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Policy Analysis
Revealing Environmental Inequality Hidden in China’s Inter-Regional Trade Wei Zhang, Yu Liu, Kuishuang Feng, Klaus Hubacek, Jinnan Wang, Miao-Miao Liu, Ling Jiang, Hongqiang Jiang, Nianlei Liu, Pengyan Zhang, Ying Zhou, and Jun Bi Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00009 • Publication Date (Web): 25 May 2018 Downloaded from http://pubs.acs.org on May 25, 2018
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Environmental Science & Technology
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Revealing Environmental Inequality Hidden in China’s Inter-Regional Trade
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Wei Zhang1,2,‡, Yu Liu3,4,‡, Kuishuang Feng5, Klaus Hubacek5,6, Jinnan Wang1,2*, Miaomiao Liu1, Ling Jiang7, Hongqiang Jiang2, Nianlei Liu2, Pengyan Zhang8, Ying Zhou2 and Jun Bi1*
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1 State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023,
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China
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2 State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy for
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Environmental Planning, Beijing 100012, China
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3 Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
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4 School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
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5 Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, United States
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6 Department of Environmental Studies, Masaryk University, Brno 60200, Czech Republic
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7 School of Government, Central University of Finance and Economics, Beijing 100081, China
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8 College of Environment and Planning, Henan University, Kaifeng 475004, China
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Abstract: Trade among regions or countries allows not only the exchange of goods and services but also leads to the
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transfer of pollution. The unequal exchange of goods and services and associated value added and pollution may be
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subject to environmental inequality in China given that Chinese provinces are in different development stages. By using
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the latest multiregional input-output tables and the sectoral air pollutant emission inventory in 2012, we traced
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emissions and value added along China’s domestic supply chains. Here we show that approximately 62%~76% of the
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consumption-based air pollution emissions of richer regions (Beijing-Tianjin, East Coast and South Coast) were
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outsourced to other regions; however, approximately 70% of value added triggered by these region’s final consumption
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was retained within the region. Some provinces in western China, such as Guizhou, Ningxia and Yunnan, not only
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incurred net pollution inflows but also suffered negative balance of value added when trading with rich provinces.
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Addressing such inequalities could not only provide a basis for determining each province’s responsibility for pollution
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control but also a model for other emerging economies.
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Table of Contents (TOC)
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1. Introduction
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China is suffering from serious regional air pollution, caused by rapid urbanization, heavy industrialization and a
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coal-based energy structure1. Over the 2010~2015 period, China accounted for approximately 50% of global coal
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consumption2, produced 48% of global steel products3, and thus contributed approximately 30% of global emissions of
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sulphur dioxide (SO2) and 20% of nitrogen oxides (NOx)4, 5 each year. In 2016, 75.1% of 338 monitored cities failed to
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reach China’s Grade II standard for air quality (≤35 µg/m3) and the annual average PM2.5 concentration in monitored
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cities was 4.7 times World Health Organization guidelines (≤10 µg/m3)6. Monitoring data and remote sensing
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observations indicate that frequent wide-range haze plagues populous economic regions, such as the
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Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta7-10, which has become one of the most
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pressing environmental problems and significantly impacts public health11, 12. Moreover, extensive cross-border physical
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transport of airborne pollutants amplifies regional problems13. For example, approximately 30% of PM2.5 in Beijing is
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from surrounding areas14. Thus, the State Council – China’s highest policymaking body – released a national action plan
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for air pollution control in 2013, which emphasized cross-provincial collaboration on air pollution control and set
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provinces’ targets for reducing air pollutant emissions mostly based on their territorial emissions15.
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However, this policy ignores the transfer of responsibility hidden in products exchanged among provinces. The
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Environmental Kuznets Curve (EKC) hypothesis states that per capita emissions may decline in relative or absolute
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terms with increasing per capita income growth after per capita wealth in the country/region reached to a turning point 16,
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pollution to low income regions with less strict environmental regulation according to the pollution haven
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hypothesis18-21. Generally speaking, the provinces with more pollution-intensive industries (thermal power, steel,
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cement, etc.) and a carbon-intensive energy mix bear the cost of the incurring air pollution22-24. From another
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perspective, exporting pollution-intensive products also stimulates economic growth in less developed provinces. For
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example, as the largest producer of iron, steel and cement in China, the relatively low-income province Hebei, gained
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46% of its GDP via exports of industrial products to other provinces. Hence, both transferred economic benefits and air
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pollutant emissions embodied in inter-regional trade should be considered when designing policies for cross-regional
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collaboration.
