Structural Changes in Provincial Emission Transfers within China

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Policy Analysis

The structural changes in provincial emission transfers within China Chen Pan, Glen Peters, Robbie Andrew, Jan Ivar Korsbakken, Shantong Li, Peng Zhou, and Dequn Zhou Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03424 • Publication Date (Web): 19 Oct 2018 Downloaded from http://pubs.acs.org on October 20, 2018

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Environmental Science & Technology

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The structural changes in provincial emission

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transfers within China

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Chen Pan†,1, Glen P. Peters‡, Robbie M. Andrew‡, Jan Ivar Korsbakken‡, Shantong Li§, Peng

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Zhou†,#, Dequn Zhou†,* †

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College of Economics and Management, Nanjing University of Aeronautics and Astronautics,

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29 Jiangjun Avenue, Nanjing 211106, China ‡

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CICERO Center for International Climate Research, Pb 1129 Blindern, 0318 Oslo, Norway §

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Development Research Center of the State Council, 225 Chaoyangmennei Street, Beijing

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100010, China #

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School of Economics and Management, China University of Petroleum, 66 Changjiang West

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Road, Qingdao 266580, China

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Corresponding authors: Chen Pan (29 Jiangjun Avenue, Nanjing 211106, China, [email protected]) Dequn Zhou (29 Jiangjun Avenue, Nanjing 211106, China, [email protected]) 1 ACS Paragon Plus Environment


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Abstract

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Chinese provinces ultimately implement China’s national climate policies. In the 2000s, there

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were unbalanced emission transfers – emissions produced in one region but consumed in other

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regions – between China’s well- and less-developed regions, mainly related to demand in the

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well-developed eastern provinces. In the past decade, the plateau in China’s exported emissions

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and changes in its industrial structure suggest features of the provincial emission transfers could

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have changed. We construct a Chinese provincial multi-year, multi-sector model (multi-regional

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input–output model) to investigate the structural changes in China’s provincial emission transfers

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from 2002 to 2012. We find that from 2007 to 2012, the international-export-associated emission

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transfers driven by eastern provinces decreased by 17% after the 262% increase in 2002-07,

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while investment dominated 99% of the increase in emission transfers. At the sector level,

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emissions caused by construction in the east and west, and technology-intensive manufacturing

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in the center that largely related to investment were the major components of the increasing

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emission transfers in 2007-12, accounting for 23%, 21%, and 10% of the increase respectively.

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Our findings indicate that attention should be given to committed emissions from investment,

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and interaction between non-uniform provincial climate policies and economic relationships

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between provinces.

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TOC Art

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1 Introduction

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The Paris Agreement calls to hold the increase in the global average temperature to “well

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below 2 degrees” above pre-industrial levels, and importantly, requires all countries to contribute

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to the global mitigation burden1. As the world's leading emitter of CO2 (28% of the world's total

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in 20162), China pledged to “achieve the peaking of carbon dioxide emissions around 2030 and

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make best efforts to peak early” in its Intended Nationally Determined Contribution (INDC)3. To

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achieve these goals, a series of policies were proposed in China’s INDC, in which regional and

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sectoral measures played important roles. As implementers of these measures, Chinese provinces

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show large variations in development stages, as well as CO2 emissions. In 2015, the per capita

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GDP of the richest province–Tianjin–was 17 thousand US dollars, four times larger than that of

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the poorest province–Gansu. The share of the tertiary sector in value-added, seen as an important

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indicator of development, was 80% in Beijing, comparable to that of the United States (79% in

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2015), but only 39% in Guangxi, among the lowest in the world4, 5.

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The variations in the development stages of Chinese provinces have led to significant

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variations in CO2 emissions from the production within the provinces (production-based

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emissions). Part of the production-based emissions were from the production of goods and

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services consumed in other provinces, leading to consumption-based emissions, which equal

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production-based emissions minus exported emissions and plus imported emissions, both

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international and inter-provincial. The emission transfers – emissions produced in one region but

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embodied in products consumed in another region, also called emissions embodied in trade or

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spatial spillovers, are the bridge between the production- and consumption-based emissions.

