A Hybrid Method for Provincial Scale Energy-related CarbonEmission Allocation in ChinaHongtao 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 targetsproposed by national governments relies on provincial/stateallocations. In this study, a hybrid method for provincial energy-related carbon emissions allocation in China was developed toprovide a good balance between production- and consumption-based approaches. In this method, provincial energy-relatedcarbon emissions are decomposed into direct emissions of localactivities other than thermal power generation and indirectemissions as a result of electricity consumption. Based on thecarbon reduction efficiency principle, the responsibility forembodied emissions of provincial product transactions isassigned entirely to the production area. The responsibility forcarbon generation during the production of thermal power isborne by the electricity consumption area, which ensures that different regions with resource endowments have rationaldevelopment space. Empirical studies were conducted to examine the hybrid method and three indices, per capita GDP, resourceendowment index and the proportion of energy-intensive industries, were screened to preliminarily interpret the differencesamong China’s regional carbon emissions. Uncertainty analysis and a discussion of this method are also provided herein.

■ INTRODUCTION

Governments around the world have frequently chosen toreduce anthropogenically produced carbon dioxide emissions(hereafter referred to as carbon emissions). This choice may bea response to global climate change, as well as the combinedeffects of political, economic, energy and other nonclimaticfactors. Many nations including the United States1 and theUnited Kingdom2 have developed national carbon emissionreduction targets (CERT). In late 2009, the Chinese govern-ment proposed a reduction of carbon dioxide emissions per10,000 Yuan of GDP from the 2005 level of 45−40% by 2020.3

The achievement of this national target is dependent onprovincial/state, urban and regional allocations and theirspecific actions. Natural resource conditions, economic growth,technical level and export opportunities may differ amongregions, which will necessitate different methods of emissionreduction policy guidance.4,5 Provincial/state and urbangovernments must consider the following issues whenrestructuring their policies: (a) how to develop differentiatedand practical emission reduction targets; and (b) how toachieve their respective targets.6

Many studies have provided insight into regional total carbonemissions allocations.7 These allocation methods, which includeindicator-based,8−11 triptych sectoral and other ap-

proaches,12−14 call for scientific carbon emission estimation.Owing to cross-border energy transfer and product con-sumption, a fixed unified estimation method has yet to be putinto use; therefore, it is not yet possible to compare carbonemissions among regions.4 Accordingly, it is necessary todevelop a carbon emission estimation method that is suitablefor regional allocation to allow experts in the field to conductdifferentiated analysis of inter-regional carbon reductionpolicies.To date, carbon emission estimations have been widely

performed while focusing on the debate between efficiency andequity. The IPCC developed a rather detailed carbon emissioninventory method based on the principle of producerresponsibility.15 Using this method, the Kyoto Protocolfounded a national-level emission reduction program.16 Thisproduction-based approach allocates all responsibility of carbonemissions to production regions, forcing these regions torethink their modes of production and promote efficient carbonemission reduction. However, this approach is only suitable for

Received: October 11, 2013Revised: January 29, 2014Accepted: January 31, 2014Published: January 31, 2014

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closed systems and onsite emissions,15,17 and it has been arguedthatit is the primary impediment to effective internationalclimate policy.18 The most prominent issue associated with thiscarbon estimation is the embodied carbon emission caused byinter-regional trade. To highlight the principle of equitabledevelopment, beneficiaries of inter-regional trade shouldassume responsibility for the emissions of productionprocesses.19,20 As a result, consumption-based accounting hasbeen proposed and discussed with increasing frequency.18,21

However, attributing embodied carbon emissions responsibil-ities entirely to final consumers throughout supply chains,which downplays the pollution liability of producers, has beencalled into question. Not only do consumers benefit from theproduction, but producers obtain employment, income andproducer surplus. In this context, shared responsibility has beenproposed as a method to obtain a balance of responsibil-ities.16,18,22−25 However, no feasible estimation method hasbeen developed to date. Moreover, the research discussedpertains to allocation of responsibility among countries, but nostudies of sharing responsibility for regional carbon estimationmethods have been conducted to date. Therefore, the presentstudy reconsiders the relationship between efficiency andequity.Owing to its greater contribution, urban-level carbon

