11
Environmental responsibility for sulfur dioxide emissions and associated biodiversity loss across Chinese provinces * Yuan Qian a, b, * , Paul Behrens b, c , Arnold Tukker b, d , Jo ~ ao F.D. Rodrigues b , Pingke Li a , Laura Scherer b a Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China b Institute of Environmental Sciences (CML), Leiden University, Einsteinweg 2, 2333 CC, Leiden, the Netherlands c Leiden University College The Hague, Anna van Buerenplein 301, 2595 DG, The Hague, the Netherlands d Netherlands Organization for Applied Scientic Research TNO, Anna van Buerenplein 1, 2595 DA, The Hague, the Netherlands article info Article history: Received 9 July 2018 Received in revised form 6 November 2018 Accepted 12 November 2018 Available online 15 November 2018 Keywords: Environmental inequality Impact assessment Multi-regional input-output analysis Responsibility sharing Soil acidication abstract Recent years have witnessed a growing volume in Chinese interregional trade, along with the increasing disparities in environmental pressures. This has prompted an increased attention on where the re- sponsibilities for environmental impacts should be placed. In this paper, we quantify the environmental responsibility of SO 2 emissions and biodiversity impacts due to terrestrial acidication at the provincial level for the rst time. We examine the environmental responsibility from the perspectives of produc- tion, consumption, and income generation by employing a Multi-Regional Input-Output (MRIO) model for 2007, 2010, and 2012. The results indicate that ~40% of SO 2 emissions were driven by the con- sumption in provinces other than where the emissions discharged. In particular, those developed provinces were net importers of SO 2 emissions and mainly outsourced their emissions to nearby developing provinces. Over the period of analysis, environmental inequality among 30 provinces was larger than GDP inequality. Furthermore, environmental inequality continued to increase while GDP inequality decreased over the time period. The results of a shared income- and consumption-based responsibility approach suggest that the environmental responsibility of SO 2 emissions and biodiver- sity impacts for developed provinces can reach up to ~4- to 93-fold the environmental pressure occurred within those provinces. This indicates that under these accounting principles the developed northern provinces in China would bear a much larger share of the environmental responsibility. © 2018 Elsevier Ltd. All rights reserved. 1. Introduction China has experienced rapid economic development over the last four decades. The GDP of China (at constant 2010 prices) increased from $264 billion to $9.50 trillion during 1997e2016, with an average annual growth rate of 9.6% (WB, 2018). However, this remarkable economic growth came at a cost of environmental damage. China has become one of the largest emitters of SO 2 , NO X , and greenhouse gases in the world (Liu et al., 2016; Meng et al., 2013). Along with ecological impacts, many emissions are linked to multiple health problems, including lung cancer (Tie et al., 2009), respiratory illness (Tao et al., 2014), and heart diseases (Wong et al., 2002), leading to a shorter life expectancy (Ebenstein et al., 2017). It has been estimated by Rohde & Muller (2015) that the air pollution contributed to1.6 million deaths per year in China, roughly 17% of all deaths. To mitigate environmental impacts, the Chinese government has promoted a series of measures, including increasing the share of non-fossil fuels (Yuan et al., 2018b), lowering CO 2 emission in- tensities (Cui et al., 2014), developing a trading scheme of carbon emissions (Wang et al., 2015), and formulating the accountability systems for local authorities (Schreifels et al., 2012). Although several environmental targets in China have been proposed at the national level, they are assigned to provinces according to the emissions of each province in policy formulation (Meng et al., 2011; Liu & Wang, 2017). However, the emissions discharged in one re- gion are not necessarily driven by the local consumption only but by the demand from other regions as well through the interregional * This paper has been recommended for acceptance by Dr. Kimberly Hageman. * Corresponding author. Department of Industrial Engineering, Tsinghua Uni- versity, Beijing, 100084, China. E-mail address: [email protected] (Y. Qian). Contents lists available at ScienceDirect Environmental Pollution journal homepage: www.elsevier.com/locate/envpol https://doi.org/10.1016/j.envpol.2018.11.043 0269-7491/© 2018 Elsevier Ltd. All rights reserved. Environmental Pollution 245 (2019) 898e908

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lable at ScienceDirect

Environmental Pollution 245 (2019) 898e908

Contents lists avai

Environmental Pollution

journal homepage: www.elsevier .com/locate/envpol

Environmental responsibility for sulfur dioxide emissions andassociated biodiversity loss across Chinese provinces*

Yuan Qian a, b, *, Paul Behrens b, c, Arnold Tukker b, d, Jo~ao F.D. Rodrigues b, Pingke Li a,Laura Scherer b

a Department of Industrial Engineering, Tsinghua University, Beijing, 100084, Chinab Institute of Environmental Sciences (CML), Leiden University, Einsteinweg 2, 2333 CC, Leiden, the Netherlandsc Leiden University College The Hague, Anna van Buerenplein 301, 2595 DG, The Hague, the Netherlandsd Netherlands Organization for Applied Scientific Research TNO, Anna van Buerenplein 1, 2595 DA, The Hague, the Netherlands

a r t i c l e i n f o

Article history:Received 9 July 2018Received in revised form6 November 2018Accepted 12 November 2018Available online 15 November 2018

Keywords:Environmental inequalityImpact assessmentMulti-regional input-output analysisResponsibility sharingSoil acidification

* This paper has been recommended for acceptanc* Corresponding author. Department of Industrial

versity, Beijing, 100084, China.E-mail address: [email protected] (Y

https://doi.org/10.1016/j.envpol.2018.11.0430269-7491/© 2018 Elsevier Ltd. All rights reserved.

a b s t r a c t

Recent years have witnessed a growing volume in Chinese interregional trade, along with the increasingdisparities in environmental pressures. This has prompted an increased attention on where the re-sponsibilities for environmental impacts should be placed. In this paper, we quantify the environmentalresponsibility of SO2 emissions and biodiversity impacts due to terrestrial acidification at the provinciallevel for the first time. We examine the environmental responsibility from the perspectives of produc-tion, consumption, and income generation by employing a Multi-Regional Input-Output (MRIO) modelfor 2007, 2010, and 2012. The results indicate that ~40% of SO2 emissions were driven by the con-sumption in provinces other than where the emissions discharged. In particular, those developedprovinces were net importers of SO2 emissions and mainly outsourced their emissions to nearbydeveloping provinces. Over the period of analysis, environmental inequality among 30 provinces waslarger than GDP inequality. Furthermore, environmental inequality continued to increase while GDPinequality decreased over the time period. The results of a shared income- and consumption-basedresponsibility approach suggest that the environmental responsibility of SO2 emissions and biodiver-sity impacts for developed provinces can reach up to ~4- to 93-fold the environmental pressure occurredwithin those provinces. This indicates that under these accounting principles the developed northernprovinces in China would bear a much larger share of the environmental responsibility.

© 2018 Elsevier Ltd. All rights reserved.