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Many previous studies on international cases find that emission transfers via international trade

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have contributed to the stabilization of production-based emissions in developed countries, but 4 ACS Paragon Plus Environment

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caused a rapid growth in production-based emissions in developing countries that produced

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goods and services exported to developed countries6-8. This led to concerns about emission

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transfers via trade between developed and developing countries and “carbon leakage”9, as well as

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intensive discussions on the interaction between international emission transfers and climate

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policies10-14. Considering the large variations between Chinese provinces, some studies focused

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on China show that, similar to the international pattern, there were significant amounts of

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emission transfers between Chinese provinces in the 2000s15-19. The developed regions of China

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had higher consumption-based emissions than production-based emissions, while situation for

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the developing regions was opposite in both 1997 and 200715,

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international exports from the developed coastal regions induced emissions from the

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less-developed inland regions21. Factors related to inter-regional trade that have influenced

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Chinese regional emissions included regional heterogeneity, inter-regional spillover, position and

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participation degree in supply chains, as well as variances in regional consumer behaviors16, 21-23.

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These findings led to discussions about the equity and effectiveness of assigning mitigation

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targets among the well- and less-developed Chinese regions15,

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approaches of emission mitigation via inter-regional trade24, 25.

20.

Between 2002 and 2007,

21, 22,

as well as potential

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In the past decade, China has experienced significant changes in its economy and emissions.

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First, after the changes in 2002–2007, China’s industrial structure has continued to change:

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Changes in industrial structure since 2007 could have contributed to the stabilization or even

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peak of Chinese emissions26; Spatially, the share of total output of the eastern provinces

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decreased, especially the mining and manufacturing sectors, while those of the western and

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central provinces increased, of which changes in the technology-intensive manufacturing sectors

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in the center and the mining and construction sectors in the west were the most significant 5 ACS Paragon Plus Environment


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(Figure S1). Second, from 2007 to 2012 the ratio of inter-provincial emission transfers to China’s

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total emissions grew, though not as fast as from 2002 to 2007 (Table S1). Third, studies have

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shown that since the late 2000s, emissions embodied in Chinese exports have plateaued27, 28,

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which had a potential influence on the pattern of provincial emission transfers. These changes

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suggest Chinese provincial emission transfers could have changed since 2007. In the current

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economic situation and with the pressure of global climate policies, it is necessary to investigate

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the features of Chinese provincial emission transfers after 2007, and discuss its policy

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implications within a longer time period.

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The multi-regional input–output (MRIO) model29 has been widely used to explore emission

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transfers via trade30, both international6,

7, 31

and inter-regional15,

20, 21, 25, 32.

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single-regional input–output (SRIO) model, MRIO can track the emission transfers via complex

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economic linkages between regions and sectors with trade between regions determined

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endogenously8. However, MRIO has a higher requirement of data. Therefore, due to lack of

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official statistics of inter-provincial trade, studies on China using MRIO have either covered

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shorter time periods21, 22, 32, or taken MRIO tables (MRIOTs) from inconsistent data sources16.

Comparing with

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We construct constant-price MRIOTs of Chinese provinces for the years 2002, 2007, and 2012

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using a consistent method for each year to investigate the structural changes in the emission

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transfers between Chinese provinces from 2002 to 2012. We also estimate CO2 emissions from

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consumption of fossil fuels and production of cement of Chinese province at the sector level.

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Based on these two datasets, environmentally extended MRIO (EEMRIO) analysis is performed

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to estimate the emission transfers between provinces over the period 2002–2012, and the changes

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are decomposed into final demands and transferring paths. Finally, we put our study in the

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context of others to discuss the policy implications. 6 ACS Paragon Plus Environment

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2 Materials and Methods The detailed materials and methods are discussed in the Supporting Information (SI; Text S1), but here we give a summary. 2.1 Environmentally extended multiregional input–output analysis

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We adopt the EEMRIO analysis in this study, which determines the environmental

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repercussions stemming from the economic activities of the regions (provinces in this study). It

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has been widely used to track the emission transfers between regions15, 30, 32-37. Our focus is on

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Chinese emissions, so we exclude from our analysis emissions embodied in imports from other