emissions have attracted increasing attention in recentyears.4,26−32 The approach used in these studies is oftenbased on industrial sectors (bottom-up methodology), life-cyclemethods (in which the city is considered as land with a certainboundary as well as an energy and material demand center) orinput-output models (top-down approach using public data).These studies estimated all carbon emissions related to urbanproduction and consumption activities. This approach is basedon consumer responsibility and designed to promote efficientregional carbon emission reduction, and it can assist in theidentification of carbon emission reduction pathways in specificcities. However, double counting often occurs owing touncertainties and randomness in life-cycle boundaries anddefinitions of finished goods.24 Because of the nonuniformity ofestimation methods or poor data availability, it is not possibleto carry out an inter-regional comparative analysis. Moreimportantly, the city scopes in some studies only cover urbanareas, which makes it difficult to solve the problem oftransboundary emissions.4,28 Achievement of CERT proposedby national governments relies on provincial/state allocations,but very few studies have been conducted to estimateprovincial-scale carbon emissions, even though calculation ofprovincial areas simplifies solving transboundary emissionswhile incorporating national carbon emissions.Generally, national governments have regional coordination

and administrative functions, while the responsibility forallocation of carbon emissions among provinces can be moreflexible than allocations at the national level. This is becausethey consider regional equity while attaching more importanceto achievement of national CERT. The method proposed inthis study is designed to facilitate national CERT achievement.To accomplish this, three issuesare considered: (i) Feasibility:the sum of provincial carbon emissions consistent with nationalgoals. To ensure the national carbon emissions are welldecomposed, double counting should be avoided in theproposed method; (ii) Efficiency: enhancement of theefficiency of the overall national emission reduction, andpromotion of regional emissions reduction. Our ultimatepurpose is not only to estimate the carbon emissions within a

certain province, but to mobilize all positive factors to pushboth governments and companies to adopt cleaner productionprocesses; and (iii) Equity: carbon emission estimations usedare consistent across provinces. Impaired competitivenessbetween different regions should be avoided and the samedevelopment space should be ensured.Accordingly, provincial energy-related carbon emissions are

decomposed into direct carbon emissions of local activitiesother than thermal power generation and indirect emissions ofelectricity consumption (see section 2). Responsibility forembodied carbon emissions of provincial products transactionsattaches entirely to the production area, while the responsibilityfor indirect carbon emissions of energy consumption such aselectricity use attaches to the consumption area.Net export in emerging markets is large, so reduction of

carbon emissions by producers is more important and moreefficient than that by consumers. From an efficiency point ofview, production-based accounting is more appropriate andeasier to implement than consumption-based accounting. Theproduction area attracts investment and increased profits, so itshould accept responsibility for the corresponding carbonemissions. It is similar to income-based responsibility.20

Provincial governments can promote low-carbon industries byestablishing industrial access policies, optimizing industrialstructure, 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’snatural resources. For example, thermal power plants in Chinaare generally located in the vicinity of the coal base. They areusually close to consumers in the last few decades to avoid theneed for long distance power transmission.33 The spatialdifferentiation of thermal power industries is not easy tochange; therefore, it is difficult for provincial governments toplay a significant role in emissions reductions by the electricpower industry. For these reasons, assigning responsibility forelectricity emissions to the production area is not conducive toequitable regional development. Consumer responsibility forelectricity emissions contributes to enhanced electricity useefficiency by consumers, which will lead to actual reductions inelectricity production. Moreover, carbon emissions by thethermal power industry are large scale and of highconcentration. Accordingly, companies should actively andsignificantly reduce emissions from electricity productionthrough process improvements, such as introducing CCStechnologies, which is also conducive to the achievement ofnational 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 balancebetween production- and consumption-based approaches. Thedeveloped method was then applied to estimate the provincialenergy-related carbon emissions throughout China andcompared with the PAP method. The differences in provincialcarbon emissions were also preliminarily interpreted in thispaper.

■ MATERIALS AND METHODSThe method most commonly used to estimate carbonemissions associated with regional fossil fuel combustion isthe IPCC model.15 In that model, it is assumed that the totalregional supply of various types of energy is equal to theindustrial final energy consumption plus losses associated withprocessing, conversion, and transport. The supply may be used

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to conveniently calculate carbon emissions produced by fuelcombustion in an enclosed area. However, on the nonclosedregional scale, where cross-border trading is present, this modelcannot efficiently process indirect carbon emissions caused byinter-regional flows of energy. Additionally, the sharedresponsibility for problems associated with carbon emissionsthat are embodied in inter-regional trade are not addressed bythis model under these conditions (Figure 1).Based on the producer accounting principle (PAP), energy-

related carbon emissions in Region I are allocated to processesthat actually emit CO2 to the atmosphere:22

= + + + + ′ + ′ + +≈ + + ′ + ′ + +

= + +

C C C C C C C C CC C C C C C

C C C

( )PAP 1 2 3 4 5 6 7 8

3 4 5 6 7 8

final energy consumption electricity procution heat production

According to the consumer accounting principle (CAP),regional energy-related carbon emissions are related to final useof goods and services, even if they are imported from outsideregions. This concept is indicated by the arrows from finalenergy consumption sectors shown in Figure 1.

