Spatial-temporal analysis of carbon emissions embodied in interprovincial trade and optimization strategies: A case study of Hebei, China

Accepted Manuscript Spatial-temporal analysis of carbon emissions embodied in interprovincial trade and optimization strategies: A case study of Hebei, China Xiaojia Fan, Sanmang Wu, Shantong Li PII:

S0360-5442(19)31300-3

DOI:

https://doi.org/10.1016/j.energy.2019.06.168

Reference:

EGY 15651

To appear in:

Energy

Received Date: 13 March 2019 Revised Date:

30 May 2019

Accepted Date: 26 June 2019

Please cite this article as: Fan X, Wu S, Li S, Spatial-temporal analysis of carbon emissions embodied in interprovincial trade and optimization strategies: A case study of Hebei, China, Energy (2019), doi: https://doi.org/10.1016/j.energy.2019.06.168. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Essential title page information •Title Spatial-Temporal analysis of Carbon Emissions Embodied in Interprovincial Trade

• Authors and affiliations Xiaojia Fan1,2, Sanmang Wu1,2*, Shantong Li3

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and Optimization strategies: a case study of Hebei, China

1. School of Economics and Management, China University of Geosciences, Beijing, 100083, People’s Republic of China

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2. Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources of the People's Republic of China, Beijing, 100083,

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People’s Republic of China

3. Development Research Center of State Council, Beijing 100010, People’s Republic of China *E-mail: [email protected]

• Corresponding author

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Sanmang Wu

School of Economics and Management

China University of Geosciences, Beijing

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No. 29 Xueyuan Road, Haidian District Beijing 100083

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P.R. China

E-mail: [email protected] Tel: 86-10-82322078

Fax: 86-10-82322078

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Spatial-Temporal analysis of Carbon Emissions Embodied in Interprovincial Trade and Optimization strategies: a case study of Hebei, China

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Abstract: Trade flows between provinces have led to the transfer of embodied carbon emissions. Therefore, when formulating carbon emission reduction policies for a province, it’s necessary to consider the carbon emissions implied in trade. In this study, we established an interprovincial carbon flow analysis framework based on multi-regional input-output model, and we used China’s

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1997, 2002, 2007, and 2012 input-output data to make an empirical research of Hebei Province. The findings are as follows. Firstly, from 1997 to 2012, the embodied carbon emissions’ net

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outflow of Hebei increased by 244.26 Mt, the number of the provinces that net inflowed carbon from Hebei increased from 18 to 22, and they extended from eastern coastal provinces and southern China to most parts of the country. Secondly, technological level and trade demand are the main factors affecting carbon emissions’ net outflow, contributing -108.45Mt and 352.71Mt, respectively. On this basis, we developed a relationship model of the net outflow of carbon

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emission and commodity value to optimize the industrial development. Different from previous studies, our research has penetrated into every industry and every related province. We not only calculated the commodity transfer and embodied carbon transfer between Hebei Province and

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other provinces, and balanced the advantages and disadvantages of trade between key industries and provinces, then gave specific solutions and optimization measures, which has stronger

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practical meaning and guiding significance. Keywords: Embodied Carbon Emissions; Multiregional Input-Output Model; Carbon Transfer; Interprovincial Trade

1. Introduction

In recent years, global warming and other climate change problems caused by excessive greenhouse gas emissions have become increasingly serious[1,2]

and become the focus of

international attention. However, surfeit CO2 emissions are the arch-criminal to the enhanced greenhouse effect[3]. Therefore, how to reduce CO2 emissions is an urgent problem to deal with climate change. In 2015, 195 countries signed the Paris Agreement of the United Nations

ACCEPTED MANUSCRIPT (UN)Framework Convention on Climate Change, under which they agreed “…to strengthen the global response to the threat of climate change, …including by holding the increase in the global average temperature to well below 2

above pre-industrial levels in the long term ”[4]. From

Copenhagen Accord to Paris Agreement, from "showdown" mandatory reduction to "national

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autonomous contribution" reduction, the international community has reached a consensus on carbon emission reduction to a certain extent[4,5]. Nevertheless, there are great divergences among different countries on the division of carbon emission responsibilities, especially on the attribution of embodied carbon emissions in international trade[6–8]. Many scholars have done

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corresponding researches based on the implicit carbon and its transfer in international trade[9–13]. Some authors have argued that most of the implicit carbon emissions in international trade flow

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from developing countries to developed countries. The former bears a lot of carbon costs and environmental costs for the latter, which is very unfavorable for developing countries to reduce carbon emissions[14–16]. In particular, China, as the world's largest developing country and energy consumer[17], is also the largest carbon emitter and carbon exporter[18]. Academics hold that carbon emissions implied in export trade are an important reason for China's excessive carbon

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emissions. To reduce carbon emissions, it is necessary for China to consider the issue of carbon transfer implied in foreign trade[18–20].

Although it is important to study carbon transfer from the perspective of international trade,

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for a big country like China, not only international trade is growing, but domestic inter-provincial trade is increasing. Thus, the transfer of carbon emissions caused by inter-provincial trade is also a

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crucial factor to be considered in formulating emission reduction policies[21]. In recent years, a large number of scholars have studied the problem of implied carbon transfer between regions in China[22–24]. These studies mainly divide China into several regions and study the transfer of embodied carbon emissions between regions[21,25,26], such as the flow from the central and western regions to the southeastern coast, from the underdeveloped regions to the developed regions[23,27], or from the perspective of producers and consumers[28,29]. And a few have begun to study the implied carbon problem at the urban level[30,31]. However, there are few researches on carbon transfer in specific provinces. The previous researches cannot clearly understand the flow of implied carbon in each province, and the conclusions are not be applicable to a specific province. Therefore, it is very meaningful to study the embodied carbon transfer in trade between

ACCEPTED MANUSCRIPT a given province and other provinces. Taking Hebei Province as a case study, it is considered that it’s a major economic province and a major carbon emission province. Since the reform and opening up, Hebei’s economy has been developing rapidly. Meanwhile, its industrial development pattern is dominated by heavy

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industry. For example, the output of crude steel in Hebei Province was 10.56 million tons in 1997 and increased to 192.6 million tons in 2016, ranking first in the country[32].At the same time, emissions of greenhouse gases such as CO2 have a steep growth (Fig. 1). In 2014, Hebei’s GDP ranked sixth in the country, accounting for 4.57% of the national GDP, while its CO2 emissions

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ranked second, accounting for 7.79% of the national total[32]. Studies have shown that more than 85% of carbon emissions are caused by the power generation and manufacturing industries[33],

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which are the main sources of carbon emissions in Hebei Province. Undoubtedly, Hebei is facing with a thrilling challenge of how to achieve emission reduction. In 2016, the 13th Five-Year Plan of Work on Controlling Greenhouse Gas Emissions issued by the State Council of China divided the carbon intensity emission reduction targets of 31 provinces (including provinces, municipalities and autonomous regions, excluding Hong Kong and Macao) into five categories, of

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which Hebei belongs to the highest type, i.e., CO2 emissions per unit GDP by 2020. It is 20.5% lower than in 2015[34]. In 2017, Hebei Provincial People's Government issued the Hebei Province's 13th Five-year Plan for Controlling Greenhouse Gas Emissions, which further

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confirmed this goal[35].