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countries. The EEMRIO is explained mathematically as 𝒒 = 𝒇(𝑰 ― 𝑨) ―1𝒚 = 𝒇𝑳𝒚, where 𝒒

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represents the emissions contributed by each sector of each region for the production of final

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demand (𝒚); 𝒇 is the vector of sector-level emission intensities of the regions (𝒇𝑠); (𝑰 ― 𝑨) ―1

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is the Leontief inverse (𝑳), with 𝑨 representing the inter-industry requirement matrix showing

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the economic linkages between the sectors of the regions, composed of the inter-industry

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requirement matrices of and between the regions (𝑨𝑠,𝑟), and 𝑰 representing the identity matrix

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with the same size as 𝑨; 𝒚 is the column vector of final demand and can be consumption,

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investment, export, or total final demand of any regions (𝒚 ∗ ,𝑟);. Given that the classifications of

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the MRIOTs were revised throughout the years (though the numbers of sectors are the same), we

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harmonize China’s MRIOTs into 37 sectors (see Table S5 for the sector list).

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Based on the basic EEMRIO, emission transfers are calculated with 𝒒𝑠,𝑟 = 𝒇𝑠𝑳𝑠, ∗ 𝒚 ∗ ,𝑟𝜹 (𝑠 ≠

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𝑟), where 𝑠 and 𝑟 are the indices for province 𝑠 and 𝑟, while ‘*’ represents all provinces. 𝜹

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is a matrix for summation obtained from 𝜹 = 𝒆 ⊗ 𝑰, where 𝒆 represents an column vector of

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ones with 30 elements (number of provinces); 𝑰 is an 37-by-37 (number of sectors) identity

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matrix; and ⊗ refers to the Kronecker product. Thus the production-based emissions can be 7 ACS Paragon Plus Environment


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obtained by 𝒒𝒑𝒃𝑠 = 𝒒𝑠,𝑠 + ∑𝑟,𝑟 ≠ 𝑠𝒒𝑠,𝑟, and the consumption-based emissions can be obtained by

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𝒒𝒄𝒃𝑟 = 𝒒𝑟,𝑟 + ∑𝑠,𝑠 ≠ 𝑟𝒒𝑠,𝑟.

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2.2 Preparation of Chinese Provincial MRIOTs

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The Chinese provincial multiregional input–output tables (MRIOTs) of 2002, 2007 and 2012

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are taken from the Chinese provincial input-output database compiled by the Development

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Research Center of the State Council of China38, 39. This database uses the “bottom-up” method

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and covers 30 provinces of the mainland China in 2002 and 2007 (except Tibet), and 31

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provinces in 2012 with Tibet included. Since there is no official energy consumption data for

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Tibet, and the CO2 emissions of Tibet are very small40, we exclude Tibet from our analysis. The

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features of our MRIOTs comparing with the previous studies and the detailed method for

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preparing the MRIOTs are shown in the SI (Text S1.2). The MRIOTs in constant price are

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provided in the SI (Table S13-S15).

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To prepare the MRIOTs, we first estimate the detailed trade flows between the sectors and the

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provinces and split the provincial input–output tables (IOTs) into local, inter-provincial and

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international imports, by assuming that for each intermediate and final demand sector (excluding

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inter-provincial and international exports), the inter-provincial and international imports account

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for the same proportion as the overall share of imports (both inter-provincial and international) in

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total local use (Text S1.2.2).

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Then, the current-price MRIOTs are converted into constant price using the widely adopted

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double-deflation method41, 42. The deflators are obtained following Pan, et al. (2017) 27, and we

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assume that the deflators of the provinces are the same as the national ones of the same year due

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to data limitation (see details in Text S1.2.3). The double-deflation method is adopted based on

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three considerations. First, this method requires less data for deflating, which suits well China’s 8 ACS Paragon Plus Environment

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case of lacking detailed deflators for intermediate use, final use, and value added. Second, by

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using double-deflation, the MRIOTs do not need to be rebalanced, so that additional

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uncertainties from rebalancing will be largely avoided. Third, the major sensitivity issue of

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double-deflation here is that it obtains deflated value added as residuals. However, since the

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value-added data are not used in this study, we see no critical reason to reduce the sensitivity of

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value added by involving additional uncertainties from rebalancing.

