The Right Place for the Right Job in the Photovoltaic Life Cycle

Jun 5, 2012 - Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1, Ono...
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The Right Place for the Right Job in the Photovoltaic Life Cycle Kotaro Kawajiri*,§ Laboratory for Manufacturing and Productivity, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States

Yutaka Genchi Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1, Onozawa, Tsukuba, Ibaraki, 305-8569, Japan S Supporting Information *

ABSTRACT: The potential for photovoltaic power generation (PV) to reduce primary energy consumption (PEC) and CO2 emissions depends on the physical locations of each stage of its life cycle. When stages are optimally located, CO2 emissions are reduced nearly ten times as much as when each stage is located in the country having the largest current market share. The usage stage contributes the most to reducing CO2 emissions and PEC, and total CO2 emissions actually increase when PV is installed in countries having small CO2 emissions from electricity generation. Global maps of CO2 reduction potential indicate that Botswana and Gobi in Mongolia are the optimal locations to install PV due to favorable conditions for PV power generation and high CO2 emissions from current electricity generation. However, the small electricity demand in those countries limits the contribution to global CO2 reduction. The type of PVs has a small but significant effect on life cycle PEC and CO2 emissions. knowledge, our study is the first to consider locations throughout the entire world in an assessment of CO2 emissions and PEC over the entire PV life cycle. Previous studies have pointed out two key problems in analyzing the geological impacts on the life cycle of CO2 emissions for PV. First, PV generation potential depends greatly on the environmental conditions of the operating locations.6−8 Second, CO2 emissions and PEC per unit electricity vary around the world.9,10 Adequate consideration of these two problems is critical for finding the most suitable locations for each stage of the PV life cycle. Here, we address both of these problems in regard to the life cycle CO2 emission for PV. To address the first problem, we use a global map of PV generation potential calculated by a new method for estimating PV potential over the entire world.1 To address the second problem, we use an LCA software package that contains the data of CO2 emissions and PEC per unit electricity for most countries in the world.10 The objective of this study is to show how much CO2 emissions and PEC can be reduced through the use of PV by managing the physical locations of its life cycle from a global perspective. The results in this study could be helpful to policy

1. INTRODUCTION Because of the concern for global warming and the risks of nuclear power, renewable energies are gaining interest. Photovoltaic power generation (PV) shows particular promise due to rapid efficiency improvements and cost reductions. PV produces electricity from solar irradiation without release of any CO2, so during its usage stage, it eliminates the CO2 emissions from carbon intensive energy sources by replacing their primary energy consumption (PEC). However, CO2 is emitted during the PV manufacturing stages. Life cycle assessment (LCA) can be used to analyze the total CO2 emissions and PEC for PV and to identify which stages are the most CO2 intensive. A difficulty in conducting LCAs of products whose manufacture uses a lot of electricity, such as PV, is that the total CO2 emissions and PEC strongly depend on the physical location of each manufacturing stage because of regional variations in the CO2 emissions and PEC per unit of electricity generated. On the other hand, PV energy generation strongly depends on the environmental conditions of its operating location.1 Nowadays, stages of the life cycle of PV can occur in many different countries. By relocating CO2 intensive stages to different parts of the world, it may be possible to reduce the life cycle CO2 emissions and PEC of PV. Although there are many previous LCA studies of PVs,2−5 the few studies that have investigated location effects6−9 focus on either the manufacturing stages or the usage stage, or they limit the scope of the assessment to a few regions. To our © 2012 American Chemical Society