However, it is not enough to issue emission reduction orders. Previous domestic studies

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usually put forward emission reduction strategies for industrial structure and production technology, but neglected the source of carbon emissions — who exactly produces carbon emissions? Which provinces have Hebei borne the cost of carbon emissions? How should Hebei adjust its trade relations with other provinces? What factors should we start with? Considering that the implied carbon emissions in inter-provincial trade are an important part of Hebei's carbon emissions, it is of great significance to study the changes and driving factors of the implied carbon emissions in Hebei's trade with other provinces, and put forward combining solutions and adjustment measures. The conclusion of this study provides a reference for Hebei to formulate carbon emission reduction policies, and also fills in the deficiencies of detailed research on carbon emission transfer of inter-provincial trade, and provides a framework for other domestic regions to

ACCEPTED MANUSCRIPT carry out emission reduction research. The following parts of this paper cover several aspects: the second part proposes the research methods and data sources; the third part presents the quantitative research results; the fourth part discusses the research results and puts forward the combining solutions; and the fifth part is the

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research conclusions.

Fig. 1. Growth of GDP and carbon emissions in Hebei from 1997 to 2012 2. Research methods and data sources

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2.1 Research methods

In this paper, the MRIO model is used to carry out research. MRIO is based on regional

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economic input-output tables depicting flows of money and embodied resources to and from sectors within between regions[36].MRIO model has been widely applied in the study of trade implied carbon[37–40]. In our research, there are two important assumptions for the MRIO model application, i.e., ignorance of international trade and unidirectional interprovincial trade. On the one hand, our research only focuses on domestic interprovincial trade, and analyses the impact of interprovincial trade on embodied carbon transfer in Hebei Province, so we exclude international trade. On the other hand, we emphasize that interprovincial trade is bidirectional. There are not only outflows from Hebei Province to other provinces, but also inflows from others. As thus, we can get the important indicators of net outflows. For this, unidirectional interprovincial trade is not

ACCEPTED MANUSCRIPT within the scope of our research. In general, the MRIO model is suitable for us to investigate the embodied carbon transfer problem in Hebei Province. The research methods are as follows. Specifically, this research first uses the inter-provincial bilateral trade model (trade between two provinces, such as Hebei and Shanxi, etc.) to calculate the implied carbon transfer between Hebei

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and other provinces. Secondly, using Structural Decomposition Analysis (SDA, which decomposes the embodied carbon changes into several parts), this paper analyses the driving forces of carbon emission transfer in bilateral trade, mainly on the technology and trade demand driving force. Finally, the relationship model between the changes of trade value net outflow and

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embodied carbon emissions net outflow is constructed, and the strategy of optimizing the commerce between Hebei and other provinces is put forward, along with the key development

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direction of Hebei's industries.

2.1.1 An inter-provincial net embodied carbon emission accounting method based on bilateral trade

The basic structure of the Chinese MRIO model adopted in this study is shown in Table 1. In

, means the the model, there are
provinces, with  sectors in each province, where ,

intermediate input from the sector of region  to the sector of region ( , = 1 ⋯ n, ,  =

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1 ⋯ m),  is the final product from the final use of sector in region  to region ,  is the total output of sector in region ,  is the total input of sector in region , and 

means the exports of sector in region .  is the final input of sector in region , and 

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means the imports of sector j in region .

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Table 1. The basic form of the Chinese MRIO model Intermediate demand

Total

Province 1

Project

Sector 1 ⋯ ⋯ Sector n

Sector 1 Province Intermediate

1

⋮ Sector n

input

⋯⋯

⋯⋯

Province

Sector 1

, ,

, ,

, ,

Final demand

, ⋯ ⋯ ,

⋯⋯

, ⋯ ⋯ ,

, ⋯ ⋯ ,

⋯⋯

Province m Sector 1 ⋯ ⋯ Sector n

⋯⋯

, ,

⋯⋯

, ,

⋯⋯

⋯⋯

⋯⋯

, ,

, ⋯ ⋯ ,

⋯⋯

⋯ ⋯ x, ,

, ⋯ ⋯ ,

Province 1 ⋯ ⋯

Exports

output

,





⋯ ⋯ ,





⋯ ⋯ ,





, ⋯ ⋯

,

,

⋯⋯

⋯⋯

Province m

⋮

⋮

⋮

⋮

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Sector n

, ,

Imports

⋯⋯





Value-added



Total input

, ⋯ ⋯ ,

⋯ ⋯  ⋯⋯

⋯⋯





⋯⋯

⋯⋯

⋯⋯

⋯⋯

⋯⋯

, ,







⋯⋯

, ⋯ ⋯ ,

,

⋯ ⋯ 



⋯ ⋯ 

⋯⋯

⋯ ⋯ ,

⋯ ⋯ 

1 

1 2 
  = 1

1 + ⋯ +    + ⋯ +  1 + ⋯ +    +  +  + ⋯ +  + 


1


 = !1 1 + ⋯ +  " + ⋯ + !1 + ⋯ +  " +  + 

-.2

-32 ⋮ -
2

-13 -23 -.3

⋮ -
3

⋯

⋯ ⋯ ⋱ ⋯

-1


1 1 1 -2
, ) 2 , ) 2 , ) 2 , -3
+ ( 3 + + ( 3 + + ( 3 + ⋮ ⋮ ⋮ ⋮ .    -
* '
* '
* '
*

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-12

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Equation (1) can be expressed by matrix, that is: -.1 1 ) 2 , ) -21 ( 2 + = ( -31 ⋮ ⋮  '
* '-
1

,

⋯ ⋯ 

According to Table 1, the following equation can be obtained:

X = AX + E + Y

⋮

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⋮

m

(1) (2)

(3)

(4)

Where, X represents the total output of each region in the country, Y represents the domestic

final demand of each region. E represents every region’s exports. -1 represents the local direct

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consumption coefficient matrix. - is the direct input coefficient matrix of region i to region j.