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Finally, the deflated MRIOTs are adjusted for the reform in China’s electricity system

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launched in 200243, which separated power plants and grids into two systems and has been found

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to have significant influences on the results27. We adopt the following rules to do the adjustment.

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For each province, (1) if the direct input coefficient of electricity to electricity sector itself

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(denoted as 𝑎𝑘𝑘) increase in 2002-07 and remain at that level during the next period 2007-12, or

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if the values of 𝑎𝑘𝑘 in 2002 and 2007 are similar, while increase in the next period, the values of

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2012 are adjusted; (2) if the 𝑎𝑘𝑘 increases in both period, or if it increases in the first period

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while decreases in the second period, the values of 2007 and 2012 are adjusted; (3) otherwise, we

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keep the initial values (see detailed methods in Text S1.2.4).

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2.3 Estimation of CO2 emissions

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2.3.1 Fossil-fuel consumption and its CO2 emissions

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To estimate the CO2 emissions from the consumption of fossil fuels at the sector level, we

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need the Energy Balance Tables (EBTs) and the final energy consumption of industrial sectors

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(both in energy units), and then apply standard emission factors. We provide a detailed

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description of the method and discuss the uncertainties in the estimation in the SI (Text S1.1.1).

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Due to data limitations, we estimate the detailed fossil-fuel consumption of the provinces.

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Energy consumption data for the industrial sectors is taken from Provincial Statistical Yearbooks 9 ACS Paragon Plus Environment


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(PSYs)44, which is only available for some provinces. The statistical standards of the data are not

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consistent across the provinces or the years in sector classification, energy type, energy

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consumption stages (consumption vs. final consumption), unit (physical vs. energy), and

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coverage (industrial enterprises above designated size vs. all industrial enterprises).

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(1) For provinces with data on individual energy types, we first convert the energy

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consumption data from PSYs into final energy consumption in energy units, using the ratios

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found in the national energy consumption data45. The converted data are then constrained by the

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total amount in the provincial EBTs.

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(2) For provinces without any data from PSYs, we use energy consumption of the industrial

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sectors for provinces in 2008 from China Economic Census Yearbook (CECY) 2008 for the

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estimation46. We follow previous studies32,

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distribution of energy consumption among the industrial sectors in the years with input-output

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data (2002, 2007, and 2012) is the same as that of 2008, and allocate the total industrial energy

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consumption to the industrial sectors. Again, we use the national data to convert the estimated

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energy consumption to final energy consumption in energy units.

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in assuming that for these provinces that the

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(3) For provinces with only total consumption of energy or total coal, we use the RAS method

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to estimate the final energy consumption of individual energy types, with the estimation of

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section (2) as the initial values.

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Finally, the data estimated above are merged with the order of precedence of section (1), then section (3), and lastly section (2).

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We then follow our previous method27 to estimate the sectoral CO2 emissions from fossil-fuel

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consumption of Chinese provinces but with two differences. The first difference is that instead of

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deducting the non-energy use of coal and coal products from the petroleum and chemicals 10 ACS Paragon Plus Environment

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sectors, we deduct it from all industrial sectors. The second difference is that the loss of coal is

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not added to the coal-mining sector as what we did in our previous method. These changes are

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small, which will not lead to substantive changes in the results (see Text S1.1.1.2 in the SI for

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details).

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The emissions cover 27 types of fossil fuels (17 types for 2002 and 2007) and 44 sectors. The

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oxidation rates and the emission factors are taken from China National Greenhouse Gas

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Inventory 2005 (CNGHG 2005)48. The IPCC tier-2 method49 is adopted to calculate the sectoral

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CO2 emissions from the final energy consumption. An IPCC tier-3 method is adopted for coal to

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obtain the average emission factors and oxidation rates for the sectors and coal types.

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2.3.2 CO2 emissions from cement production

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We adopt the IPCC tier-2 method50 to estimate the CO2 emissions from the process of cement

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production. The clinker production data of the provinces are taken or estimated from the China

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Cement Almanacs (CCAs) and the China Cement Research Institute (see details in Table S6).

