Environmental Pollution Effects of Regional Industrial Transfer Illustrated with Jiangsu, China

Abstract

Industrial transfer is reshaping the geographic layout of industries and facilitating the transfer and spread of environmental pollution. This study employs the pollution transfer estimation method to discuss the environmental effect of industrial transfer. By compiling statistics on industries of a certain scale according to time-series data, the researchers compute the pollution load generated by industrial transfer and the difference in pollution emissions for each region and industry. Through the constructed evaluation model, the empirical scope is Jiangsu, which is the most developed industry in China. The results reveal that there is an apparent spatial hierarchy among the transferred industries in Jiangsu. Most industries transfer from the southern Jiangsu region toward the central Jiangsu and northern Jiangsu regions. Environmental pollution is redistributed among prefecture-level cities because of intercity industrial transfer; the spatial characteristics of pollution exhibit a notable hierarchical pattern. Furthermore, the transferred pollution load differs considerably between industries. The textile industry and chemical raw material and chemical product industry are mainly transferred toward the Central Jiangsu and Northern Jiangsu regions, whereas the papermaking and paper product manufacturing industry is primarily redistributed to the Southern Jiangsu region. The empirical results can serve as a reference for analyzing the environmental pollution effects of regional industrial transfer.

Full text

sustainability
Article
Environmental Pollution Effects of Regional Industrial Transfer
Illustrated with Jiangsu, China
Guangxiong Mao 1, 2, †, Wei Jin 3, *,† , Ying Zhu 4, Yanjun Mao 5, Wei-Ling Hsu 1,2 and Hsin-Lung Liu 6,*


Citation: Mao, G.; Jin, W.; Zhu, Y.;
Mao, Y.; Hsu, W.-L.; Liu, H.-L.
Environmental Pollution Effects of
Regional Industrial Transfer
Illustrated with Jiangsu, China.
Sustainability 2021,13, 12128.
https://doi.org/10.3390/su132112128
Academic Editor: Alessandra De
Marco
Received: 12 October 2021
Accepted: 29 October 2021
Published: 3 November 2021
Publisher’s Note: MDPI stays neutral
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1School of Urban and Environmental Science, Huaiyin Normal University, Huai’an 223300, China;
gxmao123@126.com or 8199811008@hytc.edu.cn (G.M.); quartback@hotmail.com or
8201811011@hytc.edu.cn (W.-L.H.)
2Key Research Base of Philosophy and Social Sciences in Jiangsu Universities-Research Institute of Huaihe
River Eco-Economic Belt, Huai’an 223300, China
3School of Sociology and Population Sciences, Nanjing University of Posts and Telecommunications,
Nanjing 210003, China
4Energy College, Chengdu University of Technology, Chengdu 610059, China; zhuying1203@outlook.com
5
College of Geographical Science, Harbin Normal University, Harbin 150025, China; yjmao123@Hotmail.com
6Department of Leisure Management, Minghsin University of Science and Technology,
Hsinchu 30401, Taiwan, China
*Correspondence: kingwei@njupt.edu.cn (W.J.); hsinlung@must.edu.tw (H.-L.L.);
Tel.: +886-922225586 (H.-L.L.)
† Guangxiong Mao and Wei Jin contributed equally to this work.
Abstract:
Industrial transfer is reshaping the geographic layout of industries and facilitating the
transfer and spread of environmental pollution. This study employs the pollution transfer estimation
method to discuss the environmental effect of industrial transfer. By compiling statistics on industries
of a certain scale according to time-series data, the researchers compute the pollution load generated
by industrial transfer and the difference in pollution emissions for each region and industry. Through
the constructed evaluation model, the empirical scope is Jiangsu, which is the most developed
industry in China. The results reveal that there is an apparent spatial hierarchy among the transferred
industries in Jiangsu. Most industries transfer from the southern Jiangsu region toward the central
Jiangsu and northern Jiangsu regions. Environmental pollution is redistributed among prefecture-
level cities because of intercity industrial transfer; the spatial characteristics of pollution exhibit a
notable hierarchical pattern. Furthermore, the transferred pollution load differs considerably between
industries. The textile industry and chemical raw material and chemical product industry are mainly
transferred toward the Central Jiangsu and Northern Jiangsu regions, whereas the papermaking and
paper product manufacturing industry is primarily redistributed to the Southern Jiangsu region. The
empirical results can serve as a reference for analyzing the environmental pollution effects of regional
industrial transfer.
Keywords: industrial transfer; environmental effect; pollution load; case study
1. Introduction
Adjustments to the positions of international corporations in the global supply chain
have prompted industries to frequently transfer to or cluster in various countries and re-
gions. Since the beginning of the 20th century, four major international industrial transfers
have been completed. The first occurred at the start of the 20th century, when England
transferred its excessive industrial capacity to the United States. The second in the 1950s,
when the United States transferred its traditional industries, such as steel and textile indus-
tries, to Japan and Germany. The third occurred in the 1960s and 1970s, when Japan and
Germany transferred high-labor-intensity processing industries, such as light industries
and textile industries, to the Four Asian Tigers (i.e., South Korea, Taiwan, Hong Kong, and
Singapore). In the fourth international industrial transfer, which occurred at the start of the
Sustainability 2021,13, 12128. https://doi.org/10.3390/su132112128 https://www.mdpi.com/journal/sustainability

Sustainability 2021,13, 12128 2 of 19
21st century, China received industrial transfer of manufacturing industries worldwide. In
addition, China moved its low-end manufacturing industries inland or overseas, accelerat-
ing the industry’s development into high-end industry. Industrial transfer has also induced
the transfer of the environmental impact associate with industrial activity. Cross-border
industrial transfer primarily consists of direct or indirect interorganizational investment
into the host country.
Scholars have discussed whether the environmental stress caused by industrial de-
velopment during a country’s economic growth can be mitigated [
1
–
3
]. Studies in which
non-Chinese scholars analyze the effects of industrial transfer on environmental quality are
few; most have discussed the environmental effects of industrial transfer from a national
standpoint [
4
]. An empirical analysis conducted by Hanif Imran et al. on 15 Asian coun-
tries revealed that direct investment from overseas countries is the cause of environmental
degradation in host countries [
5
]. Wang et al. compared the environmental changes in
developing versus developed countries during the industrial transfer process and revealed
that the PM
2.5
levels increased and decreased, respectively, because of the industrial trans-
fer [
6
]. This result was also obtained by Raza et al. by using monthly statistics for the
United States from 1973 to 2015 [7].
As the global community endeavors to create greener environments, discussions on
the reduction of CO
2
emissions have become inevitable [
8
]. However, Sapkota and Bas-
tola investigated the environment of the United States and revealed that direct overseas
investment in clean energy and energy conservation industries is conducive to reducing
environmental pollution [
9
]. Sarkodie and Strezov analyzed the five countries with the
highest greenhouse gas emissions (i.e., China, India, Iran, Indonesia, and South Africa) and
discovered that it is easy for the industries with overseas investment to receive the transfer
of cleaning technology and the implementation environmental management. This discov-
ery can facilitate the sustainable development in China to a certain extent [
10
]. Charfeddine
and Kahia employed a panel vector autoregressive model to study the environment of
24 countries in the Middle East and Northern Africa; although industrial development and
transfer were found to have a positive effect on environmental governance, the effect was
minor [
11
]. However, international industrial transitions may nonlinearly influence the
environment of developing countries. This finding is consistent with that of Doytch and
Uctum [12], Liang [13], and Wei et al. [14].
Achieving sustainability and improving citizens’ health and quality of life are the
main objectives of any government [
15
–
17
]. Studies have indicated that international
industrial transfers have considerably differing environmental effects on different countries.
Scholars have focused on the environmental effects of industrial transfer within countries
or specific regions. Yoon and Nadvi [
18
] analyzed the industrial transfer performed by the
Korean brand Banwol-Sihwa and revealed that through industry clusters, high ecological
collectivism efficiency could be achieved and environmental pollution could be reduced. A
study conducted on Latin America indicated that domestic industrial transfer is conducive
to improving environmental quality [
9
]. However, studies on the effect of industrial transfer
between Chinese provinces or regions have been inconsistent. Some scholars have posited
that industrial transfer is conducive to improving environmental quality. Sun et al. [
19
]
proposed that the transfer of carbon emissions among Chinese industries facilitates the
reduction of carbon emissions, thus having positive environmental effects. Wang et al.
adopted the country perspective and proposed that under the influence of environmental
policies, industrial transfer has had a positive environmental effect [6].
Yang and Li argued that on a provincial level, improving environmental standards
reduces the environmental pollution caused by industrial clusters [
20
]. Wang et al. [
21
]
investigated industrial transfer within the Beijing-Tianjin-Hebei metropolitan area and
discovered that under the influence of environmental policies, industrial transfer increased
industrial energy consumption efficiency and reduced environmental pollution [
22
]. How-
ever, other scholars have discovered that industrial transfer in China exacerbated environ-
mental pollution in developed regions. Hu et al. investigated the industrial transfer of