1. Introduction

China has experienced rapid economic development over thelast four decades. The GDP of China (at constant 2010 prices)increased from $264 billion to $9.50 trillion during 1997e2016,with an average annual growth rate of 9.6% (WB, 2018). However,this remarkable economic growth came at a cost of environmentaldamage. China has become one of the largest emitters of SO2, NOX,and greenhouse gases in the world (Liu et al., 2016; Meng et al.,2013). Along with ecological impacts, many emissions are linkedtomultiple health problems, including lung cancer (Tie et al., 2009),

e by Dr. Kimberly Hageman.Engineering, Tsinghua Uni-

. Qian).

respiratory illness (Tao et al., 2014), and heart diseases (Wong et al.,2002), leading to a shorter life expectancy (Ebenstein et al., 2017). Ithas been estimated by Rohde &Muller (2015) that the air pollutioncontributed to 1.6 million deaths per year in China, roughly 17% ofall deaths.

To mitigate environmental impacts, the Chinese governmenthas promoted a series of measures, including increasing the shareof non-fossil fuels (Yuan et al., 2018b), lowering CO2 emission in-tensities (Cui et al., 2014), developing a trading scheme of carbonemissions (Wang et al., 2015), and formulating the accountabilitysystems for local authorities (Schreifels et al., 2012). Althoughseveral environmental targets in China have been proposed at thenational level, they are assigned to provinces according to theemissions of each province in policy formulation (Meng et al., 2011;Liu & Wang, 2017). However, the emissions discharged in one re-gion are not necessarily driven by the local consumption only butby the demand from other regions as well through the interregional

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Y. Qian et al. / Environmental Pollution 245 (2019) 898e908 899

and international trade (Yuan et al., 2018c). Since China is a countrywith large regional disparities in the levels of economic develop-ment, resource endowment, and industrial development, suchdisparities may result in the emission transfers via the interpro-vincial trade: a spatial differentiation between direct emissions ofproduction and indirect emissions of consumption. It was esti-mated by Wang et al. (2017) that ~45% of the environmentaldamage in 2007 in China was driven by the interprovincial trade.Moreover, the emissions embodied in interprovincial trade usuallyflow from developing to developed regions, making developedregions become net importers and developing regions become netexporters (Su and Ang, 2014; Wang et al., 2018; Yang et al., 2018b;Yuan et al., 2018a).

Considering these embodied emissions, an important debate isunderway on the appropriate approaches to allocating the envi-ronmental responsibility. The production-based approach attri-butes full responsibility to the producers who benefit from theproduction of goods (e.g., the Kyoto protocol). On the contrary, theconsumption-based approach attributes full responsibility to thefinal consumers who benefit from the consumption of goods (Davis& Caldeira, 2010; Peters, 2008). Since producers and consumersboth benefit from the transactions along the value chain, these tworesponsibility allocation principles may be viewed as two extremesin a continuum (Sato, 2012). A compromise is the scheme of sharedenvironmental responsibility, as a weighted combination of theproduction- and consumption-based responsibilities (Andrew andForgie, 2008; Lenzen et al., 2007; Marques et al., 2012; Peters,2008; Rodrigues et al., 2006; Rodrigues and Domingos, 2008). Be-sides, it is also possible to assign the responsibility to the earners ofincome from the production of goods (i.e., the income-basedperspective) (Liang et al., 2017; Marques et al., 2012), and definethe environmental responsibility as a combination of either of thethree perspectives (production, consumption, and income)(Andrew and Forgie, 2008; Lenzen et al., 2007;Marques et al., 2012;Peters, 2008; Rodrigues et al., 2006; Rodrigues and Domingos,2008).

For the case of China, it has been argued that some form of re-sponsibility sharing is required for various emissions along valuechains (Homma et al., 2012; Meng et al., 2013; Zhao et al., 2015).However, most of the studies focus on the production- andconsumption-based approaches for China, and the studies onshared responsibility are conducted mainly at the national level(Andrew & Forgie, 2008) or at the sectoral level (Cadarso et al.,2012). This paper sets out, for the first time to the best of ourknowledge, to apply a responsibility sharing approach to direct andindirect air pollution within China at the provincial level. We focuson SO2 emissions and related terrestrial acidification impacts onbiodiversity as the environmental indicators, since SO2 is the pre-cursor of ambient sulfate and plays a crucial role in the formation ofacid rain and fine particles (Tao et al., 2012; Yan &Wu, 2017; Zhanget al., 2015). The sulfur deposition in soils and acidification canlower the pH, leach nutrients, and increase the bioavailability oftoxic heavy metals (Kumar, 2017), which may further lead tochanges in the ecosystem services of vegetation (Aherne & Posch,2013; Lovett et al., 2009; Pandey et al., 2014). Particularly, Chinais facing a major threat to ecosystems since the sulfur depositionexceeds critical loads in many areas (Duan et al., 2016). In this pa-per, we investigate the changes of SO2 emissions and biodiversityimpacts due to the terrestrial acidification over time between 2007,2010, and 2012. The responsibility sharing approach, the time se-ries, the inclusion of biodiversity impacts, and the Gini coefficientanalysis differentiate this work from the few earlier studies on SO2emissions and interprovincial trade (Huang et al., 2018; Zhang et al.,2018a, 2018b).

2. Materials and methods

2.1. Production and consumption-based environmentalresponsibility

In this paper we allocate the SO2 emissions discharged indifferent regions of China in 2007, 2010, and 2012 by an input-output approach according to three perspectives (production-based, consumption-based, and income-based). Assuming thatthere are m regions and n sectors, the expression of monetaryoutput flows in an input-output framework is:

xri ¼Xm

s¼1

Xn

j¼1

zrsij þXm

s¼1

yrsi þ exri (1)

where xri denotes the total output of sector i in region r, zrsij denotesthe intermediate requirement of sector j in region s from sector i inregion r, yrsi denotes the final demand of region s from sector i inregion r, and exri denotes the international exports of sector i inregion r.

Since the total inputs and outputs of industries are identical, it ispossible to formulate a similar expression for monetary inputflows:

xsj ¼Xm

r¼1

Xn

i¼1

zrsij þ vsj þ impsj (2)

where vsj is the primary inputs of sector j in region s and impsj is thecorresponding imports.

Furthermore, denoting Sri the SO2 emissions of sector i in regionr and Srh the SO2 emissions from households in the same region, theproduction-based SO2 emissions (PBE) of region r in this setting arethe sum of emissions discharged in every production sector andhousehold sector of that region:

PBEr ¼Xn

i¼1

Sri þ Srh (3)

The consumption-based emissions are calculated using theLeontief model, which captures the upstream indirect impactsembodied in final demand along the supply chain (Miller & Blair,1985). However, besides the emissions embodied in the final con-sumption of a region that originate either from that region or fromother regions in China, there are three other types of SO2 emissionsthat we need to address: (a) emissions discharged outside Chinabut embodied in the final demand of China; (b) emissions dis-charged in China but embodied in the exports of China; (c) andemissions from households.

Because this paper focuses on comparing the responsibility forSO2 emissions among Chinese regions we make the followingmethodological choices. Concerning (a) we do not allocate theemissions discharged outside China, as that would demand thedata on international emissions and flows or apply the assumptionof domestic technology for imported goods (Tang et al., 2012; Zhaoet al., 2015). Considering (b) we allocate the impacts embodied inexports to none of Chinese provinces but to the rest of the world(RoW). Concerning (c) we allocate the emissions from householdsto the region where the household consumption takes place.