Assuming that the import and export of each region is not considered, formula (4) can be rewritten as: 1

2

) 2 , ) -21 2 ( 3 + = ( -31 2

⋮ '
1

-.2 -32 ⋮ -
2

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⋮ 2 '
*

-12

-13 -23

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-.1

-.3 ⋮ -
3

⋯

⋯ ⋯ ⋱ ⋯

-1


1

2

.1 + ∑ ≠1 1

-2
) 22 , ) .2 + ∑ ≠2 2 , , -3
+ ( 23 + + ( .3 + ∑ ≠3 3 + ( + ⋮ ⋮ ⋮ -.
* '2
* '.
+ ∑ ≠

*

(5)

Where,  means the total output of region r to meet domestic final demand. 2

In this study, we researched the net transfer of carbon emission between Hebei and other

provinces in China, so we took Hebei as the center to simplify the MRIO model. Based on unidirectional trade assumption[41–43], that is, assuming that there is trade between Hebei and all regions in China, but ignoring the intermediate product trade between other provinces caused by Hebei's economic activities, formula (5) can be changed into:

⋮



ℎ -.ℎ ) 2ℎ , ) -2ℎ ( 3ℎ + = ( -3ℎ ⋮ ⋮  '
ℎ * '-
ℎ

0

-.2 0 ⋮ 0

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0

-.3 ⋮ 0

⋯

⋯ ⋯ ⋱ ⋯

ℎ .ℎ + ∑ ≠ℎ ℎ 2ℎ 0 , ) 2ℎ , ) ,  + 3ℎ 0 + ( 3ℎ + ( + ⋮ ⋮ ⋮ 
ℎ -.
* '
ℎ * ' * 0

(6)

Here, 7 is the output vector of Hebei, and each element represents the output of every

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sector. And ℎ denotes the output caused by economic activity of Hebei province in the region r. According to formula (6), the input-output relationship between Hebei and regional i can be expressed as: ℎ =  − -.ℎ 

−1

.ℎ + ∑ ℎ

(7)

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 ℎ =  − -. −1 - ℎ ℎ + Y ℎ 

(8)

Here, 97 =  − -17 :, 9 =  − -1 :, ;7 = -7 7 + 7 , = 2,3, ⋯ , m. In this study,

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we use G to represent the CO2 emission from direct production of sector i in region r. The carbon emission intensity can be obtained by dividing the direct CO2 emission of region r sector i

by the total output of region r sector i, and can be expressed as 2 , namely: g  = G  /

(9)

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Combined with carbon emission intensity, the calculation formula of carbon transfer between Hebei and other provinces can be written as: Gℎ = 2?ℎ 9 ℎ

ℎ

G ℎ = 2? 9 ; ℎ

(10) (11)

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where Gℎ is the column vector of embodied carbon emission from Hebei to province i, G7

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is the column vector of embodied carbon emission from province i to Hebei, 2?ℎ and 2?

respectively represent the diagonal matrix of carbon emission intensity of Hebei and province i. Combined with the above methods, the net carbon emission outflow in the inter-provincial trade between Hebei and other provinces can be obtained. The specific calculation method is as follows: nG7 = G7 − G7

(12)

Similarly, based on the rate coefficient of value added, the net outflow calculation method of the trade value between Hebei and other provinces can be written as follows: nP7 = P7 − P7

(13)

Where, nP7 represents the net outflowed trade value vector from Hebei to province i. P7

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refers to the trade value transferred from Hebei to province i, and P7 = AB9 7 7 7 . P7 refers to

the trade value transferred form province i to Hebei, and P7 = A?C 9 ;7 . AB7 and A?C represent the diagonalization matrix of the rate coefficient of the value added of Hebei and province i, respectively.

emission outflow between Hebei and other provinces can be analyzed.

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Through the above model, the spatial and temporal evolution characteristics of net carbon

2.1.2 Analysis method of the changes on the embodied carbon emissions’ net outflow: SDA

On the basis of the above analysis, we applied structural decomposition analysis (SDA)

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approach to investigate the driving forces of the embodied carbon transference in inter-provincial trade. SDA decomposition measures carbon emissions embodied in trade through the input-output

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mode. It can not only decompose the direct and indirect embodied carbon emissions, but also examine the indirect influence of variable changes on other regions and departments[21]. Suppose there are two periods of input-output data; we represent 0 and 1 as the base year and

the end year, respectively. And we use D E (t=0 and 1) to represent the net outflow of embodied carbon emissions in the t year. That is:

D  = F × HI and D J = F J × HIJ

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Where, F E expresses the relative cumulative carbon emissions matrix

(14)

FIE is the

cumulative coefficient matrix of embodied carbon emissions outflow, and FE is the cumulative

coefficient matrix of embodied carbon emission inflow. And F E also reflects the relative

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technical level among the provinces. If F E is positive, it means that the technical level of the province in our study is at a relative disadvantage, and, the larger the number, the greater the

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disadvantage. And HIE represents the net outflow amount of the commodity value of

inter-provincial trade in t year, reflecting the scale of trade in that year. Therefore, the net outflow of carbon emissions embodied in inter-provincial trade can be calculated by the following formula:

∆nG = D  − D J = F HI − F J HIJ

= 1⁄2∆nHHI + HIJ  + 1⁄2F + F J ∆HI 

(15)

Where 1⁄2∆nHHI + HIJ  expresses the relative technical level change between the

provinces and reflects the effect of technical change; and 1⁄2F + F J ∆HI  represents the change of inter-provincial trade volume and reflects the effect of the change of demand.

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∆nHI = HI − HIJ = NI OI − NIJ OIJ

= 1⁄2∆NI  OI + OIJ  + 1⁄2NI + NIJ ∆OI 

(16)

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Where NIE is the coefficient matrix of interprovincial trade value net outflow, and it is the

coefficient matrix of trade value net outflow from all departments of a province to other provinces in t year. HIE is the interprovincial trade value net outflow matrix, and expresses the net

commodity value from a province to other provinces in t year. 1⁄2∆NI  OI + OIJ  represents the changes of inter-provincial trade structure, reflecting the influence of the trade

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trade scale, reflecting the effect of the trade scale changes.

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structure changes. And 1⁄2NI + NIJ ∆OI  represents the changes of inter-provincial

The impact of demand can be further decomposed into structure impact and scale impact, and its calculation process is as follows: 1⁄2F + F J ∆HI 

= 1⁄2F + F J 1⁄2∆NI  OI + OIJ

(17)

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+1⁄2F + F J 1⁄2NI + NIJ ∆OI 

2.1.3 Relationship model: policy choice

After analyzing the impact of technology, demand, structure, and scale, the paper combines

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the changes of " net outflow of trade value " and " net outflow of embodied carbon emissions ", and builds the analysis model to provide a basis for policy optimization, which refers to the method proposed by Cheng et al[24]. That is:

J  ∆QR = QR − QSJ = H ⁄HETEUV − HJ ∕ HETEUV J  ∆QX = QX − QXJ = D ⁄DETEUV − DJ ∕ DETEUV

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P

(18)

Where ∆QR and ∆QX represent the contribution rate changes of commodity net outflow

E and embodied carbon emissions net outflow. HETEUV = HIE + HE , means the sum of net outflow and

E net inflow of interprovincial trade value; DETEUV = DIE + DE , means the sum of net outflow and net

inflow of carbon emissions. HE and DE express the net outflow of trade value and the net

outflow of carbon emissions of industry in year t, and they display plus in the net outflow industry and minus in the net inflow industry. Through equation (18), the industries can be divided into four types: I, II, III (III-A and III-B),

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The industry of type I, ∆QR > 0 and ∆QX < 0, is characterized by an increase of the

trade value contribution of the during the study period, but a decrease on the carbon emissions. It belongs to the key development industry.