Sustainability 2021,13, 12128 3 of 19
pollution-intensive industries in China between 2007 and 2016, revealing that industrial
transfer resulted in pollution transfer [
23
]. Yin et al. investigated the relationship between
economic development and the environment of eight economic regions in China during
an industrial transfer process and discovered that industrial transfer increased the envi-
ronmental stress and pollution levels in the host regions [
24
]. Scholars researching the
effect of industrial transfer of pollution-intensive industries on urban clusters [
25
,
26
] and
Jiangsu [
27
] have derived similar conclusions. Furthermore, several scholars have reported
that different types of industrial transfer exert varying environmental influences [
28
],
and that industrial transfer under different economic development standards generates
differing environmental effects [29–31].
The literature review indicates that Chinese and worldwide scholars have researched
the effect of industrial transfer on the environment in various countries and regions,
and their findings indicate varying influences of industrial transfer on the environment.
In studies on industrial transfer, countries and regions with considerable differences in
economic development, industrial structure, and environmental policies have generally
been researched. However, studies discussing industrial transfer under these conditions
must include discussion on the effect of industrial transfer on the environment. The
environmental effects of industrial transfer can be classified into scale, composition, and
technology effects [32].
The scale effect refers to decreased environmental quality due to increased indus-
trial production from interregional industrial transfer. The composition effect is defined
as a change in environmental quality caused by a change in the industrial structure as
a result of industrial transfer. For a fixed total production quantity, regions in which
pollution-intensive industries account for a greater proportion of all industry have poorer
environmental quality. Finally, the technology effect refers to a change in regional pro-
duction technology and pollution prevention technology caused by industrial transfer.
These changes, under a fixed production value, create differences in environmental quality
among regions of environmental transfer. Few studies have investigated the environmental
effects of interprovincial or interregional industrial transfer between regions with similar
economic development, industry structure, and environmental policies.
Provincial regions with smaller differences in industrial foundation and structure
have more consistent government policies on environmental protection and governance.
This study does not consider the development of regional industries and instead discusses
differences in the industrial transfer for several regions, thereby detailing the transfer
of industrial corporations and pollution generation in the industrial transfer process.
The study findings are conducive to exploring industrial development conditions and
environment policies, identifying patterns and features in regional industrial transfer, and
understanding how coordinated regional development enhances environmental effects.
The findings will thus be of help when establishing industry transfer policies for sustainable
regional development.
In computations of the amount of pollution generated by industrial transfer, the pollu-
tion caused by the development of existing industries in the host region should be excluded
because such development in each prefecture-level city may have resulted in changes to the
amount of pollution generated. When industrial development is conducted under specific
conditions, changes in production rate are correlated with changes in production output.
In the present study, the average technology level of each prefecture-level city was set
as equal to that of Jiangsu overall. Technology level determines pollution intensity; there-
fore, the pollution intensity was set as equal to that generated by industrial development in
Jiangsu. The industrial transfer is directional, and changes in output value can only show
that the pattern of regional industrial development has changed. This is due to the transfer
of industries between different regions. This study is conducted under the conditions of an
open economy, without considering the impact of foreign capital inflow and the entry of
enterprises from other regions.

Sustainability 2021,13, 12128 4 of 19
2. Research Region and Model Construction
2.1. Research Region
Industrial environmental pollution endangers civilians’ health. Key sources of envi-
ronmental pollution include the processing, manufacturing, use, and recycling processes of
industries. China is the world’s largest production and consumption country [
33
]. Jiangsu,
located on the eastern coast of China and downstream of the Yangtze River, is situated in
the Yangtze River Economic Zone, which comprises 13 provinces (Figure 1).
Sustainability 2021, 13, x FOR PEER REVIEW 4 of 20
only show that the pattern of regional industrial development has changed. This is due to
the transfer of industries between different regions. This study is conducted under the
conditions of an open economy, without considering the impact of foreign capital inflow
and the entry of enterprises from other regions.
2. Research Region and Model Construction
2.1. Research Region
Industrial environmental pollution endangers civilians’ health. Key sources of envi-
ronmental pollution include the processing, manufacturing, use, and recycling processes
of industries. China is the world’s largest production and consumption country [33].
Jiangsu, located on the eastern coast of China and downstream of the Yangtze River, is
situated in the Yangtze River Economic Zone, which comprises 13 provinces (Figure 1).
Jiangsu has the highest gross domestic production (GDP), comprehensive competi-
tiveness, and development of life index among all provinces in China; it thus has the high-
est overall development standards and economic activity in the country [34]. In 2019,
Jiangsu’s GDP was CN¥9.96 trillion, 6.1% higher than that in 2018. Because of continuous
economic structure optimization and the replacement of old growth drivers with new
ones, Jiangsu’s secondary industry exhibited 5.9% growth in 2019. The province’s elec-
tronics, medicine, computation, and instrumentation industries exhibited 69.0%, 33.8%,
23.7%, and 79.5% growth, respectively.
Jiangsu’s high-tech industry exhibited 6.8% growth in 2019, which was 0.6% higher
than the growth rate of industries above the designated size and contributed to the growth
of the added value of such industries by 23.8%. In particular, strategic emerging industries
and high-tech industries comprised 32.8% and 44.4% of the above-designated size indus-
tries, respectively, and are thus suitable as a basis for analyzing high-quality development.
Figure 1. Position of Jiangsu.
Regarding disadvantages, Jiangsu has a shortage of natural resources and depends
on input of coal, oil, natural gas, and water. Jiangsu’s well-developed water network pri-
marily consists of cross-border water resources; therefore, the province has a shortage of
Figure 1. Position of Jiangsu.
Jiangsu has the highest gross domestic production (GDP), comprehensive competitive-
ness, and development of life index among all provinces in China; it thus has the highest
overall development standards and economic activity in the country [
34
]. In 2019, Jiangsu’s
GDP was CN
¥
9.96 trillion, 6.1% higher than that in 2018. Because of continuous economic
structure optimization and the replacement of old growth drivers with new ones, Jiangsu’s
secondary industry exhibited 5.9% growth in 2019. The province’s electronics, medicine,
computation, and instrumentation industries exhibited 69.0%, 33.8%, 23.7%, and 79.5%
growth, respectively.
Jiangsu’s high-tech industry exhibited 6.8% growth in 2019, which was 0.6% higher
than the growth rate of industries above the designated size and contributed to the growth
of the added value of such industries by 23.8%. In particular, strategic emerging industries
and high-tech industries comprised 32.8% and 44.4% of the above-designated size indus-
tries, respectively, and are thus suitable as a basis for analyzing high-quality development.
Regarding disadvantages, Jiangsu has a shortage of natural resources and depends
on input of coal, oil, natural gas, and water. Jiangsu’s well-developed water network
primarily consists of cross-border water resources; therefore, the province has a shortage of
high-quality water. In 2018, the water demand per capita was 470.6 m
3
, 1971.7 m
3
less than
the national average. In 2018, Jiangsu’s total water pollution emissions, 5.839 billion tons,
were the second highest nationwide. Relative to the recorded water pollution emissions
in 2017, this was 1.51% growth. Therefore, given its high-quality economic development,
determining how Jiangsu can continue to optimize its economic structure and replace
its old growth drivers with new ones to enhance the ecological environment is crucial,
particularly in relation to enhancing water-related environment quality.