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The regional emission factors of clinker production (for the north, northeast, east, center-south,

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southwest, and northwest) and the correction factor for cement kiln dust (CKD) are taken from

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CNGHG 200548.

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3 Results

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3.1 Production- and consumption-based CO2 emissions of Chinese provinces

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Significant changes have occurred in the regional distribution of production- and

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consumption-based emissions from 2002 to 2012 (Figure 1), with the main changes described

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here. Provinces with the highest production-based emissions were mostly located in the east, but

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some of them had decreasing growth rates from 2007 to 2012. Since 2007, emissions of several

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eastern provinces (Beijing, Shandong, Zhejiang) have flattened out, and the emissions of 11 ACS Paragon Plus Environment


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Shanghai even decreased. Consumption-based emissions increased in most eastern provinces, but

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decreased in Shanghai and Zhejiang. In the central provinces, consumption-based emissions

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increased from 2002 to 2012, with almost all the provinces (except for Hunan) becoming net

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provincial emission exporters (emissions exported to exceed emissions imported from other

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provinces) in 2012. For the western provinces, although the absolute amount of their emissions

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was lower, their production- and consumption-based emissions grew strongly from 2002 to 2012,

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especially Inner Mongolia. Among these western provinces, the southwest provinces were

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mostly provincial emission exporters in 2002 and 2007 (Figure S3), but became provincial

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emission importers in 2012 (except for Guizhou). The northwest provinces turned gradually from

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net provincial importers to exporters from 2002 to 2012, and by 2012, all the northwest

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provinces had become net provincial emission exporters. Correlation analysis shows that the

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results are consistent with those in previous studies15, 28, 32 (Table S8, S9).


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Figure 1. Chinese provincial production- and consumption-based emissions and their

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decompositions into each category of final demand. The backgrounds of the panels are colored

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by regions, where the coverages of the regions are also shown in Figure S2 and Table S2. The 13 ACS Paragon Plus Environment


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blue bars are the emissions produced and consumed by the provinces (Local). The orange bars

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are the inter-provincially exported emissions (IP exports). The green bars are the

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inter-provincially imported emissions (IP imports). Within each category, emissions associated

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with consumption (including household direct emissions), investment, and international export

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are distinguished by shades. The blue and orange bars together represent the production-based

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emissions, and the blue and green bars represent the consumption-based emissions (here the

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emissions associated with international exports are counted in the consumption-based emissions

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to reflect the emission transfers for international exports). The map in the right-bottom corner

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shows the net emission transfers of Chinese provinces in 2012.

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3.2 Tracing emission transfers between Chinese provinces

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The emission transfers, which are the bridge between production- and consumption-based

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emissions, were decomposed into origins and destinations, showing the connections between

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provinces that led to the changes described above (Figure 2). The emission transfers grew rapidly

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between 2002 and 2007, of which investment-associated transfers accounted for 52% of the

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growth, followed by 25% from international exports and 23% from consumption. The most

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active emission transfers happened between the eastern provinces that were often associated with

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international exports, as well as investment (Figure S4-S7). While from 2007 to 2012, though

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emission transfers were still increasing, the growth rate was much lower, mainly due to the

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increased emission transfers related with the investment (99% of the increase), particularly in the

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central and western provinces (Figure S5), offset by the reversed changes in emission transfers

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associated with international exports, especially between the eastern provinces (after increasing

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by 152% in 2002-2007, emission transfers between the eastern provinces associated with

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international exports decreased by 19% in 2007-2012; Figure S7). It turned out that the less 14 ACS Paragon Plus Environment

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active transfers within the eastern region from 2007 to 2012 were provincially led by less

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emission outflows from Hebei and Shandong, and less emission inflows to Guangdong and

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Zhejiang. In this period, eastern provinces like Jiangsu and Guangdong, imported more

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emissions from the west and central provinces, partly explaining the increases in the

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production-based emissions of the latter. Perhaps more importantly, the western and central

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provinces also imported more emissions from the eastern (mainly Hebei and Jiangsu), which had

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driven the increases in the consumption-based emissions of the west and center.

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Figure 2. Emission transfers between provinces and regions for the years 2002, 2007 and 2012.