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The industry of type II, ∆QR < 0 and ∆QX > 0, is characterized by a decrease the trade

value contribution, but an increase on the carbon emissions. It belongs to the controlled development industry.

The industry of type III, ∆QR > 0 and ∆QX > 0, is characterized as an increase in the

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trade value contribution and carbon emissions contribution during this period. Such industries can be divided into two categories:

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For III-A industry, ∆QR > ∆QX > 0, it’s increase of the trade value contribution is greater

than the carbon emissions. And it belongs to the moderately-guided development industry.

For III-B industry, ∆QX > ∆QR > 0, it’s increase of the trade value contribution is smaller

than the carbon emissions. And it belongs to the moderately-controlled development industry.

The industry of type IV, ∆QR < 0 and ∆QX < 0, is characterized as a decrease in the

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trade value contribution and embodied carbon emissions contribution during this period. It belongs to the maintenance development industry. 2.2 Data sources

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This study uses the 1997, 2002, 2007, and 2012 China MRIO tables[44–47]. Because the input-output table is compiled once every five years, the latest version is published in 2012. The

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China MRIO includes 30 provinces: Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi, Hainan, Chongqing, Sichuan, Sichuan, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang. There are no data for Taiwan, Tibet, Hong Kong, and Macao, so they are not included. Since the MRIO tables in different years are published by different researchers or research institutes, the sector divisions are not in the same caliber. In order to facilitate research, we consolidate the sectors according to certain rules. The consolidated tables contain 28 sectors, as shown in Table 2. In order to avoid the impact of price fluctuations, we convert the Chinese MRIO tables from current into constant price using the double-deflation method[48]. Deflators are compiled based on the price data provided from Chinese Statics

ACCEPTED MANUSCRIPT Yearbooks of the various years[49]. Table 2. The consolidated sector classification table Sector Title

S01

Farming, Forestry, Animal Husbandry, and Fishery

S02

Coal Mining and Washing

S03

Petroleum and Natural Gas Extraction

S04

Metal Ores’ Mining and Dressing

S05

Nonmetal Mineral Ores’ Mining and Dressing

S06

Food Manufacturing and Tobacco Processing

S07

Textile Industry

S08

Apparel, Leather, and Related Products

S09

Wood Processing and Furniture Manufacturing

S10

Papermaking, Printing, and Paper Product Manufacturing

S11

Petroleum Processing, Coking, and Nuclear Fuel Processing

S12

Chemicals and Medicinal Products

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Sector Code

S13

Nonmetal Mineral Products

S14

Metal Smelting and Rolling Processing

S15

Metal products

Ordinary and Special Machinery Manufacturing

S17

Transportation Equipment Manufacturing

S18

Electric Equipment Machinery Manufacturing

S19

Electronic and Telecommunications Equipment Manufacturing

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S16

S20

Instruments, Meters, Cultural and Office Machinery

S21

Other Manufacturing Industry

S22

Electricity and Heat Production and Supply

S23

Gas Production and Supply

S25 S26 S28

Construction

Transportation, Storage, and Post and Telecommunication Services

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S27

Water Production and Supply

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S24

Wholesale and Retail Trade, Catering Services Other Services

In the study, we obtain the data for the CO2 emissions for each sector of each province from

the China Emissions Accounts and Datasets (CEAD) [50]. CEAD regularly publishes CO2 emissions inventories by using the IPCC Sectoral Emission Accounting Approach for China and its 30 provinces and cities. Similar to the processing of the departments in the MRIO table, we combine the departments in the CO2 emissions inventory and obtained the same 28 sectors as in Table 2. 3. Research results 3.1 The changes of the embodied carbon emissions’ net outflow in inter-provincial trade of

ACCEPTED MANUSCRIPT Hebei Province Hebei has long been in the state of net outflow of implicit carbon emissions in inter-provincial trade, and has undertaken a large amount of carbon emissions for other provinces. The embodied carbon emissions of Hebei were 59.84 Mt in 1997, 106.27 Mt in 2002, 440.35 Mt

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in 2007, and 303.74 Mt in 2012 (Fig. 2), which grew by 79% from 1997 to 2002, 314% from 2002 to 2007, and fell by 31% from 2007 to 2012. It can be seen that the net outflow of embodied carbon emissions increased rapidly from 1997 to 2007, but decreased from 2007 to 2012. Affected by the financial crisis in 2008, the economic growth of Hebei Province slowed down. At the same

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time, in order to promote low-carbon sustainable development, Hebei has accelerated the adjustment of industrial structure and the transformation of development mode, invested in

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high-carbon-intensive industries such as steel, equipment manufacturing and petrochemical industry, promoted industrial technological transformation and eliminated backward production

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capacity. As a result, the net outflow of implicit carbon emissions has decreased.

Fig. 2. The changes of the embodied carbon emissions’ net outflow in inter-provincial trade of Hebei Province. 3.2 The spatial-temporal evolution of the embodied carbon emissions’ net outflow From 1997 to 2012, the target provinces (i.e., the provinces net inflow the embodied carbon emissions from Hebei) increased. There were 18 provinces in 1997, 21 in 2002, and 22 provinces in 2007 and 2012. In 1997, the target provinces were mainly located in the eastern and southern

ACCEPTED MANUSCRIPT coastal areas (Fig. 3a), and further extended to the central, western and northeastern provinces in 2002 (Fig. 3b). In 2007, it was mainly concentrated in the western provinces and southeastern coastal areas (Fig. 3c). By 2012, the target provinces covered most of China's provinces (Fig. 3d). Through inter-provincial trade, Hebei has provided a large number of commodities for other

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provinces, but also transferred huge amounts of implicit carbon emissions. Figure 3d shows that, in 2012, the target provinces of Hebei’s carbon emissions are mainly Jiangsu, Beijing, Henan, Anhui, and Tianjin, with net outflow of 67.65 Mt, 56.52 Mt, 54.15 Mt, 30.43 Mt and 22.44 Mt, respectively. The five provinces accounted for 76% of the total implicit carbon emissions net

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outflow in Hebei Province. However, Hebei's main target provinces for net outflow of trade value are: Henan, Jiangsu and Heilongjiang, with net outflow of 100.932 billion yuan, 92.07 billion

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yuan, and 81.684 billion yuan, respectively, accounting for 83% of the commodity net outflow. The figure shows that there are significant differences for the target provinces in terms of the two

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types net outflow.

