efficiency |
| Monocrystalline||Initial % (lifetime average %)||14.0 (13.0)|
| Multicrystalline||Initial % (lifetime average %)||13.2 (12.3)|
| Solar irradiation||kWh/m2/yr||1,700|
Because the factors affecting the lifetime power production are multiplied together, each estimate of lifetime electricity production from references passing the screens can be harmonized by multiplying the reported parameter by a multiplicative factor: the ratio of the harmonized parameter standard to the as-reported parameter value. For example, if the irradiation in a study is 1,800 kWh/m2/yr, the lifetime kilowatt-hours are multiplied by a factor of 0.944 (1,700 divided by 1,800) to achieve the harmonized lifetime electricity production, assuming a location in southern Europe. The harmonized result is calculated by dividing the study's GHG emissions by the harmonized lifetime electricity production. Similarly, the harmonized results in this article can be easily calculated for a different parameter estimate using a different multiplicative factor.
The lifetime GHG emissions, however, cannot be harmonized using an analogous multiplicative approach, as the numerator of equation (1) comprises the sum of GHG emissions (weighted by GWPs) from each life cycle stage. GHG emissions from the operation and downstream life cycle stages result mainly from activities (e.g., operation and maintenance, dismantling), and have been shown to be small (e.g., Frankl et al. 2005). In contrast, for the upstream stage, which contributes the majority of GHG emissions, embodied GHG emissions in the materials used in the PV components are most important. Potential factors for harmonization in the numerator include (1) entire life cycle stages such as downstream emissions (recycling, decommissioning), which may potentially be standardized to one value; (2) system boundary, namely the inclusion and exclusion of stages or process within a stage, such as research and development; (3) individual parameters that affect one or more life cycle stages, such as wafer thickness and kerf loss (silicon material lost from sawing).
In our analysis, the numerator was not harmonized due to insufficient reporting across all studies with the exception of one study whose GWPs were harmonized. In that instance, the harmonization step was conducted separate from the main harmonization and reported separately from the general results.
The results were categorized by technology type (mono-Si and multi-Si) and by mounting type. Mounting includes rooftop mounting, commonly used for residential PV systems, and ground-mount, commonly used for utility-scale PV systems. We report descriptive statistics of the reported GHG emissions and the harmonized GHG emissions. The median is used as the main measure of central tendency and interquartile range (IQR) (75th minus 25th percentile values) is used as the main measure of variability. These measures are more robust to outliers than mean, range, and standard deviation. For each harmonization step, changes in the median and IQR are compared with published estimates to describe the impact of the harmonization step.