Sustainability 2021,13, 12128 5 of 19
The researchers selected Jiangsu as the research target for three reasons: (1) Jiangsu
has a shortage of water resources; (2) industry in southern Jiangsu and northern Jiangsu
is currently in a state of transition and optimization; (3) the economic development, envi-
ronmental regulations, and external environment of the province are consistent across the
province. By using Jiangsu as the research target, the researchers could more effectively
quantify the environmental effect of industrial transfer in the high-quality economic devel-
opment process and devise more effective responses for addressing environmental quality
changes caused by high-quality economic development.
2.2. Subsection
In this study, the measurement model quotes He, Zhou and Zhang industrial transfer
and its environmental effect for empirical analysis [4].
Regarding notation, the previous year represents the baseline, and
γt−1,ij
and
γt,ij
denote the industrial production value of industry jin prefecture-level city iat time points
t−
1 and
t
, respectively. The industrial growth rate of each prefecture-level city is set as
equal to that of Jiangsu, thus γ(0)t1ij =.
γtj (0 represents the hypothetical situation before
the matrix conversion and “
·
” represents the growth rate). Accordingly, the production
value is calculated using
γ(0)t,ij =γt−1,i j ·(
1
+.
γtj )
. Therefore, the total production
value of prefecture-level city iduring period twhen industrial transfer does not occur is
γ(0)t,i=∑jγ(0)t,ij
. The pollution intensity of industry jduring period tis equal to the
ratio of the amount of pollution generated to the total industrial production value, which
is represented as
τt,j=Pt,j/γt,j
. In the equation,
Pt,j
represents the amount of pollution
generated by industry jin period t. Pollution intensity is determined by technology level;
the pollution intensity of each city is set as equal to that of the industries in Jiangsu.
Therefore, the amount of pollution generated by industry jof prefecture-level city iduring
period t
−
1 is
τt−1,j·γt−1,ij
; the pollution generated by industry jof prefecture-level city i
during period twhen industrial transfer does not occur is τt,j·γ(0)t,ij.
Accordingly, the change in the amount of pollution generated in prefecture-level city i
when industrial transfer does not occur is calculated using
∆P(0)t,i=∑jτt,j·γ(0)t,ij −∑j(τt−1,j·γt−1,ij)(1)
This study referenced the environmental factor decomposition model of Grossman [
32
]
to decompose Equation (1) into the following:
∆P(0)t,i≈(γ(0)t,i−γt−1,i)∑jτt,j·γ(0)t,ij
γ(0)t1i+γ(0)t,i·∑jτt,j·γ(0)t,ij
γ(0)t,i−γt−1,ij
γt−1,i
+γ(0)t,i∑j(τt,j−τt−1,j)·γ(0)t,ij
γ(0)t,i=∆P(0)s+∆P(0)c+∆P(0)t
(2)
By using Equation (2), the scale, composition, and technology effects of industrial
growth on the environment can be quantified. The effect of each factor is represented
by the scale, composition, and technology coefficients
∆P(0)s/∆P(
0
)
,
∆P(0)c/∆P(
0
)
, and
∆P(0)t/∆P(0), respectively.
After excluding foreign investment, the production generated by industrial transfer is
computed by deducting the actual production value of each industry in each prefecture-
level city by the corresponding theoretical production value when industrial transfer does
not occur. Therefore,
υt,ij
represents the amount of production generated by industrial
transfer in industry jof city ifrom period t−1 to t, computed as follows:
υt,ij =γt,i j −γ(0)t,ij =γt,i j −γt−1,ij −γt−1,i j
.
γt,j(3)
When
υ<
0 and
υ>
0, prefecture-level city itransfers out and in jindustries, respec-
tively. The number of industries transferred in and out of prefecture-level city iduring

Sustainability 2021,13, 12128 6 of 19
period tis represented as
It,i=∑jυij (υij >
0
)
and
Et,i=∑j

υij 

(υij <0)
, respectively;
υt,ij
is computed as follows:
υt,ij =γt,i j −γ(0)t,ij =∑iγt,i j
(γt,ij −γ(0)t,ij )
∑iγt,ij =∑iγt,ijγt,i j
∑iγt,ij −γt−1,i j·(1+.
γt,j)
∑iγt,ij 
=∑iγt,ij ·γt,i j
∑iγt,ij −γt−1,i j·(1+.
γt,j)
(∑iγt−1,ij )·(1+.
γt,j)=∑iγt,ij ·γt,i j
∑iγt,ij −γt−1,i j
(∑iγt−1,ij )
(4)
The net industry transfer is represented as
υt,i=∑jυij
. Accordingly, the number of
transferred industries jin prefecture-level city iis equal to the difference in the share of
industry jin prefecture-level city iin the province before and after the transfer multiplied
by the total production value of industry jafter the transfer was completed. The baseline
condition of prefecture-level city ibefore the industrial transfer in the current year is
determined by the industrial structure of said city after the industrial transfer in the
previous year. The computed result is equal to the industrial transfer result computed
using the relative market share formula.
Therefore, the amount of pollution transfer of industry jin prefecture-level city i
during period tis computed using
ρt,ij =υt,i j ·τt,j
, in which
τt,j
represents the pollution
intensity of industry jin period tand
υt,ij
represents the total pollution generated by
industrial transfer. Therefore, the amount of pollution transfer caused by industrial transfer
in prefecture-level city iduring period tis ∆P(ind f ix )t,i=∑jρt,ij.
The total amount of pollution generated due to industrial transfer, calculated using
the number of transferred industries, is
∆P(ind f i x,im)t,i=∑jυt,ij ·τt,j,(υij >0) = It1i∑j
υt,ij
It,i
·τt,j=It,i·AIt,i,(υij >0)(5)
The total pollution generated is calculated using the following equation:
∆P(ind f i x,em)t,i=∑j|υt,ij | · τt,j,(υt,ij <0) = Et,i∑j
υt,ij
Et,i
·τt,j=Et,i·AEt,i,(υij <0)(6)
where
It,i
and
Et,i
represent the GDP generated by industrial transfer in and out of
prefecture-level city i, respectively, and
AIt,i
and
AEt,i
represent the pollution coefficient
generated by industrial transfer in and out, respectively. Accordingly, the total pollution
transfer of city iis
∑t∆P(ind f i x)t,i=∑t∑jρt,ij
, in which the total import and export
pollution are ∑t∆P(ind f i x,im)t,iand ∑t∆P(in d f ix,em)t,i, respectively.
After industrial transfer, the change in the amount of pollution generated by prefecture-
level city iis calculated as follows:
∑t∆P(tran)t,i=Pt,i−Pt−1,i−∆P(0)t,i(7)
Equation (7) represents the amount of pollution generated by prefecture-level city
iafter subtracting the amount of pollution generated by the industrial development of
pre-existing industries.
∆P(
0
)
represents the environmental effect of pre-existing industries
due to their growth. In theory, ∆P(inde f ix)t,i=∆P(tran)t,i.
2.3. Data Source and Processing
The data in this study is collected from the Statistical Yearbook of Jiangsu and the
relevant yearbooks of Nanjing, Suzhou, Wuxi, Changzhou, Nantong, Taizhou, Yangzhou,
Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian. The industrial enter-
prise data is consisted of only the data on industries above the designed size; statistical
indices included the prefecture-level city of each industry, industrial output value, in-
dustrial wastewater emission (ten thousand tons), and industry category. Because direct
foreign investment in the analyzed industries increased annually, the effect of direct foreign
investment was not considered in the analysis. Because of differences in industry classifi-

Sustainability 2021,13, 12128 7 of 19
cation standards, this study selected industry classification statistics from the Statistical
Yearbook of Jiangsu between 2006 and 2018 for analysis.
Taking into account that the cost of carbon emissions to environmental pollution is not
limited to Jiangsu Province, it will further spread to East Asia and the world. Water envi-
ronmental pollution has significant regional characteristics, and under strict water quality
monitoring, the cost of water pollution control is mainly determined by the enterprises
commitment which can better reflect who is responsible for water pollution. Therefore,
the environmental pollution in this article mainly refers to the discharge of industrial
wastewater.
3. Industrial Composition Changes and Pollution Transfer in Jiangsu
3.1. Status of Industrial Transfer in Jiangsu
At the time of writing, a consensus had not yet been reached among scholars regarding
the definition of industrial transfer. However, most scholars have defined industrial transfer
as the spatial transfer or movement of a certain industry. Accordingly, this study defined
industrial transfer in Jiangsu to be the growth of each prefecture-level city minus the
estimated growth if industrial transfer were to not have occurred.
3.2. Spatial Characteristics of Industrial Transfer in Jiangsu
To comprehensively analyze the overall trend in industrial transfer in Jiangsu’s
prefecture-level cities during the research period, this study computed the number of
total transferred-in industries (
∑tIt,i
) and transferred-out industries (
∑tEt,i
); the results
are illustrated in Figure 2. Among the prefecture-level cities in Jiangsu between 2006 and
2018, industries mainly transferred out of Suzhou, Wuxi, and Nanjing and transferred to
Xuzhou, Taizhou, and Huaian.
Sustainability 2021, 13, x FOR PEER REVIEW 8 of 20
central Jiangsu and Northern Jiangsu—such as Taizhou, Xuzhou, and Huaian—the num-
ber of industries transferred in far exceeded that of industries transferred out. Most pre-
fecture-level cities with notable changes in industrial structure had more active industrial
transfer, such as Yangzhou, Changzhou, Nanjing, Zhenjiang, and Nantong. However,
Wuxi was unique because it had few transferred-in industries; additionally, the number
of transferred-out industries in Suqian, Lianyungang, and Taizhou was low.
Figure 2. Amount of transfer in and transfer out between 2006 and 2018 for each prefecture-level city in Jiangsu (CN¥100
million). Source: Authors calculation based on the Statistical Yearbook of Jiangsu (2007–2019).
3.3. Characteristics of Transferred Industries
Theories on industrial transfer have assumed that the direction of industrial transfer
is from economic centers to the periphery and outer regions. Additionally, transferred
industries can be categorized as resource- and labor-intensive industries or capital- and
technology-intensive industries. Further details on the transferred-in and transferred-out
industries are provided in the following. Appendix A analyzes four prefecture-level cities
with unique industrial transfer characteristics, namely Nanjing, Changzhou, Suzhou, and
Nantong.
Transferred-out industries in Nanjing were mostly those using mature production
technology. The chemical raw material, metallurgical, and petroleum processing indus-
tries accounted for large shares of Jiangsu’s industrial structure. In particular, the chemical
material, nonferrous metal ore mining, petrochemical, and food manufacturing industries
generated severe pollution [4,17]. The total number and types of transferred-out indus-
tries exceeded those of transferred-in industries. The main transferred-in industry was
that producing instruments, meters, and cultural and clerical machinery products, which
fulfils the requirements for economic culture activities in prefecture-level cities [18].
In Changzhou, more industries were transferred out than in. The city’s transferred-
in industries—other than those manufacturing articles for culture, education, and sport
activities; papermaking and paper products; leather, fur, and feather products; food prod-
ucts—were heavy industries such as those manufacturing electrical machinery and equip-
ment, smelting and pressing ferrous metals, manufacturing chemical materials, and pro-
cessing petroleum. The chemical raw material and ferrous metal smelting and pressing
industries have high pollution intensity. The transferred-out industry were the textile,
Figure 2.
Amount of transfer in and transfer out between 2006 and 2018 for each prefecture-level city in Jiangsu (CN
¥
100 mil-
lion). Source: Authors calculation based on the Statistical Yearbook of Jiangsu (2007–2019).
The data on Jiangsu indicated that in prominent prefecture-level cities in Southern
Jiangsu such as Suzhou, Wuxi, and Changzhou, the transfer out of industry was the
main method of optimizing and upgrading the industry structure, and the number of
transfers in was notably lower than that of transfers out. By contrast, in prefecture-level
cities in central Jiangsu and Northern Jiangsu—such as Taizhou, Xuzhou, and Huaian—