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Fig. 3. The spatial-temporal evolution of the embodied carbon emissions’ net outflow in inter-provincial trade of Hebei Province from 1997 to 2012.

sectors

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3.3 The embodied carbon emissions’ net outflow of Hebei Province from the perspective of

Fig. 4 shows that in 2012, the three sectors with the largest net outflow of implicit carbon emissions are S02, S14, and S22, respectively. In 1997, the net outflow from these three sectors in

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was 9.74Mt, 19.92Mt and 32.85Mt, accounting for 16.37%, 33.49% and 55.22% of the total implicit carbon emissions from Hebei Province, respectively. By 2012, the three sectors’ net

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outflow changed to 38.19Mt, 205.98Mt and 90.25Mt, accounting for 12.57%, 67.81% and 29.71%, respectively (Fig. 5). Among them, the most significant change was S14, which contributed 67.81% to the net outflow of hidden carbon emissions from 33.49%. The steel industry belongs to a typical high-carbon-intensive industry, and is dominant in Hebei’s S14 sector. At the same time, the iron and steel industry in Hebei has developed unprecedentedly since the reform and opening up, especially from 1997 to 2012. In 1997, Hebei’s crude steel production was 10.5614 million tons. By 2012, it had increased to 18.0484 million tons, ranking first in China for a long time. Hebei has provided quantities of steel products for other provinces, and also transferred massive implicit carbon emissions through the steel industry, and the growth is rapid.

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Fig. 4. The net outflow of embodied carbon emissions of 28 sectors in Hebei Province The net outflow of S22 increased from 32.85Mt in 1997 to 90.25Mt in 2012, but the contribution to total net outflow fell from 50.79% to 12.57%. This is mainly due to the fact that

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the growth rate of net transfer of carbon emissions from S14 is much faster than that of S22. The net outflow of S02 increased from 9.74Mt in 1997 to 38.19Mt in 2012. It is worth noting that, the amount in 2007 was 223.68Mt, contributing 50.79% to the total net outflow. By 2012, the

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contribution rate had fallen to 12.57%. Hebei is a large coal province, and its energy structure is characterized as "rich coal, poor oil, and little gas". In the extensive heavy industry development

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process, the energy mainly depends on coal, which accelerates the development of the coal industry. However, from 1997 to 2007, the overexploitation of coal resources in Hebei increased the depletion of resources and made mining difficult. Therefore, in the 12th five-year plan period (2011–2015), Hebei adjusted the development policy of coal mining and washing industry, and encouraged the coal enterprises to "go global". At the same time, large-scale import of coal from outside to meet the production and consumption needs of Hebei Province. As a result, the implicit carbon emissions net outflow from S02 in 2012 decreased significantly compared with 2007.

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Fig. 5. The ratio changes of the embodied carbon emissions’ net outflow of Hebei’s 28 sectors from 1997 to 2012

3.4 Driving forces of net outflow of implicit carbon emissions in Hebei inter-provincial trade Based on the analysis of the temporal and spatial evolution of net carbon emissions in Hebei Province, we use SDA two-step model to analyze the driving factors affecting the change.

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The first step is to use SDA model to analyze the impact of technology level and trade demand driving force on the net transfer of implicit carbon emissions in Hebei inter-provincial trade. From 1997 to 2012, the net outflow of embodied carbon emissions increased by 244.26Mt,

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which caused by technology driving force and demand driving force increased by -108.45Mt and 352.71Mt, respectively. This shows that the improvement of Hebei's technology level in this

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period is beneficial in reducing the carbon emissions outflow. And the rapidly increasing inter-provincial trade demand is the principal factor for the growth of the embodied carbon emissions net outflow.

From 1997 to 2007, net outflow of implicit carbon emissions increased by 380.87 Mt, which

caused by technology driving force and demand driving force increased by 145.55 Mt and 235.32 Mt, respectively. This shows that in this period, Hebei's technological level has improved slowly, relatively low technological level and relatively high inter-provincial trade demand are the two driving forces leading to the growth of implicit carbon emissions net outflow. From 2007 to 2012, the amount increased by -136.62 Mt, while the net outflow caused by technology driving force and demand driving force increased by - 517.95Mt and 381.33 Mt, respectively. This indicates that

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i−108.45j

i352.71j

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Total

Demand (Mt) −2.10 ] 93.14 g \−3.42f \ f 2.29 \ f \−0.32f \ 1.00 f \−0.14f \ 0.17 f \−0.01f \−0.01f \−6.45f \−1.36f \ 11.21 f \ 87.89 f \ 0.23 f \−0.35f \−0.11f \ f −0.18 \ f \−0.17f \ 0.00 f \−0.17f \ 61.57 f \−0.54f \ 0.09 f \−0.07f \−6.78f \−1.57f [ 1.50 e

Technology (Mt) 6.32 ]−345.97g \ −0.30 f \ f −5.23 \ f \ 0.28 f \ −1.46 f \ 0.46 f \ −0.27 f \ −0.01 f \ −0.59 f \ 0.19 f \ 6.62 f \ −29.07 f \−141.07f \ −0.42 f \ 0.00 f \ −0.14 f \ f 0.29 \ f \ 0.42 f \ 0.00 f \ 0.05 f \ −24.63 f \ 1.45 f \ 0.00 f \ −0.97 f \ 13.07 f \ 4.21 f [ −1.16 e

i145.55j

i235.32j

Demand (Mt) −1.77 ] 160.49 g \ −7.71 f \ f 2.80 \ f \ −0.37 f \ 1.03 f \ −0.08 f \ 0.20 f \ 0.02 f \ 0.17 f \ −2.64 f \ −4.64 f \ 12.28 f \ 174.38 f \ 0.32 f \ 0.44 f \ 0.03 f \ f −0.14 \ f \ −0.22 f \ 0.01 f \ −0.17 f \ 61.51 f \ −0.83 f \ 0.01 f \ −0.56 f \−11.74f \ −2.17 f [ 0.70 e

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Technology (Mt) −0.38 ] 120.80 g \ −1.18 f \ f 0.61 \ f \ 0.12 f \ −0.22 f \ 0.00 f \ −0.01 f \ 0.03 f \ 0.40 f \ 8.86 f \ −4.57 f \ 2.98 f \ 64.86 f \ 0.05 f \ 1.04 f \ 0.28 f \ f 0.08 \ f \ −0.06 f \ 0.01 f \ 0.13 f \−41.04f \ −0.40 f \ −0.15 f \ −0.04 f \ −4.20 f \ −0.90 f [ −1.54 e