. However, other evidence shows that the reduction in pollution emissions is to some extent due to the outsourcing
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Ecologically Unequal Exchange (EUE) is generally understood as the unequal material exchange relations among
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countries holding different positions in the world-system25-27, and were mostly found between “core” countries (e.g. the
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United States) and “peripheral” countries28, 29. Recent research operationalized EUE by tracing and comparing flows of
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trade-embodied wealth and pollution along global supply chains30-32. China, as the world’s factory, plays the role of a
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“semi-core” country in the global trade network but also suffers from environmental inequality from developed
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countries33, 34. Therefore, establishing shared responsibility for pollution between rich consumers and poor producers
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can mitigate some of the problems caused by EUE globally, and also within countries such as China with serious wealth
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and pollution inequalities35-37. At present, most previous studies have focused on trade-embodied emissions22, 38, their
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related contributions to air quality39, 40 or public health41-43 and, to some extent, the unequal relationships between
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developed and less developed regions within China. However, the economic-environmental inequality hidden of China’s
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inter-regional trade has seldom been quantified. The quantification of unequal exchange of environmental pollution and
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value added may provide not only the basis for determining each province’s responsibility for pollution control but also
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a model for other emerging economies.
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Using the latest multiregional input-output (MRIO) model and air pollutant emission inventories, this paper built
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consumption-based inventories of air pollution emissions and value added by tracking air pollution and contribution to
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value added along the entire intra- and inter-regional supply chain in China. Moreover, a regional environmental
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inequality (REI) index was developed to represent the relative degree of inequality between a pair of provinces by
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employing net transfers of emissions and value added associated with inter-provincial trade, which is different from
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other inequality indices such as the pollution-wealth or emissions-wealth ratio29, 32. These indices merely displayed the
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mismatch of some country’s economic gains and emissions when trading with other countries. Additionally, a measure
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called atmospheric pollutant equivalents (APE) was introduced to comprehensively represent the severity of air
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pollution. The details of the MRIO model, emission inventories, REI index and APE are presented in the Materials and
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Methods section and Supporting Information (SI). It is important to note that the focus of this study is the transfer of air
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pollutant emissions and economic gain associated with inter-regional exchange of goods and services within China.
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Emissions and value added embodied in international exports are excluded in our analysis. Additionally,
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production-based accounting in this study refers to all emissions and value added associated with the production of
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goods and services within a region, whereas consumption-based accounting refers to all emissions and value added
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(also referred as embodied or virtual emissions or value added) associated with the production along the entire supply
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chain across regions to meet final consumption in a region.
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2. Materials and Methods
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2.1 MRIO Analysis
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An input-output model is a quantitative economic approach for analysing flows of goods and services between
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economic sectors of a region or country based on input-output tables. The advantage of using an input-output model is
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its ability to capture the direct and indirect (supply chain) effects of final consumption of goods and service in a country
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or region captured through the Leontief inverse matrix44, 45, which captures the infinite round by round production
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effects triggered by final demand. MRIO to further track economic flows between sectors and consumers of different
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regions and thus is able to characterize the supply chain relationships between regions and between economic sectors46.
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The environmentally extended MRIO approach can reveal resource consumption and emissions in other regions caused
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by the consumption of a focal region47. MRIO analysis has been widely applied to international and inter-regional
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transfers of carbon dioxide48, 49, water50, 51, atmosphere pollution22, 23, 52 and public health impacts41-43.