Sustainability 2021,13, 12128 8 of 19
the number of industries transferred in far exceeded that of industries transferred out.
Most prefecture-level cities with notable changes in industrial structure had more active
industrial transfer, such as Yangzhou, Changzhou, Nanjing, Zhenjiang, and Nantong.
However, Wuxi was unique because it had few transferred-in industries; additionally, the
number of transferred-out industries in Suqian, Lianyungang, and Taizhou was low.
3.3. Characteristics of Transferred Industries
Theories on industrial transfer have assumed that the direction of industrial transfer
is from economic centers to the periphery and outer regions. Additionally, transferred
industries can be categorized as resource- and labor-intensive industries or capital- and
technology-intensive industries. Further details on the transferred-in and transferred-out
industries are provided in the following. Appendix Aanalyzes four prefecture-level cities
with unique industrial transfer characteristics, namely Nanjing, Changzhou, Suzhou, and
Nantong.
Transferred-out industries in Nanjing were mostly those using mature production
technology. The chemical raw material, metallurgical, and petroleum processing industries
accounted for large shares of Jiangsu’s industrial structure. In particular, the chemical
material, nonferrous metal ore mining, petrochemical, and food manufacturing industries
generated severe pollution [
4
,
17
]. The total number and types of transferred-out industries
exceeded those of transferred-in industries. The main transferred-in industry was that
producing instruments, meters, and cultural and clerical machinery products, which fulfils
the requirements for economic culture activities in prefecture-level cities [18].
In Changzhou, more industries were transferred out than in. The city’s transferred-in
industries—other than those manufacturing articles for culture, education, and sport activi-
ties; papermaking and paper products; leather, fur, and feather products; food products—
were heavy industries such as those manufacturing electrical machinery and equipment,
smelting and pressing ferrous metals, manufacturing chemical materials, and processing
petroleum. The chemical raw material and ferrous metal smelting and pressing industries
have high pollution intensity. The transferred-out industry were the textile, rubber, and
plastic product industries and heavy industries in which severe environmental pollution
is generated, such as those manufacturing general and special purpose machinery and
smelting and pressing nonferrous metals.
Far fewer industries were transferred in than out. Those transferred out were primarily
heavy industries that generate severe pollution. However, the transfer-in and transfer-
out conditions of Nantong were discovered to differ from those of Jiangsu overall; fewer
industries were transferred out of industries in Nantong than transferred in, and most of
the transferred-in industries were heavy industries.
4. Discussion
4.1. Differences in Spatial Pattern of Pollution Emissions Caused by Industrial Transfer
Each prefectural-level city has a different industrial structure and industrial growth
rate, and the pollution emission intensity of each industry is different. Therefore, to
determine the spatial pattern characteristics of pollution emissions caused by industrial
transfer, the researchers investigated the environmental effects caused by industrial growth
in each industry category. Figures 3and 4depict the total industrial wastewater emission
and pollution intensity for key industries in 2006, 2012, and 2018.
Figure 3indicates that differences existed in the pollution emissions of each industry
during the research period. In particular, the pollution emissions of the chemical raw
material, electric power and heat power production and supply, paper manufacturing,
petroleum processing, medicine manufacturing, food manufacturing, and nonferrous metal
smelting and pressing industries decreased over the entire period. However, the pollution
emissions of the beverage manufacturing, coal mining, metal product manufacturing, and
agricultural product food processing industries increased.

Sustainability 2021,13, 12128 9 of 19
Sustainability 2021, 13, x FOR PEER REVIEW 9 of 20
rubber, and plastic product industries and heavy industries in which severe environmen-
tal pollution is generated, such as those manufacturing general and special purpose ma-
chinery and smelting and pressing nonferrous metals.
Far fewer industries were transferred in than out. Those transferred out were primar-
ily heavy industries that generate severe pollution. However, the transfer-in and transfer-
out conditions of Nantong were discovered to differ from those of Jiangsu overall; fewer
industries were transferred out of industries in Nantong than transferred in, and most of
the transferred-in industries were heavy industries.
4. Discussion
4.1. Differences in Spatial Pattern of Pollution Emissions Caused by Industrial Transfer
Each prefectural-level city has a different industrial structure and industrial growth
rate, and the pollution emission intensity of each industry is different. Therefore, to deter-
mine the spatial pattern characteristics of pollution emissions caused by industrial trans-
fer, the researchers investigated the environmental effects caused by industrial growth in
each industry category. Figures 3 and 4 depict the total industrial wastewater emission
and pollution intensity for key industries in 2006, 2012, and 2018.
Manufacture of chemical raw
material and chemical products
Manufacture of textiles
Production and supply of
electric power and heat power
Smelting and pressing of
ferrous metals
Manufacture of paper
and paper products
Processing of petroleum, coking,
and processing of nucleus fuel
Manufacture of medicines
Manufacture of chemical fibers
Manufacture of metal products
Manufacture of beverages
Manufacture of food
Manufacture of nonmetallic
mineral products
Processing of food from
agricultural products
The coal mining and washing
Manufacture of leather, fur,
feather, and related products
Nonferrous metal ore mining
Nonferrous metal ore mining
Ferrous metal ore mining
10 kilo-tons
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
Figure 3. Pollution emissions of key industries in 2006, 2012, and 2018 (industrial wastewater). Source: Authors calculation
based on the Statistical Yearbook of Jiangsu (2007, 2013, and 2019).
Figure 3 indicates that differences existed in the pollution emissions of each industry
during the research period. In particular, the pollution emissions of the chemical raw ma-
terial, electric power and heat power production and supply, paper manufacturing, pe-
troleum processing, medicine manufacturing, food manufacturing, and nonferrous metal
smelting and pressing industries decreased over the entire period. However, the pollution
emissions of the beverage manufacturing, coal mining, metal product manufacturing, and
agricultural product food processing industries increased.
The pollution emissions of the textile; leather, fur, feather, and related product; and
nonferrous metal smelting and pressing industries increased between 2006 and 2012 but
Figure 3.
Pollution emissions of key industries in 2006, 2012, and 2018 (industrial wastewater). Source: Authors calculation
based on the Statistical Yearbook of Jiangsu (2007, 2013, and 2019).
Sustainability 2021, 13, x FOR PEER REVIEW 10 of 20
then decreased between 2012 and 2018. The pollution emissions of the chemical fiber man-
ufacturing, nonmetallic mineral product manufacturing, and ferrous metal smelting and
pressing industries also had a turning point in 2012. However, the pollution emissions of
these three industries decreased between 2006 and 2012 but then increased between 2012
and 2018.
Figure 4 depicts the pollution intensity for each industry in 2006, 2012, and 2018. The
pollution intensity of all industries other than the coal mining and washing, ferrous metal
ore mining, and agricultural product processing industries decreased within the research
period. The computed pollution intensity indicated that the nonferrous metal ore mining,
paper manufacturing, electric power and heat power production and supply, chemical
raw material manufacturing, food manufacturing, medicine manufacturing, and textile
industries had the highest pollution intensity.
In 2006, the wastewater produced by the chemical raw material and chemical product
manufacturing industry was 617.7972 metric tons, 24% of the total industrial wastewater
of Jiangsu. In addition, the textile, electrical power and heat power production and sup-
ply, ferrous metal smelting and pressing, and paper manufacturing industries produced
considerable industrial wastewater. The combined wastewater of these seven industries
and the chemical raw material and chemical product manufacturing industry constituted
more than 80% of the industrial wastewater produced in Jiangsu.
Nonferrous metal ore mining
Manufacture of paper
and paper products
Production and supply of
electric power and heat power
Manufacture of food
Manufacture of chemical raw
material and chemical products
Manufacture of medicines
Smelting and pressing of
ferrous metals
Manufacture of textiles
Processing of petroleum, coking,
and processing of nucleus fuel
Manufacture of beverages
The coal mining and washing
Manufacture of chemical fibers
Ferrous metal ore mining
Manufacture of nonmetallic
mineral products
Processing of food from
agricultural products
Manufacture of metal products
Nonferrous metal ore mining
Manufacture of leather, fur,
feather, and related products
10 kilo-tons per 100 million yuan
0
5
10
15
20
25
30
35
40
Figure 4. Pollution intensity of key pollution industries in 2006, 2012, and 2018 (industrial wastewater). Source: Authors
calculation based on the Statistical Yearbook of Jiangsu (2007, 2013, and 2019).
The difference in the environmental effect caused by industrial growth was divided
into industrial scale, structure, and differences in pollution intensity. By hypothesizing
that technological development within Jiangsu did not vary spatially, the spatial differ-
ences in pollution intensity and pollution emissions could be ignored.
Because environmental pollution increases with production, when the production
conditions and industrial structure are set, an increase in production results in increased
pollution. Therefore, the difference in the spatial distribution of environmental effects
caused by industrial growth would be influenced by differences in the industrial structure
of the city as well as the industrial structure of the city at baseline.
Figure 4.
Pollution intensity of key pollution industries in 2006, 2012, and 2018 (industrial wastewater). Source: Authors
calculation based on the Statistical Yearbook of Jiangsu (2007, 2013, and 2019).
The pollution emissions of the textile; leather, fur, feather, and related product; and
nonferrous metal smelting and pressing industries increased between 2006 and 2012 but
then decreased between 2012 and 2018. The pollution emissions of the chemical fiber
manufacturing, nonmetallic mineral product manufacturing, and ferrous metal smelting
and pressing industries also had a turning point in 2012. However, the pollution emissions
of these three industries decreased between 2006 and 2012 but then increased between 2012
and 2018.