2007-2012

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Demand (Mt) −2.11 ] 52.66 g \ −9.95 f \ f 3.32 \ f \ −0.75 f \ 1.94 f \ −0.13 f \ 0.32 f \ −0.02 f \ −0.38 f \−18.30f \ 0.21 f \ 14.09 f \ 164.02 f \ 0.40 f \ −0.99 f \ −0.39 f \ f −0.34 \ f \ −0.24 f \ 0.00 f \ −0.46 f \ 160.66 f \ −0.65 f \ 0.25 f \ −0.80 f \−11.31f \ −1.89 f [ 3.56 e

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^1 ] ^2 g \ ^3 f \ f ^4 \ f \ ^5 f \ ^6 f \ ^7 f \ ^8 f \ ^9 f \^10f \^11f \^12f \^13f \^14f \^15f \^16f \^17f \ f ^18 \ f \^19f \^20f \^21f \^22f \^23f \^24f \^25f \^26f \^27f [^28e

Technology (Mt) 4.18 ] −24.21 g \ −2.66 f \ f −2.85 \ f \ 0.46 f \ −1.60 f \ 0.36 f \ −0.23 f \ 0.05 f \ 0.35 f \ 18.26 f \ −4.16 f \ −16.69 f \ 22.04 f \ −0.22 f \ 2.13 f \ 0.45 f \ f 0.39 \ f \ 0.20 f \ 0.01 f \ 0.29 f \−103.25f \ 0.33 f \ −0.30 f \ −0.83 f \ 1.66 f \ 1.46 f [ −4.06 e

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1997-2012

i−517.95j

i381.33j

The second step is to use SDA model to decompose the demand driving force into the

structure driving force and the scale driving force. In the process of inter-provincial trade of unit output value, each department will transfer different carbon emissions to different target provinces. Therefore, when formulating optimization strategies, we should not only pay attention to the impact of the structure and scale of various sectors, but also consider the changes of net transfer value of trade and net transfer value of carbon emissions between Hebei Province and the target provinces.

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3.5 The sectoral classification of Hebei Province In the above analysis, it is found that the net outflow of implicit carbon emissions in Hebei's inter-provincial trade increased rapidly between 1997 and 2012. The target provinces spread

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gradually from the eastern coastal provinces to the northern provinces and the central provinces. Hebei has assumed more and more carbon emissions for other provinces. At the same time, there are significant differences between the target provinces of net outflow of trade value and net outflow of implied carbon emissions. From the perspective of promoting China's carbon emission

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reduction, it is necessary to further reduce the embodied carbon emissions net outflow of Hebei Province. However, according to the inter-provincial input-output relationship, if only reduce the

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inter-provincial trade volume of a sector, it will impact the related industries of the downstream provinces. For example, Hebei Province is a major iron and steel province, and most provinces of China rely on it to supply steel products for production and consumption. In 2012, the trade surplus between Hebei Metal Smelting and Rolling Processing Sector (S14) and other provinces was 32.912 billion yuan. Therefore, reducing the inter-provincial transfers of iron and steel

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products in Hebei will have a huge impact on the downstream industries in other provinces. In combination with the embodied emissions in bilateral trade (EEBT) model and the SDA model, we find that different departments have discrepancies in four driving factors: relative

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technology level, trade demand, trade structure and trade scale. As a result, the net outflow of carbon emissions from Hebei Province can be concentrated in some sectors. Meanwhile, we also

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find that the net transfer of commodities and the net transfer of implied carbon emissions in various sectors are not one-to-one correspondence. Some industries can inflow huge amounts of commodity value and outflow large numbers of carbon emissions, while some industries are on the contrary. Therefore, in order to reduce the implicit carbon emissions and keep the provincial trade scale as much as possible, this paper divides 28 departments into four categories according to the dual relationship between the net transfer of trade value and the net transfer of implicit carbon emissions in Hebei Province from 1997 to 2012, and puts forward corresponding industrial development policies (Fig. 6).

Type I: ∆QR > 0, ∆QX < 0. The proportion of the net outflow of commodity value is

rising, which means that the outside provinces’ demand for such industries is growing. At the

ACCEPTED MANUSCRIPT same time, the proportion of the net outflow of embodied carbon emissions is declining, indicating that the pressure caused by such industries on carbon emissions is easing. The overall performance of such industries in Hebei is as follows: large market demand, relatively high technology level, low energy consumption, and low carbon emissions. It belongs to the key development industry

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and includes 5 industries: S04, S06, S23, S24, and S26, respectively. Hebei should guide these industries to expand their investment scale and further increase the market share in inter-provincial trade.

Type II: ∆QR < 0, ∆QX > 0. The proportion of the net outflow of commodity value is

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declining, indicating that the demand of outside provinces for such industries is decreasing. At the same time, the ratio of the net outflow of carbon emissions is rising, which means that these

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industries have increased the carbon emission pressure of Hebei Province. Generally speaking, such industry has the following characteristics: relatively low technical level, high pollution, and high emission, and decreasing market demand. It belongs to the controlled development industry and includes 7 industries: S01, S02, S09, S10, S15, S18, and S22. Hebei should regulate and control the development of such industries, especially gradually reduce the inter-provincial trade transfer of such products.

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Type III: ∆QR > 0, ∆QX > 0. The proportion of the net outflow of commodity value is

rising, this means that demand of outside provinces from such industries is rising. Meantime, the

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proportion of the net outflow of carbon emissions is rising too, indicating that such industry’s development has increased the carbon emission pressure of Hebei. Type III includes eight industries: S07, S11, S14, S17, S19, S20, and S27. And such industries should be further divided.

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If ∆QR > ∆QX (III-A), then the industry belongs to the moderately-guided development industry, such as S16 (Ordinary and Special Machinery Manufacturing). Hebei Province should actively guide and pay attention to improving the technical level of these industries and reducing their carbon emissions. If ∆QR < ∆QX (III-B), then the industry belongs to the

moderately-controlled development industry, such as S14. Hebei Province should reduce the industrial scale through policy guidance, while increasing imports from provinces with technological advantages.

Type IV: ∆QR < 0, ∆QX < 0. The ratio of the net outflow of commodity value is declining,

indicating that the demand of outside provinces for such industries is decreasing. And the ratio of

ACCEPTED MANUSCRIPT the net outflow of embodied carbon emissions is declining too, indicating that the pressure placed by such industries on carbon emissions is easing. There are 8 industries in this category: S03, S05, S08, S12, S13, S21, S25 and S28. This kind of industry belongs to the maintenance development industry. Hebei Province should give full play to the role of market regulation, appropriately

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reduce the trade scale with provinces with relatively high technical level, and expand the trade

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scale with provinces with relatively low technical level.

