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A Hybrid Method for Provincial Scale Energy-related Carbon Emission Allocation in China Hongtao Bai,†,* Yingxuan Zhang,‡,§ Huizhi Wang,∥ Yanying Huang,† and He Xu†,* †

College of Environmental Science and Engineering, Nankai University, Tianjin 300071, P. R. China Department of Urban Planning & Design, University of Hong Kong, Hong Kong, P. R. China § SRS Consortium for Advanced Study in Cooperative Dynamic Games, Hong Kong Shue Yan University, Hong Kong, P. R. China ∥ Tianjin Academy of Social Sciences, Tianjin 300191, P. R. China ‡

S Supporting Information *

ABSTRACT: Achievement of carbon emission reduction targets proposed by national governments relies on provincial/state allocations. In this study, a hybrid method for provincial energyrelated carbon emissions allocation in China was developed to provide a good balance between production- and consumptionbased approaches. In this method, provincial energy-related carbon emissions are decomposed into direct emissions of local activities other than thermal power generation and indirect emissions as a result of electricity consumption. Based on the carbon reduction efficiency principle, the responsibility for embodied emissions of provincial product transactions is assigned entirely to the production area. The responsibility for carbon generation during the production of thermal power is borne by the electricity consumption area, which ensures that different regions with resource endowments have rational development space. Empirical studies were conducted to examine the hybrid method and three indices, per capita GDP, resource endowment index and the proportion of energy-intensive industries, were screened to preliminarily interpret the differences among China’s regional carbon emissions. Uncertainty analysis and a discussion of this method are also provided herein.

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proaches,12−14 call for scientific carbon emission estimation. Owing to cross-border energy transfer and product consumption, a fixed unified estimation method has yet to be put into use; therefore, it is not yet possible to compare carbon emissions among regions.4 Accordingly, it is necessary to develop a carbon emission estimation method that is suitable for regional allocation to allow experts in the field to conduct differentiated analysis of inter-regional carbon reduction policies. To date, carbon emission estimations have been widely performed while focusing on the debate between efficiency and equity. The IPCC developed a rather detailed carbon emission inventory method based on the principle of producer responsibility.15 Using this method, the Kyoto Protocol founded a national-level emission reduction program.16 This production-based approach allocates all responsibility of carbon emissions to production regions, forcing these regions to rethink their modes of production and promote efficient carbon emission reduction. However, this approach is only suitable for

INTRODUCTION Governments around the world have frequently chosen to reduce anthropogenically produced carbon dioxide emissions (hereafter referred to as carbon emissions). This choice may be a response to global climate change, as well as the combined effects of political, economic, energy and other nonclimatic factors. Many nations including the United States1 and the United Kingdom2 have developed national carbon emission reduction targets (CERT). In late 2009, the Chinese government proposed a reduction of carbon dioxide emissions per 10,000 Yuan of GDP from the 2005 level of 45−40% by 2020.3 The achievement of this national target is dependent on provincial/state, urban and regional allocations and their specific actions. Natural resource conditions, economic growth, technical level and export opportunities may differ among regions, which will necessitate different methods of emission reduction policy guidance.4,5 Provincial/state and urban governments must consider the following issues when restructuring their policies: (a) how to develop differentiated and practical emission reduction targets; and (b) how to achieve their respective targets.6 Many studies have provided insight into regional total carbon emissions allocations.7 These allocation methods, which include indicator-based, 8−11 triptych sectoral and other ap© 2014 American Chemical Society