Sustainability 2021,13, 12128 10 of 19
Figure 4depicts the pollution intensity for each industry in 2006, 2012, and 2018. The
pollution intensity of all industries other than the coal mining and washing, ferrous metal
ore mining, and agricultural product processing industries decreased within the research
period. The computed pollution intensity indicated that the nonferrous metal ore mining,
paper manufacturing, electric power and heat power production and supply, chemical
raw material manufacturing, food manufacturing, medicine manufacturing, and textile
industries had the highest pollution intensity.
In 2006, the wastewater produced by the chemical raw material and chemical product
manufacturing industry was 617.7972 metric tons, 24% of the total industrial wastewater
of Jiangsu. In addition, the textile, electrical power and heat power production and
supply, ferrous metal smelting and pressing, and paper manufacturing industries produced
considerable industrial wastewater. The combined wastewater of these seven industries
and the chemical raw material and chemical product manufacturing industry constituted
more than 80% of the industrial wastewater produced in Jiangsu.
The difference in the environmental effect caused by industrial growth was divided
into industrial scale, structure, and differences in pollution intensity. By hypothesizing that
technological development within Jiangsu did not vary spatially, the spatial differences in
pollution intensity and pollution emissions could be ignored.
Because environmental pollution increases with production, when the production
conditions and industrial structure are set, an increase in production results in increased
pollution. Therefore, the difference in the spatial distribution of environmental effects
caused by industrial growth would be influenced by differences in the industrial structure
of the city as well as the industrial structure of the city at baseline.
Using 2018 as an example, and the aforementioned method for computation, Figure 5
illustrates the environmental effect
∆P(0)t1i
caused by industrial growth between 2015 and
2018 in each city. The ratio of environmental effect with structural component coefficient
was ∆P(0)s/∆P(0)t1i.
Sustainability 2021, 13, x FOR PEER REVIEW 11 of 20
Using 2018 as an example, and the aforementioned method for computation, Figure
5 illustrates the environmental effect
1
(0)
ti
P
Δ caused by industrial growth between 2015
and 2018 in each city. The ratio of environmental effect with structural component coeffi-
cient was
1
(0) / (0)
s
ti
PP
ΔΔ
.
Figure 5. Environmental effect and structural component coefficients attributable to the industrial
growth for each prefecture-level city between 2015 and 2018. Source: Authors calculation based on
the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Changzhou, Nantong, Taizhou, Yangzhou,
Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2016 and 2019).
The size of the environmental effect was closely related to the overall economic de-
velopment and industrial structure of each prefecture-level city. Xuzhou, Nanjing, and
Suzhou were the cities with the highest GDP in Jiangsu; combined, they generated 86.88
million tons of industrial wastewater due to industrial growth. Zhenjiang, Huaian, Yan-
cheng, and Yangzhou also had considerable wastewater emissions due to industrial
growth; these prefecture-level cities had notably high GDP, which was strongly influ-
enced by the proportion of highly polluting industries in their industrial structure. For the
prefecture-level cities that had an increase in GDP, a component coefficient [
1
(0) / (0)
s
ti
PP
ΔΔ
] higher and lower than 0 indicated that the city’s industrial structure
had a negative and positive effect, respectively, on the environment. Between 2015 and
2017, most prefecture-level cities had a negative component coefficient; only Wuxi and
Nantong had a positive component coefficient. Thus, the prefecture-level cities having
more industries with greater pollution intensity exhibited faster growth.
4.2. Differences in Spatial Characteristics of Pollution Emissions Caused by Industrial Transfer
To analyze the total pollution transfer during the research period, the amounts of
pollution transferred in [
1
(,)
tti
indfix im
P
Δ] and out [
1
(,)
tti
indfix em
P
Δ] between
2006 and 2018 was calculated. However, because various industries were inspected and
the pollution intensity of each industry varied, this study collected pollution transfer sta-
tistics for industries above the designed size in each region between 2006 and 2018.
Figure 6 indicates that among Jiangsu’s prefecture-level cities, Suzhou, Wuxi, Nan-
jing, and Changzhou had the highest amount of transferred-out pollution. Most of these
cities are prosperous and have undergone notable changes to their industrial structure.
Figure 5.
Environmental effect and structural component coefficients attributable to the industrial
growth for each prefecture-level city between 2015 and 2018. Source: Authors calculation based
on the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Changzhou, Nantong, Taizhou, Yangzhou,
Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2016 and 2019).
The size of the environmental effect was closely related to the overall economic devel-
opment and industrial structure of each prefecture-level city. Xuzhou, Nanjing, and Suzhou
were the cities with the highest GDP in Jiangsu; combined, they generated 86.88 million
tons of industrial wastewater due to industrial growth. Zhenjiang, Huaian, Yancheng, and
Yangzhou also had considerable wastewater emissions due to industrial growth; these