Fig. 6. Changes in the share of net outflow of trade value and carbon Emission of Hebei

4. Discussions

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Province industries from 1997 to 2012

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The above contents show our research ideas and results. Next, we will use these research

ideas and results to discuss key industries and propose specific comprehensive solutions. This is a different place from previous researches and is our innovation point. Previous studies tend to focus on general policy proposals, generally proposing to promote technological development and industrial upgrading, but do not go deep into specific industries to propose targeted solutions, which has less guiding and implementation significance for how to reduce implied carbon emissions. Now, our research has more specific guiding significance. We should not only analyze the specific industries, but also balance the trade relations with the relevant provinces, and put forward definite policy recommendations.

ACCEPTED MANUSCRIPT In our findings, the three industries with the largest net outflow of embodied carbon emissions in 2012 were S14 (Metal Smelting and Rolling Processing), S22 (Electricity and Heat Production and Supply), and S02 (Coal Mining and Washing). In order to formulate relevant industrial policies and reduce Hebei's carbon emissions, further policy analysis is carried out on

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the three industries and their target provinces for carbon transfer.

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Fig. 7. Distribution of target provinces in the three industries with the largest net outflow of carbon emissions in 2012

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Fig. 8. Changes of the proportion of embodied carbon emissions and trade value of 29 target provinces transferred from Hebei in S14, S22 and S02 in 2012 4.1 The Optimization Measures of S14 (Metal Smelting and Rolling Processing) Firstly, we consider the strategy of reducing the net carbon emissions of Hebei on S14. In 2012, the industry with the largest net carbon emissions in inter-provincial trade in Hebei was S14,

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with a net outflow of 205.9755Mt, accounting for 67.81% of the total net outflow of embodied carbon emissions of Hebei Province. S14 belongs to the moderately-controlled development

industry, namely, ∆QX > ∆QR > 0. In 2012, the top three provinces with the largest net

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outflow of embodied carbon emissions from S14 were Beijing, Jiangsu, and Henan (Fig. 7a), contributing 19.11%, 15.83%, and 13.72%, respectively. Meanwhile, they were also the provinces

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with the largest net outflow of trade value, accounting for 23.10%, 19.33% and 15.12% respectively (Fig. 8a). In the trade between Hebei Province and the three target provinces, the change of net outflow ratio of trade value is greater than that of net outflow ratio of carbon emissions. This means that Hebei has a comparative technological advantage in trade with these provinces. Hebei should expand the scale of inter-provincial trade with Beijing, Jiangsu and Henan. Similarly, Hebei has technological advantages over eight provinces and cities, such as Shanghai, Zhejiang, and Anhui, in terms of S14, and can consider expanding its trade scale. 4.2 The Optimization Measures of S22 (Electricity and Heat Production and Supply) Secondly, we consider the strategy of reducing the net outflow of embodied carbon emissions of Hebei on S22. In 2012, the net outflow of implicit carbon emissions from S22 to other

ACCEPTED MANUSCRIPT provinces was 90.25Mt, accounting for 29.71% of the total, ranking second among all industries. S22 transferred a net trade value of -71.233 billion yuan to other provinces, which generally represented a net inflow. In the comparison of the dual relationship between 2012 and 1997 (Fig. 6), S22 belongs to the controlled development industry (Type II). Especially in the comparison

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between 2012 and 2007, Hebei S22's net outflow share of trade value decreased by 1%, while the net outflow share of carbon emissions increased by 4.94%. This shows that the technology level of this industry has not improved compared with other provinces during this period, and the technological advantages in this area have turned into technological disadvantages, and such

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inter-provincial trade has also increased the pressure of carbon emissions. Therefore, Hebei Province should reduce its investment in the industry, control the scale of production and reduce

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its market share in inter-provincial trade.

In 2012, the net carbon emissions from S22 in Hebei Province to Jiangsu, Beijing and Henan were the largest, which were 27.5864 Mt, 21.9119 Mt and 19.2370 Mt, respectively. The net trade value transferred to these three provinces was 0, 46.94 billion yuan and 144 million yuan. In the trade with Jiangsu, S22 of Hebei transferred 30.57% of the net implied carbon

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emissions to Jiangsu, while the net trade value transferred 0% (Fig. 8b). This is mainly due to the high correlation between S22 and S14. Because of the industrial relationship, Hebei transferred huge amounts of commodity value of S14 to Jiangsu through inter-provincial trade and also

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transferred large numbers of embodied carbon emissions, including carbon emissions from S22. As thus, in order to reduce the transfer of implicit carbon emissions from Hebei S22 to Jiangsu, it

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is necessary to further improve the technical level of S14 and reduce the carbon intensity in this industry.

In the trade with Beijing, the net transfer of implicit carbon emissions from Hebei S22 to

Beijing accounted for 24.28%. However, from the perspective of trade value, Hebei net transfer from Beijing accounted for 65.90% (Fig. 8b). This shows that Hebei is in an extremely disadvantageous position in the trade. Beijing has acquired considerable value through the headquarters effect, but large carbon emissions are borne by Hebei, which has a negative impact on the environment. Hence, Hebei Province should reduce the trade of such industry products to Beijing. In the transaction with Henan, S22 of Hebei transferred a net implied carbon emission of

ACCEPTED MANUSCRIPT 21.32% to Henan. The trade value was net inflow, contributing 0.20%. This uncoordinated relationship also reflects the fact that Hebei is at a technological disadvantage in S22, and the trade volume of such industry with Henan should be reduced to lessen the carbon emission pressure. The trade between Hebei and 15 provinces such as Liaoning, Heilongjiang and Shaanxi

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are similar. 4.3 The Optimization Measures of S02 (Coal Mining and Washing)

Thirdly, we consider the strategy of reducing the net outflow of embodied carbon emissions of Hebei on S02. In 2012, the net outflow of embodied carbon emissions of S02 was 38.1871Mt,

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accounting for 12.57% of the total net outflow, ranking third among all industries. In 2012, the trade value net outflow of this industry in Hebei was -49.604 billion yuan, showing a trade value

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net inflow. In the comparison of the double relationship between 2012 and 1997 (Fig. 6), S02 belongs to the controlled development industry (Type II). It is worth noting that, in 2007, the net outflow of implied carbon emissions of S02 was 223.6752Mt, contributing 50.79%, and it declined to 38.1871Mt in 2012, contributing 12.57%. This indicates that the technical level of S02 in 2012 is higher than that in 2007, but it is still at a disadvantage level compared with other

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provinces, belonging to the controlled development industry, which will increase the pressure of carbon emissions in Hebei. Therefore, Hebei Province should consider reducing investment in this industry, controlling production scale and reducing its market share in inter-provincial trade.