Received: Revised: Accepted: Published: 2541

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closed systems and onsite emissions,15,17 and it has been argued thatit is the primary impediment to effective international climate policy.18 The most prominent issue associated with this carbon estimation is the embodied carbon emission caused by inter-regional trade. To highlight the principle of equitable development, beneficiaries of inter-regional trade should assume responsibility for the emissions of production processes.19,20 As a result, consumption-based accounting has been proposed and discussed with increasing frequency.18,21 However, attributing embodied carbon emissions responsibilities entirely to final consumers throughout supply chains, which downplays the pollution liability of producers, has been called into question. Not only do consumers benefit from the production, but producers obtain employment, income and producer surplus. In this context, shared responsibility has been proposed as a method to obtain a balance of responsibilities.16,18,22−25 However, no feasible estimation method has been developed to date. Moreover, the research discussed pertains to allocation of responsibility among countries, but no studies of sharing responsibility for regional carbon estimation methods have been conducted to date. Therefore, the present study reconsiders the relationship between efficiency and equity. Owing to its greater contribution, urban-level carbon emissions have attracted increasing attention in recent years.4,26−32 The approach used in these studies is often based on industrial sectors (bottom-up methodology), life-cycle methods (in which the city is considered as land with a certain boundary as well as an energy and material demand center) or input-output models (top-down approach using public data). These studies estimated all carbon emissions related to urban production and consumption activities. This approach is based on consumer responsibility and designed to promote efficient regional carbon emission reduction, and it can assist in the identification of carbon emission reduction pathways in specific cities. However, double counting often occurs owing to uncertainties and randomness in life-cycle boundaries and definitions of finished goods.24 Because of the nonuniformity of estimation methods or poor data availability, it is not possible to carry out an inter-regional comparative analysis. More importantly, the city scopes in some studies only cover urban areas, which makes it difficult to solve the problem of transboundary emissions.4,28 Achievement of CERT proposed by national governments relies on provincial/state allocations, but very few studies have been conducted to estimate provincial-scale carbon emissions, even though calculation of provincial areas simplifies solving transboundary emissions while incorporating national carbon emissions. Generally, national governments have regional coordination and administrative functions, while the responsibility for allocation of carbon emissions among provinces can be more flexible than allocations at the national level. This is because they consider regional equity while attaching more importance to achievement of national CERT. The method proposed in this study is designed to facilitate national CERT achievement. To accomplish this, three issuesare considered: (i) Feasibility: the sum of provincial carbon emissions consistent with national goals. To ensure the national carbon emissions are well decomposed, double counting should be avoided in the proposed method; (ii) Efficiency: enhancement of the efficiency of the overall national emission reduction, and promotion of regional emissions reduction. Our ultimate purpose is not only to estimate the carbon emissions within a

certain province, but to mobilize all positive factors to push both governments and companies to adopt cleaner production processes; and (iii) Equity: carbon emission estimations used are consistent across provinces. Impaired competitiveness between different regions should be avoided and the same development space should be ensured. Accordingly, provincial energy-related carbon emissions are decomposed into direct carbon emissions of local activities other than thermal power generation and indirect emissions of electricity consumption (see section 2). Responsibility for embodied carbon emissions of provincial products transactions attaches entirely to the production area, while the responsibility for indirect carbon emissions of energy consumption such as electricity use attaches to the consumption area. Net export in emerging markets is large, so reduction of carbon emissions by producers is more important and more efficient than that by consumers. From an efficiency point of view, production-based accounting is more appropriate and easier to implement than consumption-based accounting. The production area attracts investment and increased profits, so it should accept responsibility for the corresponding carbon emissions. It is similar to income-based responsibility.20 Provincial governments can promote low-carbon industries by establishing industrial access policies, optimizing industrial structure, and enhancing the level of industrial technology. However, energy sectors are different and the regional distribution of energy depends on the conditions of the region’s natural resources. For example, thermal power plants in China are generally located in the vicinity of the coal base. They are usually close to consumers in the last few decades to avoid the need for long distance power transmission.33 The spatial differentiation of thermal power industries is not easy to change; therefore, it is difficult for provincial governments to play a significant role in emissions reductions by the electric power industry. For these reasons, assigning responsibility for electricity emissions to the production area is not conducive to equitable regional development. Consumer responsibility for electricity emissions contributes to enhanced electricity use efficiency by consumers, which will lead to actual reductions in electricity production. Moreover, carbon emissions by the thermal power industry are large scale and of high concentration. Accordingly, companies should actively and significantly reduce emissions from electricity production through process improvements, such as introducing CCS technologies, which is also conducive to the achievement of national CERTs. Based on the above principles, a hybrid estimation method focusing on the national target achievement was developed. This method is a first attempt to provide a good balance between production- and consumption-based approaches. The developed method was then applied to estimate the provincial energy-related carbon emissions throughout China and compared with the PAP method. The differences in provincial carbon emissions were also preliminarily interpreted in this paper.

