The impact of cross-region industrial structure optimization on economy, carbon emissions and energy consumption: A case of the Yangtze River Delta

https://doi.org/10.1016/j.scitotenv.2021.146089Get rights and content

Highlights

  • A model is proposed to decouple economic development with environmental issues across regions.

  • The goal programming model optimization across regions is established in the model.

  • A super DEA model evaluates the final plan which reflects the coordination of the economy and environment.

  • Key output of the model is a roadmap of eco-industrial development by retuning industrial structure.

Abstract

Industry structure adjustment is an important way to solve environmental problems. The adjustment of the industrial structure across regions not only needs to meet the goals of each region, but also involves the industrial transfer between regions. The same industry in each region has differences in economic development, energy consumption and carbon emissions. So these regions can reasonably distribute industries in various regions through the industrial transfer to meet their own requirements. A cross-regional multi-objective planning model combined the data envelopment analysis method is put forward to solve the problem of the reasonable industries distribution. The representative result which is selected from the set of different preference solutions reflects the coordination of economic development and environment. In order to distinguish the effects, the results of cross-region and single-region industry structure optimization models are compared. The Yangtze River Delta as a case study is analyzed. The results show that each province can realize the reasonable distribution of industries through the industrial transfer, and complete the phased goals in the 13th Five-Year Plan. Meanwhile, the eco-efficiency of each province is improved and the difference in economy has narrowed. The case provides a basis for other regions to balance development of economy and environmental protection through regional cooperation and division of labor.

Graphical abstract

A reasonable industrial division and collaboration system has been formed through the guidance of cross-region industrial structure optimization.

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Introduction

China has achieved great success in economy after reform and opening up. The rapid economy growth rate often comes at the expense of the environmental development that has led to the depletion of resources and ecological environment deterioration, high energy consumption, high pollution phenomenon in a few places (Z.X. Zhou et al., 2020). China's economic losses caused by unilateral pursuit of environmental pollution account for about 8%–15% of gross domestic product (GDP). Sustainable regional economic development is under serious threat (X. Liu et al., 2015b). Realizing high economic growth, continuous utilization of resources, and effective environmental protection have become the primary problem in regional economic and social development (Cheng et al., 2014).

Over a decade now, researchers conduct related researches on economic production and various measures for energy saving and emissions reduction. Some studies focus on certain specific industries. They investigate the impact of production methods (Hosseinzadeh-Bandbafha et al., 2018; Elsoragaby et al., 2019; Mostashari-Rad et al., 2019) and technological progress (Bahman et al., 2018; Jafari-Sejahrood et al., 2019) on energy and carbon emissions. For example, Lv et al. (2019) estimated iron life cycle energy consumption and greenhouse gas emissions, providing solutions for energy conservation and emissions reduction in China's steel industry. Other studies focus on the impact of regional or national industries on energy and carbon emissions. These researches (González and Martínez, 2012; Wang et al., 2016; Wurlod and Noailly, 2018) often investigate the carbon emissions or energy efficiency of the industry. Especially, some researches (Xiong et al., 2019; D. Li et al., 2020c; Zhu and Shan, 2020) analyze the impact of industry structure optimization on energy consumption and carbon emissions, and conclude that the industry structure adjustment not only is an important way to achieve high-speed regional economic growth, but also directly determines the consumptions structure and utilization efficiency of energy. Energy consumption is closely related to carbon emissions. So the industry structure adjustment is an important way to solve environmental problems and reduce carbon emissions (Wu et al., 2018). Through industry structure adjustment each region can increase investment in technology-intensive and knowledge-intensive industries, improve technological progress and support emerging industries, reduce investment in high-pollution and energy-intensive industries, and control energy consumption and pollution emissions from the source.

However, there is little literature focus on the cross-regional industrial structure adjustment. China's current industrial reconstructuring mainly relies on industrial policies implementation and intervention. And the similar industrial policies of local governments may lead to the isomorphism of industries among regions and the intensification of low-level repeated construction. Local governments in backward areas encourage the development of some high-tech industries that do not have a comparative advantage in the short term, to improve their returns in the future regional division. The result of this kind of rational behavior of local government is just a round of repeated construction. If all the regions optimize their industrial structure without mutual cooperation, industrial homogeneity may occur. The rational layout of industries will be affected, and the improvement of industrial energy efficiency will also be reduced (Han et al., 2018).