= + + ′ + ′ + + ′ ++

= + + ′ + ′ + + + ′+

= ++

C C C C C C C CC

C C C C C C CC

C CC

( ) ( )

PAP 3 4 5 6 9 10 11

embodied

3 4 5 6 embodied 9 10

11

final energy consumption electricity consumption

heat consumption

CPAP and CCAP can be divided into three components, carbonemissions related to final energy consumption, electricity, andheat. However, direct emissions from final energy consumptionsectors, electricity and heat production are likely to differ fromthe indirect emissions caused by consumption. This is becauseconsumption and production processes of products, electricityand heat are separated in space, which results in the maindifferences between CPAP and CCAP.

Carbon Emissions Related to Final Energy Consump-tion. Final energy consumption sectors include transport,commerce, households and industry. In the current study,urban carbon emissions by these sectors were estimatedseparately based on the bottom-up principle (This approachis illustrated in Supporting Information (SI)). The foci of thesestudies included determination of (1) transboundary emissionsof surface transport, aviation and marine sectors, and (2)embodied emissions of the products.

Transboundary Emissions. Estimation of transport emis-sions is mainly based on fuel consumption (characterized byfuel sales) or vehicle travel mileage (VTM).15,29 The actual fuelconsumption data for urban vehicles are difficult to obtainseparately; therefore, the VTM method is commonly used.However, the uncertainty and availability of VTM data resultsin, a great level of error, and the separate calculation oftransport emissions remains an issue.4 In China’s energystatistical system, fuel consumption by vehicles is included inthe transport and household energy consumption. Thus,transport, commerce, household, and industrial sectors areregarded as final energy consumption sectors for overallestimation so that transboundary emissions of the transportsector may be accounted for more accurately.28 In this study, itwas assumed that the inter-regional transport flow is balanced.Specifically, the local refueling quantities of outward-regionvehicles (vehicles leaving the province) were equal to theoutward-region refueling quantities of local vehicles. As a result,local oil sales are regarded as the local energy consumption ofthe transport sector.

Embodied Emissions. Embodied emissions of the productsare included in the industrial sectors of the correspondingproduction areas in this paper. Unlike energy sectors, theseindustrial sectors should positively reduce emissions and acceptrelevant responsibilities. It has been determined that mostenergy sectors are unable to be arbitrarily transferred by meansof 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

Figure 1. Fuel-combustion carbon emission and its inter-regional flow. The dots indicate the actual carbon emission positions in the energyconsumption process and the dashed lines indicate a lack of carbon emissions during the actual process. The processes employed by the energyindustry are commonly included in the industrial energy consumption in some nations, that is, C1 and C2 are included in C4. Using the pragmaticapproach of the International Council for Local Environmental Initiatives,29,34 the emissions in Scope I can be defined as in the boundary fuelcombustion, 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 andregional emission reduction efficiency, Cembodied is included in the industrial emissions of the production area; therefore, Scopes I + II are appropriatein regional estimation.27,30

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energy consumption of transport, commerce, household, andindustrial sectors.Electricity Emissions. Emissions from electricity gener-

ation account for about one-third of global energy carbonemissions,35 and the proportion of China’s electricityconsumption in the final energy consumption is alsoincreasing.36,37 Thermal power generation has been the mostimportant 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 alsoconsumed during the production of equipment for thegeneration of hydro, nuclear and wind power, which resultsin the emission of greenhouse gases. It is believed that carbonemissions associated with the production of equipment shouldbe included in the production industry; however, it is importantto ensure that they are not double counted during evaluation of

Figure 2. Electricity generation methods vary widely among the provinces of China. The proportion of thermal power generation in several northernprovinces exceeds 90%. However, this proportion is less than 30% in Hubei and Sichuan because of their rich hydropower resources. It should benoted 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 differentprovinces of China (SI Table S2).