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MATERIALS AND METHODS The method most commonly used to estimate carbon emissions associated with regional fossil fuel combustion is the IPCC model.15 In that model, it is assumed that the total regional supply of various types of energy is equal to the industrial final energy consumption plus losses associated with processing, conversion, and transport. The supply may be used 2542

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Figure 1. Fuel-combustion carbon emission and its inter-regional flow. The dots indicate the actual carbon emission positions in the energy consumption process and the dashed lines indicate a lack of carbon emissions during the actual process. The processes employed by the energy industry are commonly included in the industrial energy consumption in some nations, that is, C1 and C2 are included in C4. Using the pragmatic approach of the International Council for Local Environmental Initiatives,29,34 the emissions in Scope I can be defined as in the boundary fuel combustion, CScope I =C1+C2+C3+C4+C′5+C′6+C7+C8; the emissions in Scope II are out of the boundary of electricity emissions at the power plant, CScope II = C′10; and the emissions in Scope III are the production chain emissions, CScope III = Cembodied. Based on equitable regional development and regional emission reduction efficiency, Cembodied is included in the industrial emissions of the production area; therefore, Scopes I + II are appropriate in regional estimation.27,30

Carbon Emissions Related to Final Energy Consumption. Final energy consumption sectors include transport, commerce, households and industry. In the current study, urban carbon emissions by these sectors were estimated separately based on the bottom-up principle (This approach is illustrated in Supporting Information (SI)). The foci of these studies included determination of (1) transboundary emissions of surface transport, aviation and marine sectors, and (2) embodied emissions of the products. Transboundary Emissions. Estimation of transport emissions is mainly based on fuel consumption (characterized by fuel sales) or vehicle travel mileage (VTM).15,29 The actual fuel consumption data for urban vehicles are difficult to obtain separately; therefore, the VTM method is commonly used. However, the uncertainty and availability of VTM data results in, a great level of error, and the separate calculation of transport emissions remains an issue.4 In China’s energy statistical system, fuel consumption by vehicles is included in the transport and household energy consumption. Thus, transport, commerce, household, and industrial sectors are regarded as final energy consumption sectors for overall estimation so that transboundary emissions of the transport sector may be accounted for more accurately.28 In this study, it was assumed that the inter-regional transport flow is balanced. Specifically, the local refueling quantities of outward-region vehicles (vehicles leaving the province) were equal to the outward-region refueling quantities of local vehicles. As a result, local oil sales are regarded as the local energy consumption of the transport sector. Embodied Emissions. Embodied emissions of the products are included in the industrial sectors of the corresponding production areas in this paper. Unlike energy sectors, these industrial sectors should positively reduce emissions and accept relevant responsibilities. It has been determined that most energy sectors are unable to be arbitrarily transferred by means of geography, resources and political factors. Therefore, Cfinal energy consumption for both CPAP and CCAP can be calculated by the IPCC model according to the total final fossil

to conveniently calculate carbon emissions produced by fuel combustion in an enclosed area. However, on the nonclosed regional scale, where cross-border trading is present, this model cannot efficiently process indirect carbon emissions caused by inter-regional flows of energy. Additionally, the shared responsibility for problems associated with carbon emissions that are embodied in inter-regional trade are not addressed by this model under these conditions (Figure 1). Based on the producer accounting principle (PAP), energyrelated carbon emissions in Region I are allocated to processes that actually emit CO2 to the atmosphere:22 C PAP = C1 + C2 + C3 + C4 + C5′ + C6′ + C7 + C8 ≈ (C3 + C4 + C5′ + C6′) + C7 + C8 = Cfinal energy consumption + Celectricity procution + C heat production