Sustainability 2021,13, 12128 11 of 19
prefecture-level cities had notably high GDP, which was strongly influenced by the pro-
portion of highly polluting industries in their industrial structure. For the prefecture-level
cities that had an increase in GDP, a component coefficient [
∆P(0)s/∆P(0)t1i
] higher and
lower than 0 indicated that the city’s industrial structure had a negative and positive effect,
respectively, on the environment. Between 2015 and 2017, most prefecture-level cities
had a negative component coefficient; only Wuxi and Nantong had a positive component
coefficient. Thus, the prefecture-level cities having more industries with greater pollution
intensity exhibited faster growth.
4.2. Differences in Spatial Characteristics of Pollution Emissions Caused by Industrial Transfer
To analyze the total pollution transfer during the research period, the amounts of
pollution transferred in [
∑t∆P(ind f i x,im)t1i
] and out [
∑t∆P(ind f i x,em)t1i
] between 2006
and 2018 was calculated. However, because various industries were inspected and the
pollution intensity of each industry varied, this study collected pollution transfer statistics
for industries above the designed size in each region between 2006 and 2018.
Figure 6indicates that among Jiangsu’s prefecture-level cities, Suzhou, Wuxi, Nanjing,
and Changzhou had the highest amount of transferred-out pollution. Most of these cities
are prosperous and have undergone notable changes to their industrial structure.
Sustainability 2021, 13, x FOR PEER REVIEW 12 of 20
Figure 6. Pollution transfer caused by industrial transfer for each prefecture-level city between 2006
and 2018. Source: Authors calculation based on the Statistical Yearbook of Jiangsu (between 2007
and 2019).
Cities with high levels of transferred-in pollution were Xuzhou, Taizhou, Nantong,
Lianyungang, and Yangzhou. Since implementation of the reform and opening-up policy,
heavy industries have remained the main component of industry in Xuzhou. As a key
province for the transfer in of industry, Xuzhou has adjusted its industrial structure and
attracted various highly polluting industries, namely the wood manufacturing, chemical
raw material, textile, nonmetallic processing, ferrous metal smelting and processing, and
instrumentation manufacturing industries. Because Xuzhou, Lianyungang, Yancheng,
and Suqian have been the recipients of industrial transfer in the Jiangnan region, the trans-
ferred-in industries of these cities had high pollution emissions.
Overall, in prefecture-level cities such as Nanjing, Wuxi, and Suzhou, the transferred-
in pollution load was notably lower than the transferred-out pollution load. This indicated
that the industrial structure of these cities underwent a greater change.
Figure 7 presents the net transfer of pollution generated for each city, which was
computed by subtracting the transferred-in pollution load from the transferred-out pollu-
tion load. The spatial characteristics of pollution transfer were revealed to be hierarchical.
In the first level, prefecture-level cities in Southern Jiangsu—such as Suzhou, Wuxi, and
Nanjing—exhibited a net transfer out of pollution load, indicating that in these cities, less
pollution load was transferred in than out. In the second level, prefecture-level cities in
Central Jiangsu and Northern Jiangsu—such as Taizhou, Xuzhou, and Yancheng—had a
net transfer in of pollution load. Comparing the industrial transfer characteristics of cites
in the two levels revealed that those in the second level had relatively less industrial trans-
fer than those in the first level.
Figure 6.
Pollution transfer caused by industrial transfer for each prefecture-level city between 2006
and 2018. Source: Authors calculation based on the Statistical Yearbook of Jiangsu (between 2007 and
2019).
Cities with high levels of transferred-in pollution were Xuzhou, Taizhou, Nantong,
Lianyungang, and Yangzhou. Since implementation of the reform and opening-up policy,
heavy industries have remained the main component of industry in Xuzhou. As a key
province for the transfer in of industry, Xuzhou has adjusted its industrial structure and
attracted various highly polluting industries, namely the wood manufacturing, chemical
raw material, textile, nonmetallic processing, ferrous metal smelting and processing, and
instrumentation manufacturing industries. Because Xuzhou, Lianyungang, Yancheng,
and Suqian have been the recipients of industrial transfer in the Jiangnan region, the
transferred-in industries of these cities had high pollution emissions.
Overall, in prefecture-level cities such as Nanjing, Wuxi, and Suzhou, the transferred-
in pollution load was notably lower than the transferred-out pollution load. This indicated
that the industrial structure of these cities underwent a greater change.
Figure 7presents the net transfer of pollution generated for each city, which was
computed by subtracting the transferred-in pollution load from the transferred-out pollu-

Sustainability 2021,13, 12128 12 of 19
tion load. The spatial characteristics of pollution transfer were revealed to be hierarchical.
In the first level, prefecture-level cities in Southern Jiangsu—such as Suzhou, Wuxi, and
Nanjing—exhibited a net transfer out of pollution load, indicating that in these cities, less
pollution load was transferred in than out. In the second level, prefecture-level cities in
Central Jiangsu and Northern Jiangsu—such as Taizhou, Xuzhou, and Yancheng—had a
net transfer in of pollution load. Comparing the industrial transfer characteristics of cites in
the two levels revealed that those in the second level had relatively less industrial transfer
than those in the first level.
Sustainability 2021, 13, x FOR PEER REVIEW 13 of 20
Figure 7. Net transfer of pollution generated for each prefecture-level city between 2006 and 2018. Source: Authors calcu-
lation based on the Statistical Yearbook of Jiangsu (between 2007 and 2019).
4.3. Differences in Pollution Load Caused by Industrial Transfer
Different industries have differing pollution intensity. This study specifically ana-
lyzed the highly polluting industries, namely the textile, papermaking and paper product
manufacturing, and chemical raw material and chemical product manufacturing indus-
tries. However, because of limitations in the collected data, only data on the pollution
transfer conditions of each industry between 2011 and 2018 were included.
The textile industry is the traditional major industry of Jiangsu and a major source of
pollution of the province’s water bodies. Figure 8 indicates that pollution was mainly trans-
ferred out of Suzhou, Nanjing, Wuxi, and Suqian and transferred into Xuzhou, Yancheng, and
Huaian. The change in the industrial structure of each prefecture-level city was observed from
pollution transfer conditions. For example, a considerable portion of Suzhou’s pollution-in-
tensive industries was transferred out to Southern Jiangsu, which now has a cluster of various
pollution-intensive industries due to its advantageous geographic conditions. However, be-
cause of rapid economic development in the region, pollution problems have increased resi-
dents’ awareness of industrial pollution risks and knowledge of environmental protection.
Furthermore, government agencies have endeavored to establish and implement environ-
mental protection policies. By actively implementing policies to change its industrial structure,
Suzhou has prompted pollution-intensive industries to transfer out or shut down. The textile
industry is also a pollution-intensive industry that should transfer out.
Figure 7.
Net transfer of pollution generated for each prefecture-level city between 2006 and 2018. Source: Authors
calculation based on the Statistical Yearbook of Jiangsu (between 2007 and 2019).
4.3. Differences in Pollution Load Caused by Industrial Transfer
Different industries have differing pollution intensity. This study specifically analyzed
the highly polluting industries, namely the textile, papermaking and paper product man-
ufacturing, and chemical raw material and chemical product manufacturing industries.
However, because of limitations in the collected data, only data on the pollution transfer
conditions of each industry between 2011 and 2018 were included.
The textile industry is the traditional major industry of Jiangsu and a major source of
pollution of the province’s water bodies. Figure 8indicates that pollution was mainly trans-
ferred out of Suzhou, Nanjing, Wuxi, and Suqian and transferred into Xuzhou, Yancheng,
and Huaian. The change in the industrial structure of each prefecture-level city was ob-
served from pollution transfer conditions. For example, a considerable portion of Suzhou’s
pollution-intensive industries was transferred out to Southern Jiangsu, which now has
a cluster of various pollution-intensive industries due to its advantageous geographic
conditions. However, because of rapid economic development in the region, pollution
problems have increased residents’ awareness of industrial pollution risks and knowledge
of environmental protection. Furthermore, government agencies have endeavored to estab-
lish and implement environmental protection policies. By actively implementing policies
to change its industrial structure, Suzhou has prompted pollution-intensive industries to
transfer out or shut down. The textile industry is also a pollution-intensive industry that
should transfer out.