Mathematically, the consumption-based SO2 emissions (CBE) ofregion s are:

CBEs ¼Xm

r¼1

Xn

i¼1

uri yrsi þ Srh (4)

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Y. Qian et al. / Environmental Pollution 245 (2019) 898e908900

The first term on the right-hand side of Eq. (4) denotes theemissions embodied in the final demand of region s, which iscalculated as the sum of the emissions embodied in the purchasesof every product from every region by the final demand of region s.The second term accounts for the emissions from households. Theconsumption-based responsibility of the RoW for the emissions

discharged within China isPm

s¼1

Pn

i¼1usi ex

si .

The consumption-based (or upstream) emissions embodied inthe final demand are quantified as the product of the upstreamintensity (total SO2 emissions discharged along the supply chainover unit of output) and the volume of final demand. By theLeontief model, the vector of upstream intensities, u, is calculatedas:

u ¼ b0ðI � AÞ�1 (5)

where b is the column vector of direct intensities, whose entries arebri ¼ Sri =x

ri , b

0 denotes the transpose of b, ðI � AÞ�1 is the Leontiefinverse matrix, and A is the technical coefficient matrix whoseentries are Ars

ij ¼ Zrsij =xsj .

Later, we will quantify the flows of upstream emissionsembodied in the interregional trade, which requires disaggregatingthe total upstream embodied emissions according to their sources.The matrix of disaggregated upstream intensity U, whose entry Urs

ijdenotes the emissions discharged in sector i of region r per unit ofoutput of sector j in region s, and is calculated as U ¼ b

!$ðI � AÞ�1

where b!

is the diagonalizedmatrix of b. The flow of emissions fromregion r to region s is now:

CBErs ¼Xm

k¼1

Xn

i¼1

Xn

j¼1

Urkij y

ksi (6)

Notice that it is possible for there to be emissions flowing fromregion r to region s through the purchase of final consumptiongoods produced in region k (but whose supply chain in turn leads toemissions in region r).

2.2. Terrestrial acidification and biodiversity loss

Terrestrial acidification is characterized by the changes in soilchemical properties and caused mainly by the atmospheric depo-sition of acidifying pollutants including NOX, SO2, and NH3 (Royet al., 2014). The acidification impacts of emissions can beassessed with the characterization factors obtained from a char-acterization model investigating the cause-effect chain of theemissions to the potential impacts (e.g., human health or biodi-versity loss) (Udo de Haes et al., 2002). The characterization factorfor terrestrial acidification is expressed as a function of (1) an at-mospheric fate factor representing the link between emissions anddeposition locations, (2) a soil sensitivity factor representing thechange of Hþ concentration in soil related to acid deposits over acertain area, and (3) an effect factor representing the loss ofvascular plant species due to the change of Hþ concentration in soil(Azevedo et al., 2013; Roy et al., 2014).

To assess the terrestrial acidification caused by SO2 emissionsderived from the MRIO model, the LC-Impact model is applied,which is a spatially differentiated method for global impactassessment. Compared to previous methods of life cycle impactassessment, the LC-Impact method incorporates new impactpathways, includes spatial differentiation for 11 major environ-mental mechanisms, and quantifies impacts on ecosystem qualityas potential global species loss (Verones et al., 2016). Whenassessing the terrestrial acidification caused by SO2 emissions, the

characterization factors of SO2 emissions at grid level (2.0� 2.5�

resolution) are obtained from the LC-Impact webpage (LC-Impact,2013). The zonal statistics are performed in GIS software toaggregate them to the provincial level, i.e., the raster map ofcharacterization factors for SO2 emissions is overlaid with thespatial information on provinces, and then the averages of all rastercells within each province are calculated.

2.3. Inequality analysis using the Gini coefficient

The Gini index is used to analyze the inequality of GDP, SO2emissions, and biodiversity impacts among 30 Chinese provinces(excluding Tibet, Hong Kong, Macau, and Taiwan). The Gini indexhas beenwidely used to investigate economic inequality (Gastwirth& Glauberman, 1976), and is increasingly used to analyze envi-ronmental inequality too (Dong and Liang, 2014; Jacobson et al.,2005; Luo et al., 2016; Sun et al., 2010).

When analyzing the inequalities of GDP, SO2 emissions, andbiodiversity impact, they are visualized in Lorenz curves where theordinate values represent the cumulative share of GDP and theabscissa values represent the cumulative shares of population, SO2emissions, and biodiversity impacts, respectively. The Gini indicesare calculated from the Lorenz curves, with a value of 0 indicatingthe complete equality of allocation and a value of 1 indicating thecomplete inequality of allocation (in the case of income, it meansone individual accrues all the national wealth). The Gini index isestimated as:

Gini ¼ 1�X30

r¼1

ðzr � zr�1Þðgdpr � gdpr�1Þ (7)

where zr denotes the cumulative share of population (or SO2emissions and biodiversity impacts when calculating the Giniindices of SO2 emission and biodiversity impact) in province r, gdprdenotes the cumulative share of GDP in province rwith conventionthat z0 ¼ 0 and gdp0 ¼ 0.

2.4. Income-based and shared environmental responsibility

In the same way as the Leontief model quantifies the indirectimpacts occurring upstream along a supply chain, the Ghosh modelquantifies the indirect impacts occurring downstream along asupply chain (Ghosh, 1958). The Leontief model can be used toaccount for the upstream emissions embodied in final demand,defining the consumption-based responsibility. Analogously, theGhoshmodel can be used to account for the downstream emissionsembodied in primary inputs, defining the income-based re-sponsibility (Marques et al., 2012).

As in the case of consumption-based perspective, it is necessaryto decide how to allocate the emissions embodied in internationaltrade and from final demand among different regions. We followthe same routine and (a) ignore the emissions discharged outsideChina; (b) allocate the downstream emissions embodied in importsto the RoW; and (c) allocate the emissions from final demand to theregion where the final consumption occurs.

Mathematically, the income-based SO2 emissions (IBE) of regions are:

IBEs ¼Xn

i¼1

dsi vsi þ Srh (8)

The new term dsi is the downstream intensity, calculated as:

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Fig. 1. Net transfers of SO2 emissions of eight regions in China.

Y. Qian et al. / Environmental Pollution 245 (2019) 898e908 901

d ¼ ðI � GÞ�1b (9)

where b is the column vector of direct intensities as in Eq. (5),

ðI � GÞ�1 is the Ghosh inverse matrix, and G is the matrix of fixed

sales coefficients whose entries are Grsij ¼ Zrsij =x

ri . The income-based

responsibility of the RoW for the emissions discharged within

China isPm

s¼1

Pn

i¼1dsi impsi .

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Y. Qian et al. / Environmental Pollution 245 (2019) 898e908902

To calculate the shared responsibility of SO2 emissions, we applythe indicator proposed by Rodrigues et al. (2006), whereby theenvironmental responsibility of a region is the average of itsconsumption-based and income-based emissions:

12ðCBEr þ IBErÞ (10)

Note that the current SO2 reduction targets are assigned toprovinces based on their total SO2 emissions (a production-basedapproach).