According to the consumer accounting principle (CAP), regional energy-related carbon emissions are related to final use of goods and services, even if they are imported from outside regions. This concept is indicated by the arrows from final energy consumption sectors shown in Figure 1. ′ + C11 C PAP = C3 + C4 + C5′ + C6′ + C9 + C10 + Cembodied ′) = (C3 + C4 + C5′ + C6′ + Cembodied) + (C9 + C10 + C11 = Cfinal energy consumption + Celectricity consumption + C heat consumption

CPAP and CCAP can be divided into three components, carbon emissions related to final energy consumption, electricity, and heat. However, direct emissions from final energy consumption sectors, electricity and heat production are likely to differ from the indirect emissions caused by consumption. This is because consumption and production processes of products, electricity and heat are separated in space, which results in the main differences between CPAP and CCAP. 2543

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Figure 2. Electricity generation methods vary widely among the provinces of China. The proportion of thermal power generation in several northern provinces exceeds 90%. However, this proportion is less than 30% in Hubei and Sichuan because of their rich hydropower resources. It should be noted that the proportion of nuclear and wind power in China (listed in SI Table S1) is small; therefore, they were not included in the graph.

Figure 3. Differences among direct carbon emissions of electricity generation and indirect carbon emissions of electricity consumption in different provinces of China (SI Table S2).

energy consumption of transport, commerce, household, and industrial sectors. Electricity Emissions. Emissions from electricity generation account for about one-third of global energy carbon emissions,35 and the proportion of China’s electricity consumption in the final energy consumption is also increasing.36,37 Thermal power generation has been the most important source of China’s electricity generation, but the

proportions of thermal power differ among regions (Figure 2). From a life-cycle perspective, raw materials and energy are also consumed during the production of equipment for the generation of hydro, nuclear and wind power, which results in the emission of greenhouse gases. It is believed that carbon emissions associated with the production of equipment should be included in the production industry; however, it is important to ensure that they are not double counted during evaluation of 2544

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can be calculated similar to electricity emissions. Indirect carbon emissions of local heat consumption may be calculated directly from the total consumption of various fossil fuels in local heat production, that is, Cheat consumption≈Cheat production. Therefore, the carbon emissions from heat and final energy consumption sectors can be merged into the direct carbon emissions of local activities other than thermal power generation (Cdirect) in our method. Modeling. Based on the above analyses, provincial energyrelated carbon emissions are decomposed into two types, direct emissions of local activities other than thermal power generation (Cdirect), and indirect carbon emissions of electricity consumption (Celectricity). A hybrid allocation method of provincial energy-related carbon estimation is proposed as follows:

the electricity generation for the purpose of regional allocation. Accordingly, it is assumed that the carbon emission coefficients of hydro, nuclear and wind power in the electricity generation process are approximately equal to zero, whereas carbon emissions of electricity generation are approximately equivalent to those of thermal power generation. Thus, direct carbon emissions of regional electricity generation (Celectricity production) may be calculated according to the energy consumption during thermal power generation. Estimation of indirect carbon emissions of regional electricity consumption (Celectricity consumption) is relatively complex because it includes two components, C9 and C′10, which are a portion of the direct emissions resulting from local electricity generation and the generation of outward dispatched electricity, respectively. For countries that do not possess a complete unified power grid, direct carbon emissions are higher in regions with larger proportions of thermal power generation, while electricity consumption processes occur in other regions. As shown in Figure 1, locally generated electricity is not necessarily consumed in the same region, and it is not possible to distinguish electricity consumed in regions that use higheremission thermal or lower-emission hydro, nuclear or wind power. Therefore, under the existing technical level and statistical system, it is often not possible to accurately obtain the actual indirect carbon emissions of electricity consumption in certain regions. If Celectricity production is used to directly replace Celectricity consumption, regional development space will be unequal. Figure 3 shows the differences between the carbon emissions from electricity generation and those from electricity consumption for the provinces of China. Consumption behavior is the dominant factor affecting electricity emissions. Shifting producer responsibility to consumer responsibility enhances the efficiency of embodied carbon emission reductions to promote the low-carbon development of the entire society.26 In a country in which the grid is completely unified, calculation of Celectricity consumption is convenient. However, for countries in which unification of the grid has not been completed, the electricity carbon emission factors differ greatly because of the different electricity generation methods used among regions.4,35,38 Indirect emissions of regional electricity consumption are often calculated according to the regional power consumption and respective emission factor of the grid. Nevertheless, there is also electricity deployment among grids, and the amount of deployment is believed to be greater in the future.33 This method also hides the transfer of responsibility. At the country level, the use value of power is the same for all consumers. Since consumer behaviors are our concern, the difference in power type from one province to another should not be stressed, even though there are differences in emission intensity. Therefore, regardless of whether the state grid is completely unified or not, indirect emission factors of electricity consumption in our method are calculated using the national carbon emissions of thermal power generation and electricity consumption, as well as the regional indirect emissions. The higher carbon emissions of the thermal power industry and resultant local air pollution problems may be assessed more effectively and reasonably from the industrial view than from the regional level. Heat Emissions. Carbon emissions from local heat production are relatively small in China (see SI Table S3). Furthermore, regional heat production is often supplied to local consumers in China; however, for regions in which it is not, it

C hybrid = Cdirect + Celectricity Cdirect =

∑ [(Q final consumptioni + Q heati + Q lossi) × βi × αi i

− Bi × βi × αi × ηi] × γi Celectricity = (E + ε) × σ

σ = TC /TE TC =

∑ TQ i × βi × αi × γi i

where Chybrid is the total regional carbon emissions (t); Celectricity is the indirect carbon emissions of local electricity consumption (t); Cdirect is the direct carbon emissions of local activities other than thermal power generation (t); Qfinal consumption i is the final consumption of the i-th fossil fuel in local final energy consumption sectors (tce); Qheat i is the consumption of the i-th fossil fuel used for local heating (tce); Qloss i is the loss of the ith fossil fuel (tce); βi is the energy conversion factor of the i-th fossil fuel (TJ/tce); αi is the potential carbon emission factor of the i-th fossil fuel (t C/TJ); Bi is the material consumption of the i-th fossil fuel used as raw material (tce); ηi is the carbon sequestration rate with the i-th fossil fuel used as raw material; γi is the carbon oxidation factor15 of the i-th fossil fuel in the combustion process; E is the regional final electricity consumption (kwh); ε is the regional electricity loss, which can be obtained from the China Energy Statistical Yearbook (kwh); σ is the average equivalent emission factor of national electricity consumption (t C/kwh); TC is the total carbon emission of national thermal power generation (t C); TE is the national total electricity generation (kwh); and TQi is the consumption of the i-th fossil fuel in the national thermal power generation (t C). There are two instructions for this method. (1) Electricity generation mainly consists of thermal, hydro, wind and nuclear power. Among these, thermal power generation relies on the combustion of massive amounts of fossil fuels for the generation of electricity, while hydro, power and wind power rely on water potential and nuclear, wind and other clean energies that have zero carbon emission during the electricity generation process. From the life-cycle perspective, hydro, nuclear and wind power also consume energy during the production of electricity generation equipment. Accordingly, the carbon emissions presented during this process are included in the industrial sector of the equipment production area in this method. Thus, it is assumed that the carbon emission 2545

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Figure 4. Estimated provincial carbon emissions based on the proposed hybrid method and IPCC method. The left group is northern provinces and the right is southern provinces.