Received: Revised: Accepted: Published: 7415

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We use the method described in ref 1 to estimate the PV electricity generation potential at the usage stage for PV systems mounted on a platform above ground and operated under direct connection to the grid without a battery. As in ref 1, we set the design factor K′ to 0.75 for multicrystalline Si (mcSi) and single crystalline silicon (sc-Si) PV modules and 0.77 for amorphous Si/microcrystalline Si hybrid thin Si (thin-Si) PV module, and we set the maximum power temperature coefficient to −0.004 °C−1 for mc-Si and sc-Si PV modules and −0.002 °C−1 for thin-Si PV module.11 It is assumed that module efficiencies of mc-Si, sc-Si, and thin-Si are 13.9, 14.3, and 8.6%, respectively.5 The detailed specifications of each module are shown in Supporting Information Table 2. The PEC and CO2 emission per unit electricity for each of the countries we consider are estimated using the AIST-LCA ver.5 life cycle assessment software 10 together with data from OECD reports.12,13 The PEC and CO2 emissions at each stage are obtained for each country using the values in Supporting Information Tables 1, 2, 3, and 4 and their PV potential.1 We assume that the indirect PEC and CO2 emissions from manufacturing the materials at each stage and the BOS are constant. We do not consider PEC and CO2 emissions from transport and recycling in this study. In addition, like in previous studies such as ref 2, here, we have assumed a linear relationship between inputs and outputs at each stage. If the scale of PV introduction is large enough to affect economies of scale, it might be necessary to consider nonlinearities between inputs and outputs, as well as other consequences of large scale PV, such as power supply stability

makers to assess the potential for PV to address the problems of global warming and energy shortage and to design effective policy interventions for doing this most efficiently.

2. METHOD 2.1. System Boundary and Combinations of Countries in the PV Life Cycle. Table 1 shows four different Table 1. Combinations of the Countries for the PV Life Cycle in Each Case Study stage stage stage stage stage stage stage

1 2 3 4 5 6 7

case 1

case 2

case 3

case 4

case 5

US CN CN CN CN CN DE

CA JP NO JP JP ES US

CA JP NO JP JP ES Tibet

CA JP NO JP JP ES Gobi

CA JP NO JP JP ES Nepal

combinations of countries for each stage of the PV life cycle: production of solar grade silicon (Si) metal (Stage 1), production of poly-Si (Stage 2), production of Si ingot (Stage 3), production of Si wafer (stage 4), production of PV cell (stage 5), production of PV module (Stage 6), and usage and disposal of PV (Stage 7). We assume that the CO2 emissions and PEC for manufacturing the balance of system (BOS) are constant. The BOS includes the steel module supports, cabling, and power conditioning equipment. We assume that the lifetime of power conditioning equipment is 10 years, so the equipment is replaced once during the PV’s lifetime. We selected combinations of the five countries having the largest supply capacity or PV installation for each stage of the PV life cycle (see Supporting Information Table 1). In addition, for Stage 7, we include Tibet, the Gobi desert in Mongolia, and Nepal. Tibet and Nepal are located in the Himalayan region, which has one of the largest PV potentials in the world.1 However, while China produces their electricity using a lot of coal and therefore has large CO2 emissions and PEC per unit electricity, the CO2 emission per unit electricity in Nepal is quite small because electricity is produced mainly by hydropower. The Gobi desert also has a large PV potential, and Mongolia has large CO2 emissions and PEC per unit electricity. Case 1 is the baseline case where each life cycle stage is located in the country that currently has the largest share for that stage, and the PV is installed in Berlin, Germany. Unfortunately, this is also one of the worst combinations of the top five countries for reducing CO2 emissions, due to the high CO2 emissions from electricity generation in the US and China (see Supporting Information Table 1) and the small PV potential in Germany.1 In case 2, we locate each stage of PV manufacture in the top five country for that stage having the lowest CO2 emissions per unit electricity, and we assume that the PV is installed in Los Angeles, US. Cases 3, 4, and 5 are the same as Case 2 except that the PV is installed in Tibet, Gobi, and Nepal, respectively. 2.2. Estimation of PEC and CO2 Emissions at Each Stage. In this study, the functional unit for the analysis is 1 kW PV producing electricity for 20 years. The main variables that are affected by the location are irradiation and temperature at the usage stage to estimate the PV electricity generation and PEC/CO2 emission per unit electricity at all stages.