2.5. Data sources

We used the 30-province, 30-sector Chinese MRIO tables of2007 (Liu et al., 2012), 2010 (Liu et al., 2014), and 2012 (Mi et al.,2017). These tables are in the non-competitive form and deflatedat 2012 constant prices. Furthermore, since the sectoral SO2 emis-sions data are not available at the provincial level, they are esti-mated using the method proposed by Liu & Wang (2015) as Sri ¼Qr

i $bri $ð1� hri Þ, where Sri is the sectoral SO2 emissions (kg), Qr

i is thecoal consumption (kg), bri is the sulfur content (%), and hri is the SO2removal rate (%) of sector i for region r. The industrial and non-industrial SO2 emissions for 30 provinces can be calculated byassuming that the sulfur content is constant across sectors butdiffers among provinces (bri ¼ brj ¼ br), and that the SO2 removalrate is constant across provinces but differs among sectors (hri ¼hsi ¼ hi, implying that the technology diffusion is equal acrossprovinces). Note that the SO2 removal rates might actually differamong provinces beyond differences in the industrial structure, asassumed here. The SO2 scrubbers might be preferentially deployedin developed provinces or at large power plants. However, thenecessary data to support these assumptions and include the dif-ferences in our analysis are not available.

China Emission Accounts and Datasets (CEADs) provides thecoal consumption data (Shan et al., 2016, 2018). The data on SO2emissions, industrial SO2 removal, population, and provincial GDPare obtained from the China Statistical Yearbook on Environment.Since the industrial SO2 removal data in 2012 are not released yet,they are forecasted based on the data of 2001e2010 using expo-nential smoothing (Appendix A.3).

To maintain consistency in the classification of sectors, the 44sectors with SO2 emissions data and the 30 sectors in the MRIOtables are aggregated to 27 sectors, including 5 non-industrialsectors and 22 industrial sectors. The details on the sector aggre-gation are documented in Table S1, and the abbreviations for the 30provinces are shown in Table S2.

Fig. 2. Biodiversity loss due to terrestrial acidification at provincial level (PDF in thelegend means “potentially disappeared fraction of species” and the numeric values onthe maps indicate the biodiversity loss of each province).

3. Results

3.1. Production- and consumption-based SO2 emissions

During the study period, the total SO2 emissions increased from25.8Mt (million tons) in 2007 to 26.4Mt in 2010 and thendecreased to 22.5Mt in 2012, consistent with the results obtainedby Yang et al. (2018a). Figure S24 illustrates the production- andconsumption-based SO2 emissions in 2007, 2010, and 2012, andalso shows that the production-based emissions were higher thanthe consumption-based emissions in most provinces since a largepart of emissions embodied in consumption leaked to the RoW.During 2007e2012, ~17.1e23.9% of the emissions can be attributedto the RoW. Furthermore, ~64% of the emissions embodied in theRoW occurred in five coastal provinces, namely, Guangdong,Jiangsu, Zhejiang, Shandong, and Shanghai.

Figure S24 also shows that the intra-provincial and

inter-provincial consumption varied among different provinces. Itis worth noting that the intra-provincial consumption in developedprovinces accounted for only a small part of the total consumption-based emissions. For example, the intra-provincial consumption inBeijing, Tianjin, and Shanghai only accounted for 18.8%e39.1% ofthe total consumption-based emissions. However, in some devel-oping provinces with energy-intensive industries (e.g., Inner

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Y. Qian et al. / Environmental Pollution 245 (2019) 898e908 903

Mongolia, Shanxi, and Guizhou), the intra-provincial consumptioncontributed most to the total consumption-based emissions. Be-sides, the proportion of intra-provincial consumption showeddifferent trends in some neighboring provinces. For example, theproportion of intra-provincial consumption in Beijing indicated adecreasing trend, from 31.1% in 2007 to 21.7% in 2010, and then to14.1% in 2012. However, the proportions of intra-provincial con-sumption in nearby Tianjin and Hebei kept rising during the sametime period. Such a pattern among Beijing-Tianjin-Hebei areamight be due to the provincial transfer of industries after 2007,when some heavily polluting industries in Beijing were relocated toTianjin and Hebei (Zheng et al., 2018).

3.2. Inflows and outflows of SO2 emissions

Figure S25 shows the provincial inflow and outflow of SO2emissions through the inter-provincial trade within China in 2007,2010, and 2012. During the study period, ~37.3%e38.8% of theemissions were generated by the consumption of other provinces.Furthermore, for some developed provinces, e.g., Beijing, Tianjin,Shanghai, Jiangsu, Zhejiang, and Guangdong, the inflows weremuch larger than the outflows. For example, the inflows of SO2emissions in Beijing were ~9.9-, 18.2-, and 10.3-fold the outflows in2007, 2010, and 2012, respectively. On the contrary, for somedeveloping provinces, e.g., Shanxi, Inner Mongolia, Henan, Anhui,and Guizhou, the outflows were much larger than the inflows. Forexample, the outflows of SO2 emissions in Inner Mongolia were~6.5-, 2.3-, and 2.7-times the inflows in those years.

3.3. SO2 emissions embodied in interregional trade

From the analysis above, there are evident spatial differencesbetween inflows and outflows of SO2 emissions. To facilitate the

Fig. 3. Lorenz curves of population, SO2 emissions, and biodiversity loss relative to GDP(The numbers in brackets indicate the respective Gini values).

visualization of these flows, the 30 provinces are aggregated intoeight regions (Feng et al., 2013; Wang et al., 2017, see Figure S1 fordetails). The SO2 emissions embodied in interregional trade in2007, 2010, and 2012 are documented in Figure S26, Figure S27, andFigure S28, respectively.

Fig. 1 shows that the Northwest, Southwest, and Central regionshad the largest emissions during the study period. However, aconsiderable proportion of the emissions of these three regionswere generated by the consumption in other regions. Besides, thedeveloped Jing-Jin, East Coast, and South Coast regions were themain net importers of emissions, while the less developed North-west, Southwest, and Central regions were net exporters of emis-sions. In 2007, the Jing-Jin, East Coast, and South Coast regionsoutsourced between 0.60 and 1.54Mt to other regions, whichslightly increased in 2010. Although the inflows of these three re-gions decreased in 2012, they were still much higher than therespective outflows, ~2.1e5.9 times. In 2007, between 1.19 and1.69Mt of SO2 emissions generated in the Central, Northwest, andSouthwest regions were embodied in products traded to other re-gions, accounting for ~21.7e36.3% of the total production-basedemissions. The outflows of these three regions slightly fluctuatedin 2010 and 2012.

Fig. 1 also illustrates that the largest flow of SO2 emissions wasfrom the Central region to the East Coast region, followed by theflow from the Southwest to the South Coast, and that from theNorthwest to the East Coast. During the study period, ~59e71% ofemissions in the Central region can be attributed to the consump-tion of East Coast. The South Coast region predominately out-sourced the emissions to the Southwest region, and ~39e53% of theinflows to the South Coast were from the Southwest region. At theprovincial level, Guangdong was the main province in the SouthCoastal region outsourcing SO2 emissions to the Southwest. Besidesthe Central region, the Northwest region, particularly Gansu,

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Fig. 4. Comparison of provincial responsibility shares and reduction shares in 2010.