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In each panel, provinces are sorted into and separated by the west, center, east, and northeast

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from the left (bottom) to right (top). The smallest squares represent the emission transfers from

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one province to another (for example, the element in row 3, column 2 is the emission transfers

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from Liaoning to Guangxi), the darker the color, the larger the amount. The minor diagonal

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elements, which refer to the emissions produced and consumed in the provinces themselves, are

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removed. The grey bubbles represent the emission transfers between the four regions, which are

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the sums of the provincial emission transfers within the associated boxes.

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3.3 Tracking Chinese provincial emission transfers along supply chains

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To understand the key changes in Chinese provincial emission transfers, we further decompose

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the major changes in emission transfers into detailed paths at the sector level. One significant

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change in the emission transfers was the change within the eastern region, which was mainly

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related to changes in Hebei, Shandong, Zhejiang, and Guangdong as analyzed above. We focus

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on that particular path in more detail here (Figure 3). It turns out that from 2002 to 2007, the

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manufactures, especially the technology-intensive manufactures, consumed by Guangdong and

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Zhejiang had led the increase in emission transfers within the eastern region, with the emissions

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mainly from steel production in Hebei and electricity generated in Shandong. From 2007 to

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2012, emission transfers within the eastern provinces were less active, mainly due to an amount

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of emission transfers emitted in steel production of Hebei shifted away from, and a decrease in

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emission transfers emitted in electricity generation of Shandong induced by, manufactures

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especially the technology-intensive manufactures consumed in Guangdong and Zhejiang. This

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decrease was further reinforced by a decrease in emission transfers for the construction


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consumed in Zhejiang, and partly offset by an increase in emission transfers for the construction

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consumed in Guangdong.

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Another important change in the emission transfers was the increasing transfers between the

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west and east, as well as those between the center and east. A sector-level decomposition shows

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that the technology-intensive manufactures consumed in these three regions, especially those in

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the eastern provinces, were the key components causing the increases in emission transfers

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between 2002 and 2007, which could have related to China’s accession to the World Trade

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Organization (WTO; Figure 4). From 2007 to 2012, emission transfers induced by the

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technology-intensive manufactures continued to increase, with the most outstanding growth in

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the transfers from the east to the central provinces. During this period, perhaps related to China’s

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actions to deal with the global financial crisis in 2008–2009, the construction sector joined the

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technology-intensive manufacturing sectors becoming an important sector that caused the

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changes in emission transfers, especially for the transfers to the east, and those from the east to

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the west. Consistent with the changes in industrial structures (Figure S1), the emission transfers

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from the center to the construction consumed in the east mainly came from the production of

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non-metal mineral products, of which cement and cement products account for nearly a half

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(calculated with the total output in national input–output table51 due to lack of data at a more

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detailed level of sectors in provincial input–output tables; it might worth mentioning that the

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sector classification of the provincial input–output tables should be detailed in the future so that

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the emission transfers along the supply chains of large-scale consumption, like construction,

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could be better tracked), while the largest component of the emissions transfers from the western

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to the construction consumed by the east came from electricity generation.



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Figure 3. Decomposition of emission transfers within the east region at the sector level. In each

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panel, the horizontal axis represents the consumption-based emissions, that is, the emissions 18 ACS Paragon Plus Environment

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embodied in a certain category of products used by the destination region/province. Each bar of

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the consumption-based emissions is further decomposed into detailed products along the vertical

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axis, showing which sector of the origin region/province that has actually emitted the emissions

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(the top five sectors in each panel). Each color represents a product sector. “Agri”, “Min”,

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“Manuf-L”, “Manuf-C”, “Manuf-T”, “Util”, “Constr”, and “Serv” represent for Agriculture,

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Mining, Labor-intensive manufacturing, Capital-intensive manufacturing, Technology-intensive

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manufacturing, Utilities, Construction, and Services respectively. The major products of the

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sectors (vertical) and their abbreviations are shown in Table S7.



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Figure 4. Decomposition of emission transfers between the east and the west, central regions at

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the sector level. The figure is in the same design as Figure 3. The abbreviations for names of the


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categories of products (horizontal) are the same as those of Figure 3. The major products of the

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sectors (vertical) and their abbreviations are shown in Table S7.