3. RESULTS AND DISCUSSION 3.1. Life Cycle Analysis. Figure 1a shows the PEC and energy payback time (EPT) of mc-Si PV, currently the most popular type of PV module, in each case study. As shown in the figure, the reduction in PEC by mc-Si PV at the usage stage is nearly five times larger than the PEC to manufacture mc-Si PV in Case 1. In addition, optimizing the locations of the manufacturing stages reduces PEC to manufacture 1 kW mcSi PV by just 0.6 GJ or 2.6% of the total manufacturing PEC of 23 GJ. Therefore, the total PEC and EPT are dominated by the usage stage. Compared with Case 1, PEC nearly doubles when the present best locations in Case 2 are used, nearly triples in Case 3, and nearly quadruples in Case 4. The EPT, which is more than 3 years in Case 1, is just over 18 months in Case 2, about 14 months in Case 3, and about 9 months in Case 4. In contrast, the reduction in PEC and EPT in Case 5 are smaller than even that in Case 1 in spite of the large PV potential in the Himalayan region.1 This is because the PEC per unit electricity is small in Nepal. Figure 1b shows the CO2 emissions and CO2 payback time (CPT) of mc-Si PV in each case study. The total CO2 emissions from manufacturing stages in Case 1, 1.7 tons for 1 kW PV, are reduced by 0.5 tons, or nearly 30%, in Case 2. Therefore, unlike with PEC, optimizing locations of the manufacturing stages can produce meaningful reductions of CO2 emissions. However, changing the location of the usage stage reduces CO2 emissions by 9.4 tons or more for 1 kW PV producing electricity for 20 years. Therefore, the location of the usage stage also has the largest effect on reducing CO2 emissions. The total CO2 reduction, which is 5.8 tons in Case 1, is nearly 3 times larger in Case 2, 5 times larger in Case 3, and 9 times larger in Case 4. Because the optimal locations were chosen for low CO2 emissions, the effect of location on 7416

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Figure 1. PEC and CO2 emissions for mc-Si PV in each case study.

CO2 emissions is larger than that on PEC. This reflects the differences in the ratio of fossil fuel use for electricity generation in the different countries. On the other hand, the total emission of CO2 is actually positive in Case 5 because the total CO2 reduction during the usage stage is smaller than the CO2 emissions at the manufacturing stages, due to the small CO2 emissions per unit electricity in Nepal. In fact, the PVs would have to generate electricity for 189 years to pay back the CO2 emissions from manufacturing. Other examples of this kind of situation may already be happening now. For example, Switzerland and France, which also have small CO2 emissions per unit electricity, have installed a large amount of PVs. Replacing

Nepal with Switzerland and France in Case 5, the total CO2 emissions become 1.1 tons and −0.08 tons for 1 kW PV, respectively. Note that the positive value for Switzerland means that using PV in Switzerland will actually result in an increase in CO2 emissions. Of course, because Switzerland and France currently use nuclear power, installing PVs can reduce the risk of energy resource shortage and nuclear disaster. However, it is important to understand that CO2 emissions could increase depending on the locations of the PV lifecycle stages. Even for locations that depend heavily on fossil fuel, the CO2 reduction effect varies greatly. For example, to get the same CO2 reduction effect of installing a conventional mc-Si PV with an efficiency of nearly 14% 5 in Gobi, one would need PV 7417

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Figure 2. Annual reductions in PEC and CO2 emissions from installing 1 kW PV and generating electricity.

total PEC reduction and EPT. The potential to reduce PEC is largest in regions such as Botswana and Mongolia. The high PEC potentials result from combining large PV potentials with large PECs per unit electricity, which are nearly double of the average value in non-OECD countries of 9.8 MJ/kWh due to inefficient power plants. Previously, we reported that the Himalayan and Andes regions have large PV potentials.1 However, the PECs per unit electricity in those regions are smaller than those of Botswana and Mongolia, so the total PEC reduction is not as large. Figure 2b shows the annual CO2 reduction resulting from installing 1 kW mc-Si PV around the world. Like with PEC, the best locations to install mc-Si PV to reduce CO2 emissions are Mongolia and Botswana. Because they use a lot of coal fired power plants, the CO2 emissions per unit electricity in Botswana and Mongolia are 1.81 and 1.68 kg/kWh, respectively, almost triple the average for the non-OECD countries of 0.65 kg/kWh. Therefore, despite the large PV potentials in the Himalayan and Andes regions,1 the total CO2 reduction potentials are larger in Botswana and Mongolia. The countries north and west of Botswana have markedly smaller CO2 emission reductions because the CO2 emissions per unit electricity are smaller. This further demonstrates the importance of a country’s energy source on calculation of total CO2 emissions. 3.3. Relationship between Electricity Demand and CO2 Reduction Potential. The data for countries with large electricity demand and large potential of annual CO2 reduction are shown in Table 2. The land area and electricity demand are obtained from World Development Indicator (WDI) database;21 total irradiation potential and total PV potential are