Y. Qian et al. / Environmental Pollution 245 (2019) 898e908904

Shaanxi, and Inner Mongolia, was also another main destination towhich the East Coast outsourced SO2 emissions. Fig. 1 also dem-onstrates that the outflows from the Central region to the SouthCoast region increased significantly in 2010, mainly due to theoutflows from Jiangxi to Guangdong. More details about the nettransfers are documented in Table S4, Table S5, and Table S6,respectively.

It is also worth noting that most provinces outsourced SO2emissions to their neighboring provinces. For example, Beijing andTianjin mainly outsourced the emissions to Hebei and InnerMongolia. Shanghai, Jiangsu, and Zhejiang, the three developedprovinces in the east, mainly outsourced the emissions to nearbyregions like Shandong, Henan, and Anhui. In the south, Guangdongmainly outsourced the emissions to Guizhou and Yunnan.

3.4. Biodiversity impacts at provincial level

Fig. 2 demonstrates the biodiversity impacts caused by SO2emissions for each province. During the study period, the threeprovinces, Xinjiang, Sichuan, and Fujian, suffered most from thebiodiversity loss indicated by the high values of the characteriza-tion factors in these provinces, which can be attributed mainly tothe atmospheric fate and soil sensitivity factors (Roy et al., 2014).Therefore, the severe biodiversity loss in these three provincesmight be due to the proximity of the receptor and the source of SO2

emissions and the high levels of soil acidification in these threeprovinces. Furthermore, the biodiversity losses of Sichuan andFujian reduced during 2010e2012, while the biodiversity loss ofXinjiang increased rapidly during the same period. Besides, thebiodiversity loss due to terrestrial acidification in China showed anobvious spatial disparity, with themost severe loss occurredmainlyin thewestern and central regions, andmuch lower loss occurred inthe eastern regions.

3.5. Regional environmental inequality

From Figs. 1 and 2, we find that both the SO2 emissions and thebiodiversity loss displayed regional disparities during the studyperiod. Considering that the embodied emission flows were mainlyfrom developing regions to developed regions, the economic in-equalities were likely reflected in environmental inequalities.Hence, the Lorenz curves and Gini indices of GDP, SO2 emissions,and biodiversity loss are illustrated in Fig. 3. During 2007e2010, theinequality of SO2 emissions remained more or less static, butslightly increased during 2010e2012. Furthermore, the inequalityof SO2 emissions was larger than that of GDP. The changing patternof SO2 emissions inequality was in contrast to that of GDPinequality, consistent with Clarke-Sather et al. (2011) who foundthat carbon inequality and income inequality in China showed in-verse trends during 1997e2007. Compared to SO2 emissions andGDP, the biodiversity loss in 2007, 2010, and 2012 showed thelargest degrees of inequality, with Gini coefficients of ~0.9.

3.6. Shared income and consumer responsibility

We now investigate the shared environmental responsibilitiesof SO2 emissions and associated biodiversity loss at the provinciallevel. When the income-generating provinces share the re-sponsibility with the consuming provinces, we find a similarpattern of provincial allocation of environmental responsibility asthat under the consumption-based accounting. Under the sharedresponsibility approach, the RoWwould bear ~15% responsibility ofthe total SO2 emissions and only 7 out of 30 provinces would bearmore responsibility than the production-based emissions dis-charged in their own territory. Furthermore, these 7 provinces are

mainly developed Jing-Jin regions and developing northeasternregions (e.g., Heilongjiang, Jilin). When concerning the biodiversityloss caused by SO2 emissions, only a few provinces would bear lessresponsibility, e.g., Sichuan, Fujian, Xinjiang, and Qinghai. Furtherdetails about the shared environmental responsibility of SO2emissions and associated biodiversity loss are documented in

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Fig. 5. Provincial responsibility for the biodiversity loss caused by terrestrial acidification (Unit: PDF$yr).

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Table S7 and Table S8.Fig. 4 and Fig. 5 show the contribution of consumption, income,

and household consumption to the environmental responsibility ofSO2 emissions and biodiversity loss. As illustrated in Fig. 4, theconsumption contributed most to the environmental responsibilityfor developed regions, e.g., Beijing, Shanghai, and Zhejiang.

However, for developing regions, the income contributed most tothe shared responsibility, e.g., Shanxi, Yunnan, and Heilongjiang.These regions showed a similar pattern when assessing the envi-ronmental responsibility for biodiversity loss. In contrast to otherprovinces that would bear less responsibility, the household con-sumption in Xinjiang contributed a relatively large part to the final

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responsibility for biodiversity loss (Fig. 5).The current pollution control targets in China are designed by

the national government and then assigned to each province. Wemay assess the fairness of the current allocation scheme of SO2reduction targets among provinces under the shared responsibilityprinciple by comparing the provincial share in the allocation ofenvironmental responsibility with the pollution reduction target.The latest reduction targets for SO2 emissions on the provinciallevel were designed for 2010 according to the 2005 levels. Theprovincial shares of SO2 reduction in the policy are calculated basedon the provincial reduction targets for SO2 emissions, as shown inTable S9. The comparison between the provincial shares of envi-ronmental responsibility and the reduction targets is conducted inFig. 4. The results indicate that the reduction targets of someprovinces fall behind their estimated environmental responsibilityfor SO2 emissions, e.g., Beijing, Tianjin, and Inner Mongolia. Forsome other provinces, e.g., Shanxi, Shanghai, and Jiangsu, thereduction targets exceeded the environmental responsibility.

4. Discussion

Our results showed that the developed provinces had largeroutflows than inflows of SO2 emissions and mainly outsourcedemissions to those developing provinces with energy-intensiveindustries, especially to their neighboring developing provinces.Under a shared income- and consumption-based responsibilityapproach, some developed provinces would bear more emissionresponsibility than that under the production-based accountingmethod. Furthermore, the developing provinces mainly acted asresource suppliers in the domestic supply chain, especially in theenergy intensive sectors (e.g., coal mining, chemistry, metallurgy,and electricity). The developed provinces, however, mainly acted asfinal consumers rather than resources suppliers, especially in theconstruction and service sectors (Figure S29, Figure S30).

However, the responsibility of SO2 emissions and associatedbiodiversity loss showed different patterns. Only a few provinceswould bear more responsibility for SO2 emissions, while mostprovinces would bear more responsibility for biodiversity loss. Thelarge differences of biodiversity effects among regions were mainlydue to the variations in the distances between emissions anddeposition, the buffer capacity, and the plant species sensitivity.

When comparing biodiversity loss to SO2 emissions, Xinjiang,Sichuan, and Fujian sufferedmost as indicated by the high values ofthe characterization factors in these provinces. Furthermore, thehousehold consumption in Xinjiang accounted for ~38.9%, 26.8%,and 22.2% of the total responsibility in 2007, 2010, and 2012, largerthan the corresponding proportions in other provinces, indicatingthat improving the energy efficiency in household consumptioncould be an efficient way to lower the SO2-related biodiversity lossin Xinjiang.