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4 Discussion

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From 2002 to 2007, with China’s accession to the WTO, China’s provincial emission transfers

324

increased, which was coastal-oriented15,

52.

325

provinces induced by international exports were the most active, and meanwhile, the emission

326

transfers from the central and western provinces to the eastern coastal provinces were high.

327

About 50% of the increase in provincial emission transfers in this period was associated with

328

investments (the increase), followed by considerable contributions from international exports and

329

consumption. During this period, the emission transfers were mainly induced by manufactures,

330

especially technology-intensive products. After 2007, as emissions embodied in Chinese

331

international exports plateaued and even decreased27, 28, 53, the emission transfers within China

332

caused by international exports, especially those by the east (decreased by 17% after the 262%

333

increase in 2002-07) decreased, and the continued growth in emission transfers became

334

dominated by investment between 2007 and 2012 (99%). As the emission transfers within the

335

eastern region became less active, the emission transfers both into and out of the central and

336

western regions increased, mainly due to the rapid growth in construction in the eastern and

337

western provinces (23% and 21% of the increase), and technology-intensive manufacturing in

338

the central provinces (10% of the increase) associated with investments.

The emission transfers between Chinese eastern

339

Based on our findings, we explore factors that relate to the investment-driven emission

340

transfers between Chinese provinces and discuss the policy implications in general. There are

341

two likely candidates that could have driven the changes.



Page 22 of 29

342

First, investment led by policies could have played a role in the structural changes in emission

343

transfers. On the demand side, the investment-oriented measures of China to deal with the 2008–

344

09 global financial crisis was likely to have contributed to the dominant role of investment in the

345

emission transfers, reinforced by China’s decreasing international exports associated emissions.

346

On the supply side, the increase in emission outflows from the central provinces to the east

347

generated in cement production between 2007 and 2012 could have been related to the “Rise of

348

the Central Region” strategy started in 2006, which would have stimulated the increase in

349

cement production in the center (see correlation analysis in Text S2). And the increase in

350

emission outflows from the western provinces to the east emitted in electricity generation could

351

partly be explained by the “West-East Power Transmission Project” started in the early 2000s –

352

the proportion of emissions embodied in the transmitted electricity via this project to the

353

emission transfers from the west to the east emitted in electricity generation increased from 18%

354

in 2002 to 28% in 2012 (Table S11).

355

Second, investment driven by production cost could have contributed to the changes in the

356

structure of emission transfers. Good evidence for this is the increase in emission transfers from

357

the east to the center. From 2007 to 2012, with 43% of the new fixed assets invested for

358

manufacturing in the central region5, its manufacturing, especially technology-intensive

359

manufacturing, underwent a rapid increase. This increase could be explained by rising costs in

360

the east and lower costs in the central. (a) The labor cost in the eastern region had been higher

361

than the center and increased (Table S12). (b) Increase in the price of real estate associated with

362

rising land cost, and rise in service price had increased the living and social costs in the eastern

363

provinces54, 55. (c) Regulations of environmental protection in the eastern provinces has been

364

strengthening, while those in the central and western provinces were less strict. (d) The largely 22 ACS Paragon Plus Environment

Page 23 of 29


365

improved infrastructure has lowered the cost of transport and communication in the central and

366

western regions, and thus lowered trade cost with these regions.

367

These potential forces driving the changes in investment-associated emission transfers suggest

368

that (1) attention should be given to the potential environmental and climatic influences of the

369

economic policies, and conversely, how non-uniform provincial climate policies might interact

370

with the economic relationships between provinces; (2) cost of production can be used to guide

371

the shifts of industries and emissions transfers via supply chains, e.g., environmental access

372

regulations, carbon tax, and carbon trading; (3) if the shift of production will potentially cause

373

“carbon leakage6”, such as the shift from Chinese east to the center, policy levers based on

374

adjusted emission accounting13, 14 and technology transfer could be used to offset the potential

375

leakages.

376

In the future, given that the export-oriented emission transfers to the eastern provinces have

377

changed, and that the investment-associated emission transfers with the central and western

378

provinces have increased, the central and western provinces will potentially play a significant

379

role in the mitigation of China’s CO2 emissions. Here we analyze the potential changes in

380

emissions and emission transfers, and suggest some measures from the policy side.