having an efficiency of 49% in Los Angeles. This value is over the theoretical limit of conventional single layer PV14 and is equivalent to the maximum efficiency that has been achieved by multilayer PV in laboratories.15 Installing PV in the most suitable locations in the world can reduce CO2 emissions and PEC without requiring radical technological developments. While changing the countries of manufacturing stages produces a smaller reduction in CO2 emissions than changing the country of the usage stage, it still results in significant changes in CPT. The reduction in CO2 emissions during manufacturing stages from Case 1 to Case 2 results in nearly 30% reduction in CPT. Recently, concern has been raised about what will happen when additional energy consumption or CO2 emissions to replace conventional power plants becomes large.16−20 Reducing the PEC or CO2 emissions in the manufacturing stages makes it easier to replace conventional power without increasing PEC or CO2 emissions.20 However, one problem is the manufacturing capacity at each stage. The share of supply capacity of each country for each manufacturing stage in the optimal case is relatively small. It may be difficult for those countries to rapidly increase their capacity to cover the global demand while keeping their CO2 emissions and PEC per unit electricity at the current level. 3.2. Global Map of Reduction Potentials in Annual PEC and CO2 Emissions. Figure 2a shows the annual reduction in PEC resulting from installing 1 kW mc-Si PV around the world; black regions show countries where the required data are not available. The map is obtained from the calculated mc-Si PV potential 1 and the PEC in each country. Using this map together with the PECs for the manufacturing stages of mc-Si PV from Figure 1a, we can roughly estimate the 7418

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Table 2. Characteristics of Countries (a) Countries with Lame Electricity Demands

country

country

US

United States China Japan Russian federation India Germany Canada France Korea, republic of Brazil United kingdom Italy Spain Australia South africa Mexico Saudi arabia Iran, islamic republic Turkey Ukraine

CN JP RU IN DE CA FR KR

BR GB IT ES AU ZA MX SA IR TR UA

country BW MN KZ IN CN CU AU LY ZA YE KH OM SA JM AE MA IL TM MT SN

country Botswana Mongolia Kazakhstan India China Cuba Australia Libyan Arab South Africa Yemen Cambodia Oman Saudi Arabia Jamaica United Arab Emirates Morocco Israel Turkmenistan Malta Senegal

electricity consumption [PWh]

land area [106km2]

total irradiation potential [EWh]

4.16

9.15

14.94

1.53

0.27

1.61 - 1.16 - 0.71

14.95 - 10.76 - 6.59

0.86 - 0.62 - 0.38

3.25 1.03 0.91

9.33 0.36 16.38

16.80 0.53 19.41

1.76 0.05 2.07

0.19 1.92 0.04

1.95 - 1.36 - 0.76 1.18 - 1.06 - 0.95 1.34 - 0.88 - 0.53

19.34 - 13.46 - 7.53 14.23 - 12.81 - 11.46 15.79 - 10.38 - 6.27

1.6 - 1.12 - 0.63 0.63 - 0.57 - 0.51 0.78 - 0.51 - 0.31

0.65 0.59 0.57 0.49 0.43

2.97 0.35 9.09 0.55 0.10

5.81 0.39 11.13 0.73 0.16

0.56 0.04 1.19 0.07 0.02

0.11 1.49 0.05 0.66 2.63

1.81 0.94 1.14 1.25 1.24

20.81 - 15.74 - 12.75 8.99 - 7.79 - 7.3 7.06 - 5.63 - 3.54 12.68 - 9.9 - 8.22 12.4 - 12.14 - 11.88

1.66 - 1.26 - 1.02 0.46 - 0.4 - 0.37 0.2 - 0.16 - 0.1 0.09 - 0.07 - 0.06 0.58 - 0.57 - 0.56