Therefore, under the circumstances of energy-saving and emissions reduction, how to optimize the cross-regional industrial structure to achieve high-speed economic growth has become a hot issue of concern to academia. Existing researches have played an important role in explaining and guiding regional industrial structure optimization, but there are also some obvious limitations. These researches (Tian et al., 2014; Chang, 2015; Y. Yu et al., 2018; Chen et al., 2019) either considered the industry structure optimization within a region or country, or do not effectively guided the effective division of labor in each area. Very few kinds of literature went further to discuss the cooperation between regions, and adjust industrial structure through industrial transfer and division to achieve economic development, energy conservation, and emissions reduction. Thus we still don't know how to optimize industrial structure and form a reasonable division of labor system. The solution of the serious environmental pollution problem caused by the regional development of the championship model needs to be found.

In order to fill such research gaps, this paper investigates the effect of cross-regional industry structure optimization on economic development, energy and carbon emissions. Because the same industry in different regions will produce different carbon emissions and energy consumption during the production process. These regions can reasonably distribute industries in various regions through the form of industrial transfer to meet their economic development, energy consumption and carbon emissions requirements. This process can be achieved by constructing a cross-regional multi-objective planning model. We take the Yangtze River Delta region as an example. Regional integration in the Yangtze River Delta has become a national strategy. Inter-regional industrial transfer and coordinated development are conducive to the structural optimization and upgrading of the Yangtze River Delta region, and promote the regional economy to a higher level. Each province's industry structure is adjusted to realize the goals of energy conservation and emissions decrease while meeting the requirements of economic development in 2018. The model has five goals: the growth rate of GDP, energy consumption, energy and carbon intensities, as well as the proportion of service industry. Because some provinces are unable to complete all goals, this model adopts goal programming method. And different settings of priority in the goal programming model will get different results, the super-efficiency data envelopment analysis (DEA) model which can better sort schemes is used to choose the best solution. The result reflects the coordination of economic development and environment. Thus, we expand the previous analysis to the following aspects: (1) Carrying out not just optimization within a region, but an optimization problem across regions. And discussing the adjustment of industrial structure through industrial transfer and division to obtain the industry distribution of each province. (2) In terms of method, the goal programming model and the super-efficiency DEA model combine to compare the pros and cons of different results based on economy and environment coordination, and solve the regional industrial structure optimization problem.

The rest of this paper is organized as follows. Section 2 is the overview of relationship between industrial structure, emissions and consumption. Section 3 shows the goal programming model's construction. In Section 4 the Yangtze River Delta as a case is analyzed. Section 5, a general conclusion and discussion is given.

Section snippets

Literature review

Since economists Grossman and Krueger (1995) had put forward the famous environmental Kuznets curve, a series of relevant related researches on environment and economic growth were developed (Carson et al., 1997; Narayan and Smyth, 2008; Sari et al., 2008; Shahbaz et al., 2015). Galeotti et al. (2006) also proved this inverted U-shaped curve relationship for Organization for Economic Cooperation and Development (OECD) countries. Acaravci and Ozturk (2010) checked the validation of the

The model

For the purpose of examining the performance of cross-region industrial structure optimization on carbon emissions and energy consumption, two optimization models including the single-region and the cross-region industry structure optimization models are set up for comparison.

Industrial structure optimization is a multi-objective planning model which contains several constraints which are local governments' phased goals according to the targets of the 13th Five-Year Plan of each province. The

Study area

The Yangtze River Delta (YRD) is situated in the East Asia Geographic Center and the East Pacific route of the Western Pacific (as can be seen in Fig. 1). It is a key intersection of the Yangtze River Economic Belt and the “Belt and Road”. The YRD not only has excellent natural endowments with a mild climate and rich products, but also has strong comprehensive strength, such as convenient transportation conditions, a complete industrial system, rich scientific and technological achievements,

Sensitivity analysis settings

The results of the optimized models will vary with the changes of the parameters in the model. The main influencing factors include the following three categories:

The first category is the growth and decline limits of the six industries in each region in the model. They are based on the maximum fluctuation of historical data during the 12th Five Year Plan period. And the degree of industrial transfer is a key variable that expands the limits of industrial growth and decline. The second category

Conclusion

As the world's largest emitter of greenhouse gases, the development of a low-carbon economy has been the key task for China's sustainable development. The industry structure directly determines the energy consumption structure and utilization efficiency, and energy consumption is closely related to CO2 emissions. Therefore, accelerating the upgrading of industry structure has become not only a key driving force for long-term sustainable economic development, but also an important means to solve

Funding project

Anhui Philosophy and Social Science Planning Project (AHSKY2020D21).

CRediT authorship contribution statement

Bing Zhu: Methodology, Data curation, Writing – original draft. Tinglong Zhang: Conceptualization, Writing – review & editing.

Declaration of competing interest

The authors declare that there is no conflict of interests regarding the publication of this article.

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