Sustainability 2021,13, 12128 13 of 19
Sustainability 2021, 13, x FOR PEER REVIEW 13 of 20
Figure 7. Net transfer of pollution generated for each prefecture-level city between 2006 and 2018. Source: Authors calcu-
lation based on the Statistical Yearbook of Jiangsu (between 2007 and 2019).
4.3. Differences in Pollution Load Caused by Industrial Transfer
Different industries have differing pollution intensity. This study specifically ana-
lyzed the highly polluting industries, namely the textile, papermaking and paper product
manufacturing, and chemical raw material and chemical product manufacturing indus-
tries. However, because of limitations in the collected data, only data on the pollution
transfer conditions of each industry between 2011 and 2018 were included.
The textile industry is the traditional major industry of Jiangsu and a major source of
pollution of the province’s water bodies. Figure 8 indicates that pollution was mainly trans-
ferred out of Suzhou, Nanjing, Wuxi, and Suqian and transferred into Xuzhou, Yancheng, and
Huaian. The change in the industrial structure of each prefecture-level city was observed from
pollution transfer conditions. For example, a considerable portion of Suzhou’s pollution-in-
tensive industries was transferred out to Southern Jiangsu, which now has a cluster of various
pollution-intensive industries due to its advantageous geographic conditions. However, be-
cause of rapid economic development in the region, pollution problems have increased resi-
dents’ awareness of industrial pollution risks and knowledge of environmental protection.
Furthermore, government agencies have endeavored to establish and implement environ-
mental protection policies. By actively implementing policies to change its industrial structure,
Suzhou has prompted pollution-intensive industries to transfer out or shut down. The textile
industry is also a pollution-intensive industry that should transfer out.
Figure 8.
Pollution transfer for the textile industry in each prefecture-level city between 2011 and 2018. Source: Authors
calculation based on the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Changzhou, Nantong, Taizhou, Yangzhou, Zhenjiang,
Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2012 and 2019).
The papermaking and paper product manufacturing industry is representative of
pollution-intensive light industries. Figure 9shows that the pollution generated by this
industry was primarily transferred out from Wuxi, Suzhou, and Nanjing and transferred
in to Huaian, Changzhou, Nantong, Yancheng, and Yangzhou. In particular, Huaian had
the greatest amount of transferred-in pollution for the papermaking and paper product
manufacturing industry. From the provincial standpoint, the transferred-in pollution of the
papermaking and paper production manufacturing industry considerably exceeded the
industry’s transferred-out pollution. In addition, a transfer in of pollution was observed in
some cities in Southern Jiangsu.
Sustainability 2021, 13, x FOR PEER REVIEW 14 of 20
Figure 8. Pollution transfer for the textile industry in each prefecture-level city between 2011 and 2018. Source: Authors
calculation based on the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Changzhou, Nantong, Taizhou, Yangzhou, Zhen-
jiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2012 and 2019).
The papermaking and paper product manufacturing industry is representative of
pollution-intensive light industries. Figure 9 shows that the pollution generated by this
industry was primarily transferred out from Wuxi, Suzhou, and Nanjing and transferred
in to Huaian, Changzhou, Nantong, Yancheng, and Yangzhou. In particular, Huaian had
the greatest amount of transferred-in pollution for the papermaking and paper product
manufacturing industry. From the provincial standpoint, the transferred-in pollution of
the papermaking and paper production manufacturing industry considerably exceeded
the industry’s transferred-out pollution. In addition, a transfer in of pollution was ob-
served in some cities in Southern Jiangsu.
− 200
− 100
0
100
200
300
400
500
600
700
800
万
吨
污染量
Nanjing
Wuxi
Xuzhou
Changzhou
Suzhou
Nantong
Lianyungang
Huai'an
Yancheng
Yangzhou
Zhenjiang
Taizhou
Suqian
Amount of pollution
10 kilo-tons
Figure 9. Pollution transfer for the papermaking and paper product manufacturing industry in each prefecture-level city
between 2011 and 2018. Source: Authors calculation based on the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Chang-
zhou, Nantong, Taizhou, Yangzhou, Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2012 and
2019).
The trend in pollution generated by the chemical raw material and chemical product
manufacturing industry was similar to that for the papermaking and paper product man-
ufacturing industry. Figure 10 shows the pollution load of the chemical raw material and
chemical product industry in Nanjing, Suzhou, Wuxi, and Yangzhou, indicating that the
pollution was transferred out because of the transfer out of that industry. Once a main
energy production city in China, Xuzhou has more than 100 years of coal mining history,
which propelled the development of Xuzhou’s classic heavy industry industrial layout
and prompted the city to develop into a major traditional industrial city in Jiangsu. The
constantly changing proportions of the textile, machinery, and chemical industries in the
industrial structure reflect the considerable number of pollution-intensive industries that
have transferred into Xuzhou. The transfers in from the textile and chemical raw material
industries were particularly prominent, bringing considerable pollution as well as eco-
nomic development.
Figure 9.
Pollution transfer for the papermaking and paper product manufacturing industry in each prefecture-level city
between 2011 and 2018. Source: Authors calculation based on the Statistical Yearbook of Nanjing, Suzhou, Wuxi, Changzhou,
Nantong, Taizhou, Yangzhou, Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2012 and 2019).
The trend in pollution generated by the chemical raw material and chemical prod-
uct manufacturing industry was similar to that for the papermaking and paper product
manufacturing industry. Figure 10 shows the pollution load of the chemical raw material

Sustainability 2021,13, 12128 14 of 19
and chemical product industry in Nanjing, Suzhou, Wuxi, and Yangzhou, indicating that
the pollution was transferred out because of the transfer out of that industry. Once a
main energy production city in China, Xuzhou has more than 100 years of coal mining
history, which propelled the development of Xuzhou’s classic heavy industry industrial
layout and prompted the city to develop into a major traditional industrial city in Jiangsu.
The constantly changing proportions of the textile, machinery, and chemical industries in
the industrial structure reflect the considerable number of pollution-intensive industries
that have transferred into Xuzhou. The transfers in from the textile and chemical raw
material industries were particularly prominent, bringing considerable pollution as well as
economic development.
Sustainability 2021, 13, x FOR PEER REVIEW 15 of 20
Figure 10. Pollution transfer for the chemical raw material and chemical product manufacturing industry in each prefec-
ture-level city between 2011 and 2018. Source: Authors calculation based on the Statistical Yearbook of Nanjing, Suzhou,
Wuxi, Changzhou, Nantong, Taizhou, Yangzhou, Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (be-
tween 2012 and 2019).
5. Conclusions and Implications
This study collected data on the pollution load and gross industrial output of large
industries in Jiangsu between 2006 and 2018 to investigate the industrial-transfer-induced
changes in pollution load and spatial characteristics of each industry. After deducting the
environmental pollution generated by the growth of pre-existing industries in each pre-
fecture-level city, the industrial transfer condition and pollution transfer in each prefec-
ture-level city were estimated, and the following conclusions were made.
First, Jiangsu’s prefecture-level cities underwent a volatile change in industrial struc-
ture between 2006 and 2018. During this period, industrial transfer exhibited clear spatial
hierarchical characteristics. Industries mainly transferred out from the most developed
Southern Jiangsu region to its vicinity and then to the Central Jiangsu and Northern
Jiangsu regions.
Second, there existed heterogeneities in the factors including scale, structure, and
technology of the industries of various prefecture-level cities, and accordingly, the scale
effect, structure effect and technology effect also existed in the impact of industrial devel-
opment on the environment, which resulted in significant spatial differences in the degree
of influence of environmental pollution due to the change of industrial structure.
Third, the transfer of pollution intensive industries has led to changes in the indus-
trial structure of the industry transfer-out areas and the industry transfer-in areas, and the
corresponding industrial scale has also changed. Therefore, the transfer of pollution in-
tensive industries shows obvious spatial gradient characteristics. In detail, the cities such
as Suzhou, Wuxi, and Nanjing have reduced the proportion of polluting enterprises in
transfer-out areas and improved the environment due to the transfer out of pollution in-
tensive industries; by contrary, the environment pollution in the transfer-in areas includ-
ing Xuzhou, Huaian, Yancheng, and Taizhou was more severe.
Finally, differences were observed in the destinations of industry and pollution trans-
fer; the textile industry and chemical raw material and chemical products industry mainly
transferred to the Central Jiangsu and Northern Jiangsu regions, whereas the paper in-
dustry resulted in pollution transfer to cities in the Southern Jiangsu region.
Overall, the industrial spatial pattern of Jiangsu has been significantly regulated in
recent years. However, with the regulation of industrial structures, industrial transfer has
also changed the scale, structure, and innovation of related industries in the prefecture-
Figure 10.
Pollution transfer for the chemical raw material and chemical product manufacturing industry in each prefecture-
level city between 2011 and 2018. Source: Authors calculation based on the Statistical Yearbook of Nanjing, Suzhou, Wuxi,
Changzhou, Nantong, Taizhou, Yangzhou, Zhenjiang, Yancheng, Xuzhou, Huaian, Lianyungang, and Suqian (between 2012
and 2019).
5. Conclusions and Implications
This study collected data on the pollution load and gross industrial output of large
industries in Jiangsu between 2006 and 2018 to investigate the industrial-transfer-induced
changes in pollution load and spatial characteristics of each industry. After deduct-
ing the environmental pollution generated by the growth of pre-existing industries in
each prefecture-level city, the industrial transfer condition and pollution transfer in each
prefecture-level city were estimated, and the following conclusions were made.
First, Jiangsu’s prefecture-level cities underwent a volatile change in industrial struc-
ture between 2006 and 2018. During this period, industrial transfer exhibited clear spatial
hierarchical characteristics. Industries mainly transferred out from the most developed
Southern Jiangsu region to its vicinity and then to the Central Jiangsu and Northern Jiangsu
regions.
Second, there existed heterogeneities in the factors including scale, structure, and
technology of the industries of various prefecture-level cities, and accordingly, the scale
effect, structure effect and technology effect also existed in the impact of industrial devel-
opment on the environment, which resulted in significant spatial differences in the degree
of influence of environmental pollution due to the change of industrial structure.
Third, the transfer of pollution intensive industries has led to changes in the indus-
trial structure of the industry transfer-out areas and the industry transfer-in areas, and
the corresponding industrial scale has also changed. Therefore, the transfer of pollution
intensive industries shows obvious spatial gradient characteristics. In detail, the cities such
as Suzhou, Wuxi, and Nanjing have reduced the proportion of polluting enterprises in