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the electricity generation for the purpose of regional allocation.Accordingly, it is assumed that the carbon emission coefficientsof hydro, nuclear and wind power in the electricity generationprocess are approximately equal to zero, whereas carbonemissions of electricity generation are approximately equivalentto those of thermal power generation. Thus, direct carbonemissions of regional electricity generation (Celectricity production)may be calculated according to the energy consumption duringthermal power generation.Estimation of indirect carbon emissions of regional electricity

consumption (Celectricity consumption) is relatively complex becauseit includes two components, C9 and C′10, which are a portion ofthe direct emissions resulting from local electricity generationand the generation of outward dispatched electricity,respectively. For countries that do not possess a completeunified power grid, direct carbon emissions are higher inregions with larger proportions of thermal power generation,while electricity consumption processes occur in other regions.As shown in Figure 1, locally generated electricity is notnecessarily consumed in the same region, and it is not possibleto distinguish electricity consumed in regions that use higher-emission thermal or lower-emission hydro, nuclear or windpower. Therefore, under the existing technical level andstatistical system, it is often not possible to accurately obtainthe actual indirect carbon emissions of electricity consumptionin certain regions. If Celectricity production is used to directly replaceCelectricity consumption, regional development space will be unequal.Figure 3 shows the differences between the carbon emissionsfrom electricity generation and those from electricityconsumption for the provinces of China.Consumption behavior is the dominant factor affecting

electricity emissions. Shifting producer responsibility toconsumer responsibility enhances the efficiency of embodiedcarbon emission reductions to promote the low-carbondevelopment of the entire society.26 In a country in whichthe grid is completely unified, calculation of Celectricity consumptionis convenient. However, for countries in which unification ofthe grid has not been completed, the electricity carbon emissionfactors differ greatly because of the different electricitygeneration methods used among regions.4,35,38 Indirectemissions of regional electricity consumption are oftencalculated according to the regional power consumption andrespective emission factor of the grid. Nevertheless, there is alsoelectricity deployment among grids, and the amount ofdeployment is believed to be greater in the future.33 Thismethod also hides the transfer of responsibility. At the countrylevel, the use value of power is the same for all consumers.Since consumer behaviors are our concern, the difference inpower type from one province to another should not bestressed, even though there are differences in emissionintensity. Therefore, regardless of whether the state grid iscompletely unified or not, indirect emission factors of electricityconsumption in our method are calculated using the nationalcarbon emissions of thermal power generation and electricityconsumption, as well as the regional indirect emissions. Thehigher carbon emissions of the thermal power industry andresultant local air pollution problems may be assessed moreeffectively and reasonably from the industrial view than fromthe 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 localconsumers in China; however, for regions in which it is not, it

can be calculated similar to electricity emissions. Indirectcarbon emissions of local heat consumption may be calculateddirectly from the total consumption of various fossil fuels inlocal heat production, that is, Cheat consumption≈Cheat production.Therefore, the carbon emissions from heat and final energyconsumption sectors can be merged into the direct carbonemissions of local activities other than thermal powergeneration (Cdirect) in our method.

Modeling. Based on the above analyses, provincial energy-related carbon emissions are decomposed into two types, directemissions of local activities other than thermal powergeneration (Cdirect), and indirect carbon emissions of electricityconsumption (Celectricity). A hybrid allocation method ofprovincial energy-related carbon estimation is proposed asfollows:

= +C C Chybrid direct electricity

∑ β α

β α η γ

= + + × ×

− × × × ×

C Q Q Q

B

[( )

]

ii i i i i

i i i i i

direct final consumption heat loss

ε σ= + ×C E( )electricity

σ = TC TE/

∑ β α γ= × × ×TC TQi

i i i i

where Chybrid is the total regional carbon emissions (t); Celectricityis the indirect carbon emissions of local electricity consumption(t); Cdirect is the direct carbon emissions of local activities otherthan thermal power generation (t); Qfinal consumption i is the finalconsumption of the i-th fossil fuel in local final energyconsumption sectors (tce); Qheat i is the consumption of the i-thfossil fuel used for local heating (tce); Qloss i is the loss of the i-th fossil fuel (tce); βi is the energy conversion factor of the i-thfossil fuel (TJ/tce); αi is the potential carbon emission factor ofthe i-th fossil fuel (t C/TJ); Bi is the material consumption ofthe i-th fossil fuel used as raw material (tce); ηi is the carbonsequestration rate with the i-th fossil fuel used as raw material;γi is the carbon oxidation factor15 of the i-th fossil fuel in thecombustion process; E is the regional final electricityconsumption (kwh); ε is the regional electricity loss, whichcan be obtained from the China Energy Statistical Yearbook(kwh); σ is the average equivalent emission factor of nationalelectricity consumption (t C/kwh); TC is the total carbonemission of national thermal power generation (t C); TE is thenational total electricity generation (kwh); and TQi is theconsumption of the i-th fossil fuel in the national thermalpower generation (t C).There are two instructions for this method. (1) Electricity