Our analysis also showed that the Gini indices of GDP and SO2emissions have the opposite temporal trends during the period2007e2012, consistent with the research by Clarke-Sather et al.(2011) investigating the relationship between income and carbonemissions. However, our analysis revealed that the inequality of SO2emissions exceeded GDP inequality while the inequality of carbonemissions was lower than income inequality as shown in Clarke-Sather et al. (2011). According to Chen et al. (2016), the differ-ences of interprovincial carbon emissions from coal in China weregreater than that from fossil fuels. Considering that coal combus-tion accounts for ~72% of the total energy consumption in Chinaand is the main source of SO2 emissions (Yang et al., 2016), the SO2emission differences were greater than the GDP differences. Adistinct characteristic in the inequality analysis is that the biodi-versity impact inequality was far greater than GDP and SO2

inequalities, because the biodiversity loss in Xinjiang, Sichuan, andFujian was much more severe than in other provinces.

The impacts of other acidifying pollutants (NOx and NH3) and ofpollutant interactions on terrestrial biodiversity may be investi-gated in an analogous manner. In addition, the impacts on aquaticecosystems and on human health deserve more research attention.

5. Conclusions

Using a MRIO model, this paper conducted a quantification ofthe shared responsibility for SO2 emissions and associated biodi-versity loss for 30 provinces in China for 2007, 2010, and 2012. Theresults showed that the developed provinces caused more SO2emissions through consumption than through production, whilethe opposite applied to the developing provinces. Under the sharedresponsibility principle, the rest of the world would bear ~15% re-sponsibility of the total SO2 emissions in China. Some developednorthern provinces (e.g., Beijing, Tianjin) and developing north-eastern provinces (e.g., Heilongjiang, Jilin) would bear more re-sponsibility for SO2 emissions. Other provinces, especially thosewith energy-intensive industries, would bear less responsibility forSO2 emissions. For example, the responsibility for SO2 emissions inBeijing was ~1.8-, 2.4-, and 3.6-times the actual emissions in 2007,2010, and 2012. However, the responsibility for SO2 emissions inInner Mongolia was only 69.7%, 77.4%, and 75.6% of the actualemissions.

Compared to SO2 emissions, biodiversity loss was much moreunequal within 30 provinces in China, with Gini coefficients ofabout 0.9. The provinces that suffered from severe biodiversity loss,e.g., Sichuan, Fujian, and Xinjiang, would bear less environmentalresponsibility. Furthermore, the differences between environ-mental responsibility and biodiversity loss occurred within theprovinces were even larger. For example, in Xinjiang, the environ-mental responsibility for biodiversity loss was ~73.8%, 74.6%, and74.9% of the biodiversity loss occurred within the province in 2007,2010, and 2012. However, in Shanghai, the responsibility forbiodiversity loss was ~58-, 54-, and 93-fold the biodiversity lossoccurred within the province.

Acknowledgements

This work was partially supported by the “Tsinghua UniversityInitiative Scientific Research Program” [grant number 2014z2017]and the “Short-Term Study Abroad Fund for the Ph.D. Students ofTsinghua University” [contract number 2017173].

Appendix A. Supplementary data

Supplementary data related to this article can be found athttps://doi.org/10.1016/j.envpol.2018.11.043.

References

Aherne, J., Posch, M., 2013. Impacts of nitrogen and sulphur deposition on forestecosystem services in Canada. Curr. Opin. Environ. Sustain. 5, 108e115. https://doi.org/10.1016/j.cosust.2013.02.005.

Andrew, R., Forgie, V., 2008. A three-perspective view of greenhouse gas emissionresponsibilities in New Zealand. Ecol. Econ. 68, 194e204. https://doi.org/10.1016/j.ecolecon.2008.02.016.

Azevedo, L.B., Van Zelm, R., Hendriks, A.J., Bobbink, R., Huijbregts, M.A.J., 2013.Global assessment of the effects of terrestrial acidification on plant speciesrichness. Environ. Pollut. 174, 10e15. https://doi.org/10.1016/j.envpol.2012.11.001.

Cadarso, M.�A., L�opez, L.A., G�omez, N., Tobarra, M.�A., 2012. International trade andshared environmental responsibility by sector. An application to the Spanisheconomy. Ecol. Econ. 83, 221e235. https://doi.org/10.1016/j.ecolecon.2012.05.009.

Chen, J., Cheng, S., Song, M., Wang, J., 2016. Interregional differences of coal carbon

Page 10: Environmental responsibility for sulfur dioxide emissions ... · 01/01/2019  · Environmental responsibility for sulfur dioxide emissions and associated biodiversity loss across

Y. Qian et al. / Environmental Pollution 245 (2019) 898e908 907

dioxide emissions in China. Energy Pol. 96, 1e13. https://doi.org/10.1016/j.enpol.2016.05.015.

Clarke-Sather, A., Qu, J., Wang, Q., Zeng, J., Li, Y., 2011. Carbon inequality at the sub-national scale: a case study of provincial-level inequality in CO2 emissions inChina 1997e2007. Energy Pol. 39, 5420e5428. https://doi.org/10.1016/j.enpol.2011.05.021.

Cui, L.B., Fan, Y., Zhu, L., Bi, Q.H., 2014. How will the emissions trading scheme savecost for achieving China's 2020 carbon intensity reduction target? Appl. Energy136, 1043e1052. https://doi.org/10.1016/j.apenergy.2014.05.021.

Davis, S.J., Caldeira, K., 2010. Consumption-based accounting of CO2 emissions. Proc.Natl. Acad. Sci. Unit. States Am. 107, 5687e5692. https://doi.org/10.1073/pnas.0906974107.

Dong, L., Liang, H., 2014. Spatial analysis on China's regional air pollutants and CO2emissions: emission pattern and regional disparity. Atmos. Environ. 92,280e291. https://doi.org/10.1016/j.atmosenv.2014.04.032.

Duan, L., Yu, Q., Zhang, Q., Wang, Z., Pan, Y., Larssen, T., Tang, J., Mulder, J., 2016. Aciddeposition in Asia: emissions, deposition, and ecosystem effects. Atmos. Envi-ron. 146, 55e69. https://doi.org/10.1016/j.atmosenv.2016.07.018.

Ebenstein, A., Fan, M., Greenstone, M., He, G., Zhou, M., 2017. New evidence on theimpact of sustained exposure to air pollution on life expectancy from China'sHuai River Policy. Proc. Natl. Acad. Sci. Unit. States Am. 114, 10384e10389.https://doi.org/10.1073/pnas.1616784114.

Feng, K., Davis, S.J., Sun, L., Li, X., Guan, D., Liu, W., Liu, Z., Hubacek, K., 2013.Outsourcing CO2 within China. Proc. Natl. Acad. Sci. Unit. States Am. 110,11654e11659. https://doi.org/10.1073/pnas.1219918110.

Gastwirth, J.L., Glauberman, M., 1976. The interpolation of the Lorenz curve and Giniindex from grouped data. Econometrica 44, 479e483.

Ghosh, A., 1958. Input-output approach in an allocation system. Economica 25,58e64.

Homma, T., Akimoto, K., Tomoda, T., 2012. Quantitative evaluation of time-seriesGHG emissions by sector and region using consumption-based accounting.Energy Pol. 51, 816e827. https://doi.org/10.1016/j.enpol.2012.09.031.

Huang, R., Hubacek, K., Feng, K., Li, X., Zhang, C., 2018. Re-examining embodied SO2and CO2 emissions in China. Sustainability 10, 1505. https://doi.org/10.3390/su10051505.