0.43 0.37

8.46 0.24

15.80 0.25

1.52 0.03

0.03 1.47

1.63 - 1.29 - 1.05 0.9 - 0.75 - 0.67

7.47 - 5.93 - 4.84 7.95 - 6.69 - 5.92

0.11 - 0.09 - 0.07 0.42 - 0.35 - 0.31

0.34 0.29 0.24 0.23 0.21 0.19 0.17

0.29 0.50 7.68 1.21 1.94 2.00 1.63

0.48 0.87 16.80 2.67 4.07 4.50 3.25

0.05 0.09 1.63 0.26 0.40 0.43 0.32

0.71 0.33 0.01 0.09 0.05 0.04 0.05

1.42 - 1.17 - 0.98 1.4 - 1.25 - 0.99 1.75 - 1.53 - 1 1.7 - 1.57 - 1.26 1.66 - 1.49 - 1.18 1.74 - 1.55 - 1.41 1.59 - 1.43 - 1.08

11.38 10.56 18.39 16.96 16.74 20.56 13.84

0.59 - 0.49 - 0.41 0.45 - 0.4 - 0.32 1.5 - 1.31 - 0.85 1.45 - 1.33 - 1.07 0.82 - 0.74 - 0.58 1.22 - 1.09 - 0.99 0.74 - 0.67 - 0.51

0.17 0.16

0.77 0.58

total PV potential [PWh]

electricity consumption/total PV potential [%]

PV potential [MWh/kW] max - mean - min

PEC reduction [GJ/ kW·year] max - mean - min

CO2 reduction [t/ kW·year] max - mean - min

-

1.37 0.81 0.91 0.97 1.22

-

1.11 0.76 0.57 0.81 1.19

1.33 0.14 0.13 1.41 - 1.27 - 1.05 0.74 0.08 0.22 1.05 - 0.93 - 0.85 (b) Countries with Potentials for Large Annual CO2 Reduction

-

9.35 - 7.88 9.41 - 7.45 16.04 - 10.46 15.63 - 12.6 14.95 - 11.86 18.32 - 16.65 12.4 - 9.43

9.88 - 8.9 - 7.41 11.55 - 10.21 - 9.35

0.59 - 0.53 - 0.44 0.46 - 0.41 - 0.37

land area [106km2]

total irradiation potential [EWh]

total PV potential [PWh]

electricity consumption/ total PV potential [%]

PV potential [MWh/kW] max - mean - min

PEC reduction [GJ/ kW·year] max - mean - min

CO2 reduction [t/ kW·year] max - mean - min

0.00 0.00 0.07 0.65 3.25 0.01 0.24 0.02 0.23 0.01 0.00 0.01 0.19 0.01 0.08

0.57 1.55 2.70 2.97 9.33 0.11 7.68 1.76 1.21 0.53 0.18 0.31 2.00 0.01 0.08

1.29 2.79 4.20 5.81 16.80 0.22 16.80 3.99 2.67 1.27 0.34 0.71 4.50 0.02 0.19

0.13 0.30 0.43 0.56 1.76 0.02 1.63 0.39 0.26 0.12 0.03 0.07 0.43 0.00 0.02

0.00 0.00 0.02 0.11 0.19 0.07 0.01 0.01 0.09 0.00 0.00 0.02 0.04 0.30 0.43

1.65 - 1.6 - 1.49 1.66 - 1.37 - 1.14 1.36 - 1.15 - 0.99 1.81 - 1.37 - 1.11 1.95 - 1.36 - 0.76 1.61 - 1.43 - 1.32 1.75 - 1.53 - 1 1.77 - 1.58 - 1.28 1.7 - 1.57 - 1.26 1.77 - 1.67 - 1.51 1.37 - 1.34 - 1.25 1.68 - 1.57 - 1.43 1.74 - 1.55 - 1.41 1.5 - 1.5 - 1.5 1.6 - 1.51 - 1.44

32.91 30.79 20.86 20.81 19.34 22.53 18.39 22.76 16.96 19.29 18.58 24.52 20.56 17.72 23.27