Figure 5. Carbon productivity (defined as the amount of GDP per unit of carbon emitted42) shows a general increasing trend with the increase in per capita GDP in China. Carbon intensity, the inverse of carbon productivity, was also found to decline with economic level.

based on the hybrid carbon emission estimation method featuring shared responsibility and regional allocation. Detailed data are shown in SI Table S3. When compared with the production-based method recommended by the IPCC, the hybrid method provides some rational modifications of the provincial carbon emissions in China (Figure 4). The northern provinces are often positioned as energy bases with high fossil fuel production and direct carbon emission; accordingly, net exports in these provinces are inevitably large. Conversely, the IPCC method underestimates the carbon emission responsibility in the southern provinces because of the extensive indirect carbon emission embodied in the consumption of traded goods. As a result, some carbon emissions embodied in cross-boundary energy trade are shifted into areas with net carbon import in this method. The rate of data modification in the provinces ranged from 0.41% to 38.1%.

coefficient in the electricity generation process of hydro, nuclear and wind power is zero,while the carbon emissions associated with electricity generation are approximately equivalent to those of thermal power. (2) Focusing on the low-carbonization of the electricity consumption behavior, this method assumes the homogenization of local electricity consumption in all provinces of China. The indirect carbon emission of local electricity consumption Celectricity is calculated with regional final electricity consumption E, regional electricity loss ε and average equivalent emission factor of national electricity consumption σ. Although this assumption will result in some errors, the electricity consumption behavior is highlighted. This method is greatly simplified and can also ensure that the sum of provincial carbon emissions is consistent with the directly calculated national emissions. Empirical Studies. The provincial carbon emissions associated with energy consumption in China were calculated 2546

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Figure 6. Carbon productivity decreases logarithmically as the resources endowment index increases in different provinces. Most regions possessing abundant amounts of resources prioritize the development of the energy industry, and the proportion of carbon-emission-intensive industries is relatively high, increasing the carbon intensity of the entire region.

Figure 7. Development of energy-intensive industries plays a positive role in the carbon emissions of most provinces. The current industrial structures of different provinces in China have a high similarity (the proportion of the industry in provinces is concentrated in 40−55%, and that of the tertiary industry is concentrated in 30−40%, SI Table S4); thus, the proportion of energy-intensive industries in the industrial sectors may characterize the differences in provincial carbon emissions more effectively. Note: Hainan, Xinjiang, and Heilongjiang data were excluded from this regression based on data quality assessment.

variables (per capita GDP, resource endowment index and the proportion of energy-intensive industries in the industrial sectors) into the model enabled more accurate interpretation of the differences in regional carbon emissions (Figures 5, 6, and 7). Model equations were developed with statistical fits and relationships were checked for statistical significance (listed in SI Tables S6−S9). We also verified that the trade-offs were robust by fitting the IPCC values into the model equations (SI Figure S2). It should be noted that these figures are only meant to reflect the approximate relationship between provincial

As shown in Figure 4 and SI Figure S3, the carbon emissions in China differ greatly by location. China’s CERT is based on carbon emission intensity, and this study explored the root causes for the provincial differences of this index. Previous studies have shown that the difference in carbon intensity is produced by four factors: economic development, resource endowment, energy structure and industrial technical level.39−41 Ten index variables were determined to characterize these four factors, and correlation regression analysis and the stepwise regression model were used for screening (SI Tables S4 and S5). The results showed that substitution of three index 2547

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Figure 8. Comparison of the total carbon emissions in China calculated using various carbon accounting rules.