Jacobson, A., Milman, A.D., Kammen, D.M., 2005. Letting the (energy) Gini out of thebottle: Lorenz curves of cumulative electricity consumption and Gini co-efficients as metrics of energy distribution and equity. Energy Pol. 33,1825e1832. https://doi.org/10.1016/j.enpol.2004.02.017.

Kumar, S., 2017. Acid rain-The major cause of pollution: its causes, effects and so-lution. Int. J. Appl. Chem. 13, 53e58.

LC-Impact, 2013. Characterization Factors for Terrestrial Acidification [WWWDocument]. LC-Impact, Robin Budel. URL. http://lc-impact.eu/downloads-characterisation-factors. (Accessed 6 April 2018).

Lenzen, M., Murray, J., Sack, F., Wiedmann, T., 2007. Shared producer and consumerresponsibility-Theory and practice. Ecol. Econ. 61, 27e42. https://doi.org/10.1016/j.ecolecon.2006.05.018.

Liang, S., Qu, S., Zhu, Z., Guan, D., Xu, M., 2017. Income-based greenhouse gasemissions of nations. Environ. Sci. Technol. 51, 346e355. https://doi.org/10.1021/acs.est.6b02510.

Liu, F., Zhang, Q., Van Der A, R.J., Zheng, B., Tong, D., Yan, L., Zheng, Y., He, K., 2016.Recent reduction in NOx emissions over China: synthesis of satellite observa-tions and emission inventories. Environ. Res. Lett. 11, 114002. https://doi.org/10.1088/1748-9326/11/11/114002.

Liu, Q., Wang, Q., 2017. Sources and flows of China's virtual SO2 emission transfersembodied in interprovincial trade: a multiregional input-output analysis.J. Clean. Prod. 161, 735e747. https://doi.org/10.1016/j.jclepro.2017.05.003.

Liu, Q., Wang, Q., 2015. Reexamine SO2 emissions embodied in China's exports usingmultiregional input-output analysis. Ecol. Econ. 113, 39e50. https://doi.org/10.1016/j.ecolecon.2015.02.026.

Liu, W., Chen, J., Tang, Z., Liu, H., Han, D., Li, F., 2012. Compliment Theory andPractice of China’s Interregion Input-output Table for 30 Regions in 2007 (inChinese). China Statictics Press, Beijing.

Liu, W., Tang, Z., Chen, J., Yang, B., 2014. China's Interregional Input-output Table for30 Regions in 2010 (In Chinese). China Statictics Press, Beijing.

Lovett, G.M., Tear, T.H., Evers, D.C., Findlay, S.E.G., Cosby, B.J., Dunscomb, J.K.,Driscoll, C.T., Weathers, K.C., 2009. Effects of air pollution on ecosystems andbiological diversity in the eastern United States. Ann. N. Y. Acad. Sci. 1162,99e135. https://doi.org/10.1111/j.1749-6632.2009.04153.x.

Luo, X., Dong, L., Dou, Y., Liang, H., Ren, J., Fang, K., 2016. Regional disparity analysisof Chinese freight transport CO2 emissions from 1990 to 2007: driving forcesand policy challenges. J. Transport Geogr. 56, 1e14. https://doi.org/10.1016/j.jtrangeo.2016.08.010.

Marques, A., Rodrigues, J., Lenzen, M., Domingos, T., 2012. Income-based environ-mental responsibility. Ecol. Econ. 84, 57e65. https://doi.org/10.1016/j.ecolecon.2012.09.010.

Meng, B., Xue, J., Feng, K., Guan, D., Fu, X., 2013. China's inter-regional spillover ofcarbon emissions and domestic supply chains. Energy Pol. 61, 1305e1321.https://doi.org/10.1016/j.enpol.2013.05.108.

Meng, L., Guo, J., Chai, J., Zhang, Z., 2011. China's regional CO2 emissions: charac-teristics, inter-regional transfer and emission reduction policies. Energy Pol. 39,6136e6144. https://doi.org/10.1016/j.enpol.2011.07.013.

Mi, Z., Meng, J., Guan, D., Shan, Y., Song, M., Wei, Y.-M., Liu, Z., Hubacek, K., 2017.Chinese CO2 emission flows have reversed since the global financial crisis. Nat.Commun. 8, 1712. https://doi.org/10.1038/s41467-017-01820-w.

Miller, R.E., Blair, P.D., 1985. Input-output Analysis: Foundations and Extensions.Prentice-Hall, Inc., Englewood Cliffs, New Jersery.

Pandey, B., Agrawal, M., Singh, S., 2014. Coal mining activities change plant com-munity structure due to air pollution and soil degradation. Ecotoxicology 23,1474e1483. https://doi.org/10.1007/s10646-014-1289-4.

Peters, G.P., 2008. From production-based to consumption-based national emissioninventories. Ecol. Econ. 65, 13e23. https://doi.org/10.1016/j.ecolecon.2007.10.014.

Rodrigues, J., Domingos, T., 2008. Consumer and producer environmental re-sponsibility: comparing two approaches. Ecol. Econ. 66, 533e546. https://doi.org/10.1016/j.ecolecon.2007.12.010.

Rodrigues, J., Domingos, T., Giljum, S., Schneider, F., 2006. Designing an indicator ofenvironmental responsibility. Ecol. Econ. 59, 256e266. https://doi.org/10.1016/j.ecolecon.2005.10.002.

Rohde, R.A., Muller, R.A., 2015. Air pollution in China: mapping of concentrationsand sources. PloS One 10, 1e14. https://doi.org/10.1371/journal.pone.0135749.

Roy, P.O., Azevedo, L.B., Margni, M., van Zelm, R., Deschenes, L., Huijbregts, M.A.J.,2014. Characterization factors for terrestrial acidification at the global scale: asystematic analysis of spatial variability and uncertainty. Sci. Total Environ.500e501, 270e276. https://doi.org/10.1016/j.scitotenv.2014.08.099.

Sato, M., 2012. Embodied Carbon in Trade: a Survey of the Empirical Literature.Centre for Climate Change Economics and Policy.

Schreifels, J.J., Fu, Y., Wilson, E.J., 2012. Sulfur dioxide control in China: policyevolution during the 10th and 11th Five-year Plans and lessons for the future.Energy Pol. 48, 779e789. https://doi.org/10.1016/j.enpol.2012.06.015.

Shan, Y., Guan, D., Zheng, H., Ou, J., Li, Y., Meng, J., Mi, Z., Liu, Z., Zhang, Q., 2018.China CO2 emission accounts 1997e2015. Sci. Data 5, 1e14. https://doi.org/10.1038/sdata.2017.201.

Shan, Y., Liu, J., Liu, Z., Xu, X., Shao, S., Wang, P., Guan, D., 2016. New provincial CO2emission inventories in China based on apparent energy consumption data andupdated emission factors. Appl. Energy 184, 742e750. https://doi.org/10.1016/j.apenergy.2016.03.073.

Su, B., Ang, B.W., 2014. Input-output analysis of CO2 emissions embodied in trade: amulti-region model for China. Appl. Energy 114, 377e384. https://doi.org/10.1016/j.apenergy.2013.09.036.