-

31.9 - 29.71 25.57 - 21.26 17.52 - 15.19 15.74 - 12.75 13.46 - 7.53 20.11 - 18.54 16.04 - 10.46 20.31 - 16.36 15.63 - 12.6 18.21 - 16.49 18.19 - 16.98 22.96 - 20.81 18.32 - 16.65 17.72 - 17.72 22.06 - 21.06

2.98 - 2.89 - 2.69 2.78 - 2.31 - 1.92 1.74 - 1.46 - 1.27 1.66 - 1.26 - 1.02 1.6 - 1.12 - 0.63 1.58 - 1.41 - 1.3 1.5 - 1.31 - 0.85 1.46 - 1.3 - 1.05 1.45 - 1.33 - 1.07 1.38 - 1.31 - 1.18 1.32 - 1.29 - 1.2 1.3 - 1.22 - 1.1 1.22 - 1.09 - 0.99 1.17 - 1.17 - 1.17 1.16 - 1.1 - 1.05

0.02 0.05 0.01 0.00 0.00

0.45 0.02 0.47 0.00 0.19

0.93 0.04 0.84 0.00 0.41

0.09 0.00 0.08 0.00 0.04

0.03 1.19 0.01 3.20 0.00

1.64 1.49 1.37 1.39 1.53

14.11 13.61 22.14 15.23 17.45

-

12.73 - 11.27 13.2 - 12.8 20.58 - 18.64 15.23 - 15.23 16.71 - 15.94

1.12 1.11 1.09 1.09 1.09

electricity consumption [PWh]

estimated by NASA database 22 and WDI database 21 (see Supporting Information). PV potential, PEC reduction, and yearly CO2 reduction are estimated using the method described in ref 1, and PEC and CO2 emissions per unit electricity in each country are obtained from the LCA software. As shown in Table 2, most countries having large electricity demands do not have large potentials for reducing PEC and CO2 emissions because those countries have already installed

-

1.48 1.44 1.27 1.39 1.46

-

1.31 1.4 1.15 1.39 1.4

-

1.01 1.07 1.02 1.09 1.04

-

0.89 1.04 0.92 1.09 0.99

efficient and low CO2 intensity power plants, which lowers the potential for reducing PEC and CO2 emissions by PV. Conversely, most countries having a large potential for reducing annual PEC and CO2 emissions by PV have small electricity demands. Although producing electricity using PV could be effective for reducing CO2 emissions in those countries, the impact on the global CO2 emissions will not be large. For example, while the CO2 reduction from installing 1 kW PV is 7419

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Table 3. PEC and CO2 Emissions for Different Type PV Modules in Each Case Study PEC [GJ]

CO2 [t]

case 1 stage stage stage stage stage stage stage BOS

1 2 3 4 5 6 7

total PT (year)

case 4

case 1

case 4

mc-Si

sc-Si

thin-Si

mc-Si

sc-Si

thin-Si

mc-Si

sc-Si

thin-Si

mc-Si

sc-Si

thin-Si

1.13 9.89 0.59 2.85 0.50 4.08 −147.96 3.91

1.10 9.67 7.73 2.81 0.63 5.10 −147.96 3.89

8.46 5.47 −153.77 4.86

0.76 10.07 0.23 2.87 0.51 4.06 −605.95 3.91

0.75 9.84 2.85 2.83 0.64 5.08 −605.96 3.89

8.56 5.40 −622.15 4.86

0.07 0.83 0.05 0.18 0.04 0.28 −7.56 0.28

0.07 0.81 0.65 0.18 0.05 0.34 −7.56 0.28

0.67 0.35 −7.86 0.36

0.03 0.45 0.00 0.15 0.02 0.27 −54.63 0.28

0.03 0.44 0.00 0.14 0.03 0.34 −54.63 0.28

0.45 0.33 −56.09 0.36

−125.00

−117.03

−134.98

−583.55

−580.10

−603.33

−5.84

−5.19

−6.48

−53.43

−53.37

−54.95

3.11

4.19

2.46

0.75

0.86

0.62

4.56

6.28

3.53

0.45

0.47

0.42

thin-Si PV are larger than those of mc-Si and sc-Si PVs in Table 3.