381

For the central provinces, as manufacturing in these provinces has been growing, and the

382

Thirteenth Five-Year (2016–2020) Plan for the Rise of the Central Region further emphasized

383

promoting the central region to be a center for advanced manufacturing56, manufacturing in the

384

central region, as well as new investments in manufacturing, are expected to continue to grow.

385

The major concern would be the “committed emissions57, 58” associated with these investments:

386

the committed growth in manufacturing will cause a higher demand for energy, particularly

387

electricity, which would induce more emissions and emission transfers. Meanwhile, with the 23 ACS Paragon Plus Environment


Page 24 of 29

388

growth of manufacturing, the income in the central region is expected to rise, which would lead

389

to an increase in its consumption emissions. The committed emissions and a potential increase in

390

consumption-based emissions suggest that whether the central region will in future just be a

391

replacement for the east as a major CO2 emitter is highly determined by the decarbonization of

392

the central provinces, not only in its own production, but also in its supply chains. There are

393

several possible measures. First, decreasing CO2 intensity by improving production technology,

394

e.g., transferring advanced technology from the eastern provinces to the center. Second,

395

decreasing emissions from the origins, and transferring the decrease via the supply chains, e.g.,

396

replacing thermal power with renewable energy. Third, the current carbon trading system could

397

be expanded to more industries to drive mitigation by enterprises.

398

For the western provinces, the situations are similar for the northwest and southwest, but

399

potentially playing different roles. In the past few years, both the southwestern and northwestern

400

provinces had a large amount of investments in transport infrastructure. This will be further

401

reinforced by the Belt and Road Initiative, where the northwest will be an important section of

402

the “Belt”, linking China with the countries bordering China to the northwest, and the southwest

403

will be the link between the “Belt” and the “Road”. By strengthening connections between the

404

western provinces as well as between the west and other regions, combined with the abundant

405

resources of the west, both labor and natural59, the investments to transport infrastructure would,

406

on the one hand, induce committed emissions from transportation, and on the other hand increase

407

the consumption-based emissions and emission transfers of the western provinces. In the long

408

term, as the transport infrastructure in the west is expected to continue to grow, measures may

409

need to be taken to avoid the potential increase in emissions and emission transfers. First, as road

410

transport accounted for two-thirds of the world’s committed transport CO2 emissions58, replacing 24 ACS Paragon Plus Environment

Page 25 of 29


411

the fueled vehicles with electric vehicles would be the first step to offset the committed

412

emissions from transportation. Second, a high proportion of investments in the northwest were

413

for energy projects in recent years, owing to its abundant wind and solar resources. Improving

414

the power transmission networks and energy storage systems will help the northwest to reduce

415

CO2 emissions not only within the northwestern provinces, but also in the supply chains.

416

Acknowledgements

417

We thank Jianwu He of Development Research Center of the State Council, China for

418

comments on the discussions. C.P. (in part), G.P.P., R.M.A., and J.I.K., and S.L. (in part) were

419

funded by the Research Council of Norway (no. 235523), including a Visiting Researcher Grant

420

to C.P. C.P. (in part) and S.L. (in part) were funded by the National Natural Science Foundation

421

of China (no. 71733003). C.P. (in part), D.Z. (in part), and P.Z. were funded by the National

422

Natural Science Foundation of China (no. 71573121, 71625005, 71573119, 71834003). C.P. (in

423

part) and D.Z. (in part) were funded by the Fundamental Research Funds for the Central

424

Universities (no. NP2017107). The authors declare no competing financial interest.

425

Supporting Information Available. Chinese provincial MRIOTs in constant price (Table

426

S13-S15); Detailed materials and methods (Text S1, Table S3, S4, S6); Extended results (Figure

427

S1, S3–S7, Table S1); Supplemented analysis (Text S2, Figure S8, Table S8–S12); Region and

428

sector classifications (Figure S2, Table S2, S5, S7). This information is available free of charge

429

via the Internet at http://pubs.acs.org.

430

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Structural Changes in Provincial Emission Transfers within China

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