emissions of cross-border flow energy. Furthermore, a hybrid method of provincial carbon emission estimation is evolved. This method is based on the principles of feasibility, efficiency, and equity, in which the embodied emissions of products are included in the industrial sectors of the production area. When considering the scale and specialty of electricity generation and consumption, the responsibility for carbon emissions during the production of thermal power is borne by the electricity consumption area. This ensures that different regions with resource endowments have the same development space. Additionally, this induces national regions to emphasize the indirect carbon emissions associated with electricity consumption, which is conducive to achievement of the national emission reduction target. The high carbon emissions of the thermal power industry should be governed from an industrial perspective rather than a regional one, and the thermal power industry should actively engage in reduction of technical emissions. Empirical studies were conducted and the spatial distribution of carbon emissions in China was analyzed based on the hybrid method developed in this study. Using the regression analysis method, three indices, per capita GDP, the resource endowment index and the proportion of energy-intensive industries, were screened to preliminarily interpret differences among China’s regional carbon emissions. The carbon intensities of different regions were shown to decline with economic level. The carbon productivity of resource-rich provinces is usually disappointing, and energy-intensive industries exert a larger positive contribution to carbon emissions. We also verified that these trade-offs were robust by fitting the IPCC values. Finally, uncertainty analysis of the method indicated that its estimations were accurate and credible. Owing to a lack of provincial consumption-based carbon data in China, only productionbased approaches were compared with the hybrid method. Overall, our study is a first attempt at a hybrid carbon estimation method that could evolve once measurement of regional emissions has started and improved technology has begun to be implemented. Future studies should be conducted to determine how to reduce uncertainties and ensure that the method is suitable for decision-makers.

carbon emissions and the three indices. More detailed cause− effect relationships will be investigated in the future. Uncertainty Analysis. Models are simplified representations of real-world systems and typically do not mimic actual conditions exactly.15 The major sources of uncertainties in our method are outlined below. Conceptualization Uncertainties. This method was developed based on several assumptions: (i) The inter-regional transport flow is balanced; (ii) carbon emission coefficients of hydro, nuclear and wind power electricity generation are approximately zero; (iii) regional heat production is supplied to local consumers. Uncertainties in Emission Factors. Default data regarding carbon emission factors from the IPCC were used directly in our method. As discussed by the IPCC, there were many differences concerning regional environment, technology levels, and production status.15,43 Using the default data without correction will lead to uncertainties in the method. Uncertainties Associated with Activity Data. Provincial data from officially published statistical yearbooks are used in our method. It is known that there are uncertainties and errors associated with the official calculations used in the yearbooks, and national statistics are often not entirely consistent with regional statistics.43 Using provincial statistics and adding these carbon emissions measured by both the hybrid method and IPCC method revealed that calculated values in China are slightly (10.7−17.9%) higher than those published by international agencies such as the WRI, CDIAC, and EIA (Figure 8). In addition, the total emissions in China calculated by the IPCC method are also slightly higher than those calculated by the hybrid method. This may have resulted from a loss of power transmission, which is not entirely included in the regional statistics.

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DISCUSSION In this study, shared responsibility is discussed and applied to provincial-scale carbon emissions estimation. To facilitate achievement of the national CERT, provincial carbon emissions are decomposed into direct emissions of local activities other than thermal power generation and indirect emissions of electricity consumption through analysis of the carbon 2548

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ASSOCIATED CONTENT

S Supporting Information *

First of all, the composition of electricity production in China is listed in Table S1. Then, direct and indirect carbon emissions associated with electricity in different provinces of China are listed in Table S2. The provincial carbon emission and potential variables data in China are listed in Tables S3 and S4. Spatial differentiation of carbon emissions in China are illustrated in Figure S1.Moreover, the correlation between provincial carbon emission intensity and potential variables analyzed by the Pearson Correlation Coefficient is shown in Tables S5 and S6. Statistical testing of models shown in Figures 5−7 is described in Tables S7−S9. The trade-offs estimated for the IPCC method is illustrated in Figure S2. Finally, the bottom-up approach is illustrated. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone/fax: 86-22-23508348; e-mail: [email protected]; [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research is supported by the National Natural Science Foundation of China (41301648), the Fundamental Research Funds for the Central Universities (65012501) and the National Social Science Foundation of China (11AZD103). The authors thank three anonymous referees for their extremely valuable comments and suggestions.

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