large in Botswana and Mongolia, the electricity demands in those countries are less than 1/1000 of that in US. Furthermore, because the GDP per capita in those countries is small, large-scale installation of PV is difficult economically.21 The countries appearing on Table 2a,b (China, India, Australia, South Africa, and Saudi Arabia) have both large electricity demand and large annual CO2 and PEC reduction potentials. Therefore, the impact of replacing their power plants with PV could be much larger. International electricity transmission lines could bridge the gap between demand and reduction potential. For example, a cross-national project was proposed to produce electricity in Africa and transmit it to Europe.23 However, transmission loss reduces the effectiveness of this approach. Moreover, the CO2 reduction effect will be small in European countries having small CO2 emissions per unit electricity. If low-loss electricity transmission becomes possible, the Himalayan and Gobi regions would be attractive because those regions are close to China and India, which have both large electricity demands and large CO2 emissions per unit electricity. For example, if the electricity generated in Case 5 were transmitted from Nepal to India, the total CO2 reduction would be more than 14 tons for 1 kW PV generating electricity for 20 years. 3.4. Effect of PV Module Type on PEC and CO2 Emissions. Table 3 shows the PEC and CO2 emissions at each life-cycle stage in Case 1 and Case 4 for three types PV modules: mc-Si, sc-Si, and thin-Si PV. Although the amount is rather small, the manufacturing stages with the largest PEC and CO2 emissions are different for the different types of PV modules. Stage 2 is large for mc-Si and sc-Si; Stage 3 is large for sc-Si, and Stage 5 is large for thin-Si. While Stage 6 is large for all types, most of the PEC and CO2 emissions at that stage are from manufacturing other materials. Because such indirect environmental loads is assumed to be constant, changing the location of Stage 6 will probably have a limited effect. CO2 reduction at the usage stage also changes with PV module type. While the efficiency of crystalline Si (c-Si) PV, such as mc-Si and sc-Si, decreases with increasing ambient temperature,24 thin-Si PV is more resistant to temperature increase.10 Therefore, using thin-Si PVs in regions with high temperatures can increase CO2 reduction. As a whole, due to small PEC and CO2 emissions at the manufacturing stages and large PEC and CO2 reductions at the usage stage, reductions in life cycle PEC and CO2 emissions of

4. LIMITATIONS OF THIS STUDY We have not considered the CO2 emissions and PEC resulting from transporting and installing PV, constructing the electricity transmission infrastructure, maintenance of PV, storage, and losses during electricity transmission. Transmission and energy storage are usually not important for small scale introduction of PV, but they could become important for scales required to match global demand and supply of renewable energy. External factors affecting PV potential, such as wind, snowfall, damage to the PV surface, and module degradation, are also not considered. In addition, we have not considered new PVs such as CdTe and CIGS. As these technologies become more affordable, it could be worth conducting the case studies for them. Finally, we do not consider how the PEC and CO2 emissions per unit electricity may vary within each country and over time. These factors should be analyzed separately in the future.

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ASSOCIATED CONTENT

S Supporting Information *

Table 1: the annual supply capacities and PV installation rates of the top five countries at each life-cycle stage together with their primary energy consumption (PEC) and CO2 emission per unit electricity generation; Table 2: specifications of PVs; Table 3: electricity consumed to manufacture 1 kW PV at the manufacturing and disposal stages; Table 4: PEC and CO2 emission from other materials; equations. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel: +81-29-861-8114; fax: +81-29-861-8118; e-mail: [email protected]. Notes

The authors declare no competing financial interest. § Permanent address: Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1, Onozawa, Tsukuba, Ibaraki, 305-8569, Japan. 7420

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(24) Wysocki, J. J.; Rappaport, P. Effect of temperature on photovoltaic solar energy conversion. J. Appl. Phys. 1960, 31 (3), 571−578.

ACKNOWLEDGMENTS We thank Steven Kraines for editorial contributions and helpful comments on this study. This research was supported by grants from the Research Institute of Science for Safety and Sustainability (RISS) in the National Institute of Advanced Industrial Science and Technology (AIST) and also by a Grantin-Aid for Young Scientists (A) (23681008) from the Japan Society for the Promotion of Science (JSPS).

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dx.doi.org/10.1021/es204704y | Environ. Sci. Technol. 2012, 46, 7415−7421