generation mainly consists of thermal, hydro, wind and nuclearpower. Among these, thermal power generation relies on thecombustion of massive amounts of fossil fuels for thegeneration of electricity, while hydro, power and wind powerrely on water potential and nuclear, wind and other cleanenergies that have zero carbon emission during the electricitygeneration process. From the life-cycle perspective, hydro,nuclear and wind power also consume energy during theproduction of electricity generation equipment. Accordingly,the carbon emissions presented during this process are includedin the industrial sector of the equipment production area in thismethod. Thus, it is assumed that the carbon emission

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coefficient in the electricity generation process of hydro,nuclear and wind power is zero,while the carbon emissionsassociated with electricity generation are approximatelyequivalent to those of thermal power. (2) Focusing on thelow-carbonization of the electricity consumption behavior, thismethod assumes the homogenization of local electricityconsumption in all provinces of China. The indirect carbonemission of local electricity consumption Celectricity is calculatedwith regional final electricity consumption E, regional electricityloss ε and average equivalent emission factor of nationalelectricity consumption σ. Although this assumption will resultin some errors, the electricity consumption behavior ishighlighted. This method is greatly simplified and can alsoensure that the sum of provincial carbon emissions is consistentwith the directly calculated national emissions.Empirical Studies. The provincial carbon emissions

associated with energy consumption in China were calculated

based on the hybrid carbon emission estimation methodfeaturing shared responsibility and regional allocation. Detaileddata are shown in SI Table S3.When compared with the production-based method

recommended by the IPCC, the hybrid method providessome rational modifications of the provincial carbon emissionsin China (Figure 4). The northern provinces are oftenpositioned as energy bases with high fossil fuel productionand direct carbon emission; accordingly, net exports in theseprovinces are inevitably large. Conversely, the IPCC methodunderestimates the carbon emission responsibility in thesouthern provinces because of the extensive indirect carbonemission embodied in the consumption of traded goods. As aresult, some carbon emissions embodied in cross-boundaryenergy trade are shifted into areas with net carbon import inthis method. The rate of data modification in the provincesranged from 0.41% to 38.1%.

Figure 4. Estimated provincial carbon emissions based on the proposed hybrid method and IPCC method. The left group is northern provinces andthe 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 inper capita GDP in China. Carbon intensity, the inverse of carbon productivity, was also found to decline with economic level.

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As shown in Figure 4 and SI Figure S3, the carbon emissionsin China differ greatly by location. China’s CERT is based oncarbon emission intensity, and this study explored the rootcauses for the provincial differences of this index. Previousstudies have shown that the difference in carbon intensity isproduced by four factors: economic development, resourceendowment, energy structure and industrial technicallevel.39−41 Ten index variables were determined to characterizethese four factors, and correlation regression analysis and thestepwise regression model were used for screening (SI TablesS4 and S5). The results showed that substitution of three index

variables (per capita GDP, resource endowment index and theproportion of energy-intensive industries in the industrialsectors) into the model enabled more accurate interpretation ofthe differences in regional carbon emissions (Figures 5, 6, and7). Model equations were developed with statistical fits andrelationships were checked for statistical significance (listed inSI Tables S6−S9). We also verified that the trade-offs wererobust by fitting the IPCC values into the model equations (SIFigure S2). It should be noted that these figures are only meantto reflect the approximate relationship between provincial

Figure 6. Carbon productivity decreases logarithmically as the resources endowment index increases in different provinces. Most regions possessingabundant amounts of resources prioritize the development of the energy industry, and the proportion of carbon-emission-intensive industries isrelatively 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 industrialstructures of different provinces in China have a high similarity (the proportion of the industry in provinces is concentrated in 40−55%, and that ofthe tertiary industry is concentrated in 30−40%, SI Table S4); thus, the proportion of energy-intensive industries in the industrial sectors maycharacterize the differences in provincial carbon emissions more effectively. Note: Hainan, Xinjiang, and Heilongjiang data were excluded from thisregression based on data quality assessment.