Sustainability 2021,13, 12128 15 of 19
transfer-out areas and improved the environment due to the transfer out of pollution inten-
sive industries; by contrary, the environment pollution in the transfer-in areas including
Xuzhou, Huaian, Yancheng, and Taizhou was more severe.
Finally, differences were observed in the destinations of industry and pollution trans-
fer; the textile industry and chemical raw material and chemical products industry mainly
transferred to the Central Jiangsu and Northern Jiangsu regions, whereas the paper industry
resulted in pollution transfer to cities in the Southern Jiangsu region.
Overall, the industrial spatial pattern of Jiangsu has been significantly regulated in
recent years. However, with the regulation of industrial structures, industrial transfer has
also changed the scale, structure, and innovation of related industries in the prefecture-level
cities of Jiangsu. In the initial period of high-quality development, industrial pollution
accompanied with the industrial transfer began to spread to the ecologically fragile areas
of Central and Northern Jiangsu areas. The increase in the scale of pollution intensive
industries inhibited the role of industrial development in promoting the economy, which is
not conducive to the sustainable development of the economy. For this reason, the local
government should timely adjust industrial development and environmental protection
policies based on the local industrial scale and structure change, so as to enhance the
driving force of enterprise scientific and technological innovation as well as enlarge the
role of technology effect in environmental protection. Meanwhile, force the industries
to transform and upgrade via improving the awareness of residents in environmental
protection and reducing the consumption of high-pollution products.
An understanding of environmental effects is conducive to adopting a sustainable
development perspective to discuss the environmental problems of industrial transfer.
However, due to difficulties in obtaining the necessary data, this study exclusively con-
sidered industrial enterprises of a certain scale. Future studies should investigate and
elaborate on the classification of industrial enterprises to increase the comprehensiveness
of current research findings.
Author Contributions:
Conceptualization, G.M. and W.J.; Formal analysis, G.M., W.J. and Y.M.;
Funding acquisition, G.M. and W.J.; Investigation, W.J., Y.Z. and Y.M.; Methodology, W.J. and Y.Z.;
Project administration, G.M.; Resources, Y.Z.; Software, H.-L.L.; Supervision, G.M.; Validation, W.-
L.H.; Visualization, W.-L.H.; Writing—review & editing, H.-L.L., G.M. and W.J. contributed equally
to this work. All authors have read and agreed to the published version of the manuscript.
Funding:
The Ministry of education of Humanities and Social Science project of China, grant number
(18YJA790061); Social Science Foundation of Jiangsu Province, China (18EYB008); Humanity and
Social Science Youth foundation of Chinese Ministry of Education, grant number (18YJC790065); Na-
tional Statistical Science Research Project, China, grant number (2020LY029); The major social science
project of universities in Jiangsu Province (2018jdxm002); National Natural Science Foundation of
China, grant number (41271135).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments:
We would like to thank anonymous reviewers for their valuable comments and
suggestions for improving this paper.
Conflicts of Interest: The authors declare no conflict of interest.

Sustainability 2021,13, 12128 16 of 19
Appendix A
Table A1. Industrial transfer in four prefectural-level cities in Jiangsu between 2006 and 2018.
City Transferred-In Industries Transferred-Out Industries
Nanjing
Electrical machinery and equipment
manufacturing (0.0043%); instruments,
meters, and cultural and clerical
machinery (0.2156%); textile garments,
footwear, and hat products (0.2037%),
metal products (0.1313%); production
and supply of electric power and heat
power (0.0359%); manufacture of
medicines (0.0254%); manufacture of
furniture (0.0195%); manufacture of
textiles (0.0138%); manufacture of paper
and paper products (0.0112%);
manufacture of leather, fur, feather, and
related products (0.0089%)
Manufacture of chemical raw material and chemical
products (−2.2951%); smelting and pressing of ferrous
metals (−1.0747%); petroleum refining, coking, and
nuclear fuel processing (−0.5482%); telecommunication
equipment, computers, and other electronic products
(−0.2460%); smelting and pressing of nonferrous metals
(−0.1554%); processing of food from agricultural
products (−0.1454%); manufacture of articles for culture,
education, and sport activities (−0.1332%); manufacture
of general purpose machinery (−0.1234%); manufacture
of special purpose machinery (−0.1219%); manufacture
of nonmetallic mineral products (−0.0473%);
manufacture of beverages (−0.0548%); mining and
processing of nonmetal ores (−0.1207%); manufacture of
rubber and plastic (0.0415%); production and supply of
gas (−0.0400%); manufacture of chemical fibers
(−0.0389%); printing and reproduction of recording
media (−0.0385%); manufacture of food (−0.0100%);
production and supply of water (−0.0001%); processing
of timber and manufacture of wood, bamboo, rattan,
palm, and straw products (−0.0045%)
Chang-zhou
Manufacture of electrical machinery and
equipment (1.0893%); smelting and
pressing of ferrous metals (0.8821%);
smelting and pressing of nonferrous
metals (0.3313%); manufacture of
communication equipment, computers,
and other electronic equipment (0.1414%);
manufacture of measuring instruments
and machinery for cultural activity and
office work (0.1338%); manufacture of
articles for culture, education, and sport
activities (0.0726%); manufacture of paper
and paper products (0.0544%); processing
of petroleum, coking, and processing of
nucleus fuel (0.0366%); manufacture of
leather, fur, feather, and related products
(0.0321%); manufacture of food (0.0313%);
production and supply of gas (0.0150%);
production and supply of water
(0.0062%)
Manufacture of general purpose machinery (−0.4838%);
manufacture of special purpose machinery (−0.4474%);
smelting and pressing of nonferrous metals (−0.2463%);
manufacture of textile garments, footwear, and hat
products (−0.2284%); manufacture of rubber and plastic
(−0.1443%); manufacture of medicines (−0.0960%);
processing of timber and manufacture of wood, bamboo,
rattan, palm, and straw products (−0.0637%);
manufacture of textiles (−0.0539%); production and
supply of electric power and heat power (−0.0453%);
processing of food from agricultural products
(−0.0417%); printing and reproduction of recording
media (
−
0.0368%); manufacture of furniture (
−
0.0349%);
mining and processing of nonmetal ores (−0.0234%);
manufacture of metal products (
−
0.0245%); manufacture
of nonmetallic mineral products (−0.0326%);
manufacture of beverages (−0.0201%); manufacture of
chemical fibers (−0.0133%)

Sustainability 2021,13, 12128 17 of 19
Table A1. Cont.
City Transferred-In Industries Transferred-Out Industries
Suzhou
Manufacture of general purpose
machinery (0.8408%); manufacture of
chemical fibers (0.2001%); production and
supply of gas (0.0597%); manufacture of
food (0.0488%); manufacture of beverages
(0.0032%)
Manufacture of communication equipment, computers,
and other electronic equipment (
−
3.2696%); manufacture
of electrical machinery and equipment (−1.6506%);
manufacture of measuring instruments and machinery
for cultural activity and office work (−1.6495%);
manufacture of textiles (−1.3271%); manufacture of
chemical raw material and chemical products
(−1.1365%); smelting and pressing of nonferrous metals
(−0.6654%); manufacture of special purpose machinery
(−0.6599%); smelting and pressing of ferrous metals
(
−
0.5295%); textile garments, footwear, and hat products
(−0.5075%); processing of food from agricultural
products (−0.4397%); manufacture of nonmetallic
mineral products (−0.3507); manufacture of articles for
culture, education, and sport activities (−0.2296%);
manufacture of leather, fur, feather, and related products
(−0.2293%); manufacture of medicines (−0.2267%);
manufacture of metal products (
−
0.2071%); manufacture
of paper and paper products (
−
0.1907%); manufacture of
rubber and plastic (−0.1601%); manufacture of furniture
(−0.1516%); processing of timber and manufacture of
wood, bamboo, rattan, palm, and straw products
(
−
0.1423%); production and supply of electricity, gas, and
water (−0.0650%); production and supply of water
(−0.0131%); processing of petroleum, coking, and
processing of nucleus fuel (−0.0131%); printing and
reproduction of recording media (
−
0.0453%); mining and
processing of nonmetal ores (−0.0057%)
Nantong
Manufacture of chemical raw material
and chemical products (1.2045%);
manufacture of electrocution machinery
and equipment (1.0322%); manufacture
of special purpose machinery (0.9112%);
manufacture of general purpose
machinery (0.7110%); manufacture of
communication equipment, computers,
and other electronic equipment (0.6728%);
manufacture of textiles (0.4612%);
manufacture of articles for culture,
education, and sport activities (0.4507%);
manufacture of measuring instruments
and machinery for cultural activity and
office work (0.2872%); manufacture of
chemical fibers (0.1845%); manufacture of
metal products (0.1724%); smelting and
pressing of nonferrous metals (0.1582%);
manufacture of medicines (0.0774%);
smelting and pressing of ferrous metals
(0.0683%); manufacture of food (0.0542%);
manufacture of paper and paper
products (0.0522%); production and
supply of electric power and heat power
(0.0350%); production and supply of gas
(0.0199%); production and supply of
water (0.0108%); manufacture of
nonmetallic mineral products (0.0081%)
Processing of petroleum, coking, and nucleus fuel
(−0.0002%); processing of food from agricultural
products (−0.4384%); manufacture of textile garments,
hats, and footwear (−0.3387%); manufacture of rubber
and plastic (−0.0658%); manufacture of beverages
(−0.0235%); processing of timber and manufacture of
wood, bamboo, rattan, palm, and straw product
(−0.0158%); manufacture of leather, fur, feather, and
related products (−0.0043%); manufacture of furniture
(−0.0028%); printing and reproduction of recording
media (−0.0019%)
Note: Values in parentheses represent the proportion of each industry that transferred within Jiangsu. Source: Authors calculation using
the Statistical Yearbook of Jiangsu (between 2007 and 2019).

Sustainability 2021,13, 12128 18 of 19
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