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Here, there are n sectors and m regions. r and s represent exporting and importing regions, i and j represent exporting
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and importing sectors. In this paper, matrices are indicated by italicized capital letters; vectors are denoted by bold, 3
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italicized lower case letters. In addition, scalars are presented by italicized lower case letters. Here, x is a mn×1 vector
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r with its element xi , representing the output of sector i in region r due to domestic consumption; y is a mn×1 vector
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rs with its element yi representing the products of sector i from region r consumed finally in region s. A is a mn×mn
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matrix with its element aijrs , the direct consumption coefficient, representing the requirement from sector i in region r to
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produce per unit output for sector j in region s. Note that we focus only on the transfer of air pollution and economic
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benefits within China and international export is not considered in this paper. The horizontal accounting balance of the
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monetary MRIO table (SI Table S1) can be written as following,
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x = ( I − A)−1 × y
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(1)
−1 Here, (I − A) is the Leontief inverse matrix, the element of which represents the direct and indirect consumption
of products of sector i in region r needed by sector j in region s to make a unit of final product. Let mn×1 vectors f = ( fi r ) and d = (dir ) refer to sectoral air pollution emissions intensity (SO2, NOx and PM)
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r r r r r r and value added coefficient for each region, respectively. The respective elements f i = ki xi and d i = vi xi
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r r represent the air pollutant emissions and value added per unit of total output, where ki and vi represent air pollutant
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emissions and value added of sector i in region r. Here, the notation ^ indicates the diagonalization of corresponding
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column vectors.
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s r Let yˆ and yˆ refer to the diagonal matrixes with the corresponding sectoral products consumption for region s
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and r (r≠s), but zeroes for all other regions, respectively; let fˆ r and fˆ s represent the diagonal matrixes with
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corresponding sectoral air pollution emissions intensity of region s and r (r≠s), but zeroes for all other regions. Then
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we have following equations,
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E sr = fˆ r ( I − A) −1 yˆ s
(2)
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E rs = fˆ s ( I − A) −1 yˆ r
(3)
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EN = E rs − E sr
(4)
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Here, the matrix E sr refers to the emissions of region r induced by the consumption of region s, that is,
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trade-embodied emissions flow/transfer from region s to r; and the matrix E rs refers to the emissions in region s
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induced by the consumption of region r, that is, trade-embodied emissions flow/transfer from region r to s. The matrix
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EN refers to the net flows of emissions between region r and s. Note that there are both positive and negative value in
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EN. The positive value means outflows from region r to s, and negative value exactly means inflows from r to s, that is,
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outflows from s to r. Here, EN is defined as the matrix with all positive value of emissions flows among regions for
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following calculation of REI index.
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Similarly, let dˆ r and dˆ s represent the diagonal matrixes with corresponding value added coefficients of region s and r (r≠s), but zeroes for all other regions. Then we have following equations,
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V sr = dˆ r ( I − A) −1 yˆ s
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V rs = dˆ s ( I − A) −1 yˆ r
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VN = V rs − V sr
(5)
(6)
(7)
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Here, matrix V sr refers to the value added of region r induced by the consumption of region s, that is,
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trade-embodied value added flow/transfer from region s to r; and matrix V rs refers to the value added in region s
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induced by the consumption of region r. that is, trade-embodied value added flow/transfer from region r to s; matrix VN
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refers to the net flows of value added between region r and s. Note that there are both positive and negative value in VN.
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2.2 Regional Environmental Inequality Index
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We employ the REI index to evaluate unequal transfers between Atmospheric Pollutant Equivalents (APE) emissions
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and value added associated with inter-provincial trade. Here, e rs and v rs are the corresponding elements in matrices
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EN and VN, respectively; v rs
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Assuming there is ∀Bm×m with its element b, then we normalize all elements of B to range between 0 and 1 using following general equation:
f (b ) =
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is the absolute value of v rs .
Here,
b − bmin bmax − bmin
(8)
bmax and bmin represent the maximum and minimum values of b, respectively. Therefore, we can obtain the
matrix of REI index,
Q = (q rs )m×m , whose element q rs can be calculated as follows: e rs f ( rs ) , if e rs > 0 and v rs > 0 q rs = v f (e rs ) + f ( v rs ) + 1 , if e rs > 0 and v rs < 0
(9)
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Because e rs >0, which is stated in the definition of EN , there are two types of relationship between region r and
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region s. When e rs >0 and v rs >0, both APE and value added outsourcing occur from region r to region s, and the
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elements in matrix e rs v rs are normalized to range between 0 and 1. When region r outsources more APE and less
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value added to region s, the value of q will be greater (close to 1). When e rs >0 and v rs