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carbon emissions and the three indices. More detailed cause−effect relationships will be investigated in the future.Uncertainty Analysis. Models are simplified representa-

tions of real-world systems and typically do not mimic actualconditions exactly.15 The major sources of uncertainties in ourmethod are outlined below.Conceptualization Uncertainties. This method was devel-

oped based on several assumptions: (i) The inter-regionaltransport flow is balanced; (ii) carbon emission coefficients ofhydro, nuclear and wind power electricity generation areapproximately zero; (iii) regional heat production is supplied tolocal consumers.Uncertainties in Emission Factors. Default data regarding

carbon emission factors from the IPCC were used directly inour method. As discussed by the IPCC, there were manydifferences concerning regional environment, technology levels,and production status.15,43 Using the default data withoutcorrection will lead to uncertainties in the method.Uncertainties Associated with Activity Data. Provincial

data from officially published statistical yearbooks are used inour method. It is known that there are uncertainties and errorsassociated with the official calculations used in the yearbooks,and national statistics are often not entirely consistent withregional statistics.43 Using provincial statistics and adding thesecarbon emissions measured by both the hybrid method andIPCC method revealed that calculated values in China areslightly (10.7−17.9%) higher than those published by interna-tional agencies such as the WRI, CDIAC, and EIA (Figure 8).In addition, the total emissions in China calculated by theIPCC method are also slightly higher than those calculated bythe hybrid method. This may have resulted from a loss ofpower transmission, which is not entirely included in theregional statistics.

■ DISCUSSION

In this study, shared responsibility is discussed and applied toprovincial-scale carbon emissions estimation. To facilitateachievement of the national CERT, provincial carbon emissionsare decomposed into direct emissions of local activities otherthan thermal power generation and indirect emissions ofelectricity consumption through analysis of the carbon

emissions of cross-border flow energy. Furthermore, a hybridmethod 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 areincluded in the industrial sectors of the production area. Whenconsidering the scale and specialty of electricity generation andconsumption, the responsibility for carbon emissions during theproduction of thermal power is borne by the electricityconsumption area. This ensures that different regions withresource endowments have the same development space.Additionally, this induces national regions to emphasize theindirect carbon emissions associated with electricity con-sumption, which is conducive to achievement of the nationalemission reduction target. The high carbon emissions of thethermal power industry should be governed from an industrialperspective rather than a regional one, and the thermal powerindustry should actively engage in reduction of technicalemissions.Empirical studies were conducted and the spatial distribution

of carbon emissions in China was analyzed based on the hybridmethod developed in this study. Using the regression analysismethod, three indices, per capita GDP, the resource endow-ment index and the proportion of energy-intensive industries,were screened to preliminarily interpret differences amongChina’s regional carbon emissions. The carbon intensities ofdifferent regions were shown to decline with economic level.The carbon productivity of resource-rich provinces is usuallydisappointing, and energy-intensive industries exert a largerpositive contribution to carbon emissions. We also verified thatthese trade-offs were robust by fitting the IPCC values. Finally,uncertainty analysis of the method indicated that its estimationswere accurate and credible. Owing to a lack of provincialconsumption-based carbon data in China, only production-based approaches were compared with the hybrid method.Overall, our study is a first attempt at a hybrid carbonestimation method that could evolve once measurement ofregional emissions has started and improved technology hasbegun to be implemented. Future studies should be conductedto determine how to reduce uncertainties and ensure that themethod is suitable for decision-makers.

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

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■ ASSOCIATED CONTENT

*S Supporting InformationFirst of all, the composition of electricity production in China islisted in Table S1. Then, direct and indirect carbon emissionsassociated with electricity in different provinces of China arelisted in Table S2. The provincial carbon emission and potentialvariables data in China are listed in Tables S3 and S4. Spatialdifferentiation of carbon emissions in China are illustrated inFigure S1.Moreover, the correlation between provincial carbonemission intensity and potential variables analyzed by thePearson Correlation Coefficient is shown in Tables S5 and S6.Statistical testing of models shown in Figures 5−7 is describedin Tables S7−S9. The trade-offs estimated for the IPCCmethod is illustrated in Figure S2. Finally, the bottom-upapproach is illustrated. This material is available free of chargevia the Internet at http://pubs.acs.org.

■ AUTHOR INFORMATION

Corresponding Author*Phone/fax: 86-22-23508348; e-mail: baiht@nankai.edu.cn;seacenter@nankai.edu.cn.

NotesThe authors declare no competing financial interest.

■ ACKNOWLEDGMENTS

This research is supported by the National Natural ScienceFoundation of China (41301648), the Fundamental ResearchFunds for the Central Universities (65012501) and theNational Social Science Foundation of China (11AZD103).The authors thank three anonymous referees for theirextremely valuable comments and suggestions.

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