Sun, T., Zhang, H., Wang, Y., Meng, X., Wang, C., 2010. The application of environ-mental Gini coefficient (EGC) in allocating wastewater discharge permit: thecase study of watershed total mass control in Tianjin, China. Resour. Conserv.Recycl. 54, 601e608. https://doi.org/10.1016/j.resconrec.2009.10.017.

Tang, X., Zhang, B., Feng, L., Snowden, S., H€o€ok, M., 2012. Net oil exports embodiedin China's international trade: an input-output analysis. Energy 48, 464e471.https://doi.org/10.1016/j.energy.2012.10.010.

Tao, M., Chen, L., Su, L., Tao, J., 2012. Satellite observation of regional haze pollutionover the North China Plain. J. Geophys. Res. Atmos. 117, 1e16. https://doi.org/10.1029/2012JD017915.

Tao, Y., Mi, S., Zhou, S., Wang, S., Xie, X., 2014. Air pollution and hospital admissionsfor respiratory diseases in Lanzhou, China. Environ. Pollut. 185, 196e201.https://doi.org/10.1016/j.envpol.2013.10.035.

Tie, X., Wu, D., Brasseur, G., 2009. Lung cancer mortality and exposure to atmo-spheric aerosol particles in Guangzhou, China. Atmos. Environ. 43, 2375e2377.https://doi.org/10.1016/j.atmosenv.2009.01.036.

Udo de Haes, H., Finnveden, G., Goedkoop, M.J., Hauschild, M.Z., Hertwich, E.G.,Hofstetter, P., Jolliet, O., Kl€opfer, W., Krewitt, W., Lindeijer, E., Mueller-Wenk, R.,Olson, S., Pennington, D., Potting, J., Steen, B., 2002. Life cycle impact assess-ment: striving towards best practice. In: SETAC.

Verones, F., Hellweg, S., Azevedo, L.B., Chaudhary, A., Cosme, N., Fantke, P.,Goedkoop, M., Hauschild, M., Laurent, A., Mutel, C.L., Pfister, S., Ponsioen, T.,Steinmann, Z., Zelm, R., van, Vieira, M., Huijbregts, M.A.J., 2016. LC-impactVersion 0.5-A Spatially Differentiated Life Cycle Impact Assessment Approach.

Wang, F., Liu, B., Zhang, B., 2017. Embodied environmental damage in interregionaltrade: a MRIO-based assessment within China. J. Clean. Prod. 140, 1236e1246.https://doi.org/10.1016/j.jclepro.2016.10.036.

Wang, P., Dai, H. cheng, Ren, S. yan, Zhao, D. qing, Masui, T., 2015. AchievingCopenhagen target through carbon emission trading: economic impactsassessment in Guangdong Province of China. Energy 79, 212e227. https://doi.org/10.1016/j.energy.2014.11.009.

Wang, Z., Yang, Y., Wang, B., 2018. Carbon footprints and embodied CO2 transfersamong provinces in China. Renew. Sustain. Energy Rev. 82, 1068e1078. https://doi.org/10.1016/j.rser.2017.09.057.

WB, 2018. World Bank National Accounts Data [WWW Document]. World Bank Gr.URL. https://data.worldbank.org/indicator/NY.GDP.MKTP.KD?locations¼CN&view¼chart. (Accessed 6 April 2018).

Wong, T., Tam, W., Yu, T., Wong, A., 2002. Associations between daily mortalitiesfrom respiratory and air pollution in Hong Kong, China. Occup. Environ. Med.59, 30e35.

Yan, S., Wu, G., 2017. SO2 emissions in China-Their network and hierarchicalstructures. Sci. Rep. 7, 46216. https://doi.org/10.1038/srep46216.

Yang, X., Wang, S., Zhang, W., Li, J., Zou, Y., 2016. Impacts of energy consumption,energy structure, and treatment technology on SO2 emissions: a multi-scaleLMDI decomposition analysis in China. Appl. Energy 184, 714e726. https://doi.org/10.1016/j.apenergy.2016.11.013.

Yang, X., Zhang, W., Fan, J., Li, J., Meng, J., 2018a. The temporal variation of SO2emissions embodied in Chinese supply chains, 2002e2012. Environ. Pollut. 241,172e181. https://doi.org/10.1016/j.envpol.2018.05.052.

Yang, X., Zhang, W., Fan, J., Yu, J., Zhao, H., 2018b. Transfers of embodied PM2.5

Page 11: Environmental responsibility for sulfur dioxide emissions ... · 01/01/2019  · Environmental responsibility for sulfur dioxide emissions and associated biodiversity loss across

Y. Qian et al. / Environmental Pollution 245 (2019) 898e908908

emissions from and to the North China region based on a multiregional input-output model. Environ. Pollut. 235, 381e393. https://doi.org/10.1016/j.envpol.2017.12.115.

Yuan, R., Behrens, P., Rodrigues, J.F.D., 2018a. The evolution of inter-sectoral linkagesin China's energy-related CO2 emissions from 1997 to 2012. Energy Econ. 69,404e417. https://doi.org/10.1016/j.eneco.2017.11.022.

Yuan, R., Behrens, P., Tukker, A., Rodrigues, J.F.D., 2018b. Carbon overhead: theimpact of the expansion in low-carbon electricity in China 2015e2040. EnergyPol. 119, 97e104. https://doi.org/10.1016/j.enpol.2018.04.027.

Yuan, R., Rodrigues, J.F.D., Behrens, P., 2018c. Impact of non-fossil electricity on thecarbon emissions embodied in China's exports. J. Clean. Prod. 192, 582e596.https://doi.org/10.1016/j.jclepro.2018.04.255.

Zhang, Q.Q., Wang, Y., Ma, Q., Yao, Y., Xie, Y., He, K., 2015. Regional differences inChinese SO2 emission control efficiency and policy implications. Atmos. Chem.Phys. 15, 6521e6533. https://doi.org/10.5194/acp-15-6521-2015.

Zhang, W., Liu, Y., Feng, K., Hubacek, K., Wang, J., Liu, M., Jiang, L., Liu, N., Zhang, P.,

Zhou, Y., Bi, J., 2018a. Revealing environmental inequality hidden in China'sinter-regional trade. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.8b00009.

Zhang, W., Wang, F., Hubacek, K., Liu, Y., Wang, J., Feng, K., Jiang, L., Jiang, H.,Zhang, B., Bi, J., 2018b. Unequal exchange of air pollution and economic benefitsembodied in China's exports. Environ. Sci. Technol. 52, 3888e3898. https://doi.org/10.1021/acs.est.7b05651.

Zhao, H.Y., Zhang, Q., Guan, D.B., Davis, S.J., Liu, Z., Huo, H., Lin, J.T., Liu, W.D.,He, K.B., 2015. Assessment of China's virtual air pollution transport embodied intrade by using a consumption-based emission inventory. Atmos. Chem. Phys.15, 5443e5456. https://doi.org/10.5194/acp-15-5443-2015.

Zheng, H., Wang, X., Li, M., Zhang, Y., Fan, Y., 2018. Interregional trade among re-gions of urban energy metabolism: a case study between Beijing-Tianjin-Hebeiand others in China. Resour. Conserv. Recycl. 132, 339e351. https://doi.org/10.1016/j.resconrec.2017.05.010.