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In 2012, Hebei S02 transferred the most carbon emissions to Beijing, Jiangsu, Henan and Heilongjiang provinces (Fig. 7c), which were 685.96 Mt, 566.22 Mt, 389.71 Mt and 366.71 Mt,

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respectively. The net trade value to these provinces was - 1.176.24 billion yuan, 0, - 659.43 billion yuan and 0.5147 billion yuan, respectively. In the trade with Beijing, the net transfer of implicit carbon emissions from Hebei coal

mining and washing industry (S02) to Beijing accounts for 17.96%, while the net transfer of trade value represents a net inflow, with a contribution rate of 2.37% (Fig. 8c). This shows that the trade with Beijing's is not conducive to the environmental development and increases the pressure of carbon emissions in Hebei Province. Similarly, there are six provinces such as Tianjin, Liaoning and Heilongjiang. Hebei should reduce the trade scale with these provinces on S02 so as to ease the pressure of carbon emissions. In the trade with Jiangsu, the net transfer ratio of implicit carbon emissions from Hebei S02

ACCEPTED MANUSCRIPT to Jiangsu is 14.83%, while the net transfer ratio of trade value is 0 (Fig. 8c), which is mainly caused by the transfer of a large number of steel products from Hebei to Jiangsu. Coal industry is the upstream and fuel supply industry of iron and steel industry, and the two industries are highly related. Although there is no trade between Hebei and Jiangsu in S02, due to the indirect

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relationship of input and output, carbon emissions from the coal industry are implied in the transfer of products from the iron and steel industry. Similarly, there are trade with Shanghai, Jiangxi and Hainan. Hebei should optimize the iron and steel industry structure and improve the technical level to reduce the carbon emissions.

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In the trade with Henan, the net transfer ratio of carbon emissions from Hebei S02 to Henan is 10.21%, and the net transfer ratio of trade value is 0.1% (Fig. 8c). The inconsistency reflects

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that Hebei is in a technological disadvantage compared with other provinces, and the trade with Henan has increased the adverse impact on the environment of Hebei, which is not conducive to reducing carbon emissions. Similarly, trade with Hubei, Hunan and Guangdong should be reduced in order to reduce the pressure of carbon emissions.

In the trade with Shanxi, the net transfer ratio of carbon emissions from Hebei S02 to Shanxi

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is -1.43%, which shows net inflow of carbon emissions, and the value of trade shows net inflow, accounting for 37.42%. This shows that the trade with Shanxi has a positive impact on the environment, which is conducive to reducing the pressure of carbon emissions in Hebei, and

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should expand the trade scale with Shanxi on S02. Similarly, there are transactions with Ningxia. In the trade with Inner Mongolia, the net carbon emission transfer ratio from Hebei S02 to

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Inner Mongolia is 0.75%, while the trade value is net import, accounting for 48.59%. This shows that compared with other provinces, the trade with Inner Mongolia has a relatively small adverse impact on the environment, and Inner Mongolia is an important source of coal in Hebei Province, should properly expand imports from Inner Mongolia, reduce exports. 5. Conclusions

Based on the data of China's multi-regional input-output tables in 1997, 2002, 2007 and 2012, this paper uses EEBT model to analyze the spatial-temporal characteristics of net carbon emissions in Hebei's inter-provincial trade, and uses two-step SDA model to analyze the driving factors. And based on the dual relationship between net trade value and net carbon emission, this paper puts forward some policy suggestions to reduce net transfer of implicit carbon emissions.

ACCEPTED MANUSCRIPT The specific conclusions are as follows: Firstly, Hebei has transferred a large amount of net carbon emissions in inter-provincial trade. From 1997 to 2012, net carbon emissions transferred from Hebei to other provinces increased nearly six times, while the spatial distribution of the target provinces changed greatly. In 1997, the

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target provinces mainly concentrated in the eastern and southern coastal areas, including Shandong, Jiangsu and Guangdong provinces. By 2012, the target provinces will be almost all over the country, including Xinjiang, Qinghai and Heilongjiang provinces. This change reflects that Hebei has not only outflow large numbers of high-carbon energy products to other provinces,

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but also made an important contribution to the economic development of the target provinces. At the same time, Hebei has also undertaken a large number of carbon emissions for the target

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provinces. In order to reduce carbon emissions, Hebei Province should further optimize industrial policies and reduce net carbon emissions from inter-provincial trade.

Secondly, the net outflow of embodied carbon emissions in Hebei is mainly concentrated in several key industries. From 1997 to 2012, the three industries with the largest net outflow of embodied carbon emissions in the inter-provincial trade of Hebei were S14, S22, and S02. The

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rapid development of S14 is an important reason for Hebei's net transfer of a large amount of implied carbon emissions to other provinces. In addition, there are significant differences in the target provinces of net outflow of trade value and embodied carbon emissions. This makes it

emissions.

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possible to further optimize Hebei's industrial policy and reduce the net transfer of implicit carbon

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Thirdly, demand driving force is an important factor for the growth of net implied carbon emissions in Hebei inter-provincial trade. Using the two-step Structural Decomposition Analysis method, this paper calculated the main driving factors for the net outflow growth of the embodied carbon emissions from 1997 to 2012. The findings showed that the net outflow of embodied carbon emissions increased by 224.26Mt, which caused by demand driving force and technical driving force are 352.71Mt and 108.45Mt, respectively. In addition, this paper also calculated the main driving factors for the growth of net carbon emissions from 28 industries in Hebei Province. Fourthly, Hebei should implement differentiated industrial development policies to reduce the net transfer of implicit carbon emissions in inter-provincial trade. In this paper, 28 industries are divided into four types, according to the changes of the share of trade value net outflow and

ACCEPTED MANUSCRIPT embodied carbon emissions net outflow in Hebei Province from 1997 to 2012. Type I is the key development industry, including 4 sectors, which should be expanded through industrial policy guidance to improve the market share. Type II is the controlled development industry, including 8 industries. The investment in such industry should be reduced, so as to control the production

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scale and reduce the market share. Type III consists of 8 industries, which can be divided into two categories: moderately-guided development industry and moderately-controlled development industry. Type IV is the maintenance development industry, including 8 industries. For such industries, the scale of trade with provinces with relatively high technological level should be

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reduced appropriately, and the scale of trade with provinces with relatively low technological level should be expanded. At the same time, this paper also puts forward specific policy

in Hebei and their target provinces.

Acknowledgments

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recommendations for the three industries with the largest net transfer of implicit carbon emissions

The authors are grateful for financial support from the National Natural Science Foundation of China under Grant Nos. 71773118 and 71733003. The data used in the

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ACCEPTED MANUSCRIPT 1. From 1997 to 2012, the embodied carbon’s net outflow of Hebei increased by 244Mt. 2. The number of target provinces has increased and spread across the country. 3. Technical level and trade demand are the main factors affecting carbon’s outflow. 4. The net outflow is mainly concentrated in three industries.

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5. Trade relations with other provinces need to be adjusted.

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Sanmang Wu: Review Shantong Li: Review

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