The Optimization of Industrial Structure Under the ‘Dual Carbon’ Goal via Multi-Objective Programming Model: Evidence from Guangdong Province, China

With the increasing frequency of extreme weather events, global concerns regarding climate change have intensified, with carbon dioxide widely recognized as the primary driver of global warming and climate disruption. It is necessary to investigate how to develop industries to meet the constant GDP...

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Vydáno v:Sustainability Ročník 17; číslo 13; s. 5912
Hlavní autoři: Cheng, Jing, Cai, Changhong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.07.2025
Témata:
21st century
Air quality management
Atmospheric carbon dioxide
Carbon dioxide
Climate change
Coal
Economic development
Economic growth
Economic structure
Emissions
Energy consumption
Environmental aspects
GDP
Gross Domestic Product
Industrial organization
Manufacturing
Mathematical optimization
Multiple criteria decision making
Object-oriented programming
Optimization
Regional differences
Sustainable development
Technology application
China
Guangdong China
ISSN:2071-1050, 2071-1050
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Abstract With the increasing frequency of extreme weather events, global concerns regarding climate change have intensified, with carbon dioxide widely recognized as the primary driver of global warming and climate disruption. It is necessary to investigate how to develop industries to meet the constant GDP growth and minimum carbon emissions. This study investigates the optimization of industrial structure under China’s ‘Dual Carbon’ Goal in Guangdong Province from 2012 to 2017, employing a multi-objective programming model. Using the input–output table, carbon emissions across 42 industries are calculated based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission factor method. According to Hirschman’s theory of industrial interdependence, the economic and carbon emission linkage coefficients between these industries are obtained by calculating the Ghosh inverse matrix and the Leontief inverse matrix to analyze the economic forward and backward linkage of the industries, as well as the carbon emission forward and backward linkage. The impact of industry input and output on the urban economy and the resulting carbon emission problems are discussed, and industries are divided into encouraged and restricted industries. Using a multi-objective programming model, the expected final demand, changes in final demand, and expected carbon emissions of these industries under the ‘Dual Carbon’ Goal, with the target of maintaining the same economic growth rate and promoting carbon reduction, are analyzed. The results show that most industries in Guangdong Province need to reduce final demand, including the highest carbon-emitting industries and industries that are relatively restricted by scale in development. The policy implications of optimizing the industrial structure to reduce carbon emissions are provided.
AbstractList With the increasing frequency of extreme weather events, global concerns regarding climate change have intensified, with carbon dioxide widely recognized as the primary driver of global warming and climate disruption. It is necessary to investigate how to develop industries to meet the constant GDP growth and minimum carbon emissions. This study investigates the optimization of industrial structure under China’s ‘Dual Carbon’ Goal in Guangdong Province from 2012 to 2017, employing a multi-objective programming model. Using the input–output table, carbon emissions across 42 industries are calculated based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission factor method. According to Hirschman’s theory of industrial interdependence, the economic and carbon emission linkage coefficients between these industries are obtained by calculating the Ghosh inverse matrix and the Leontief inverse matrix to analyze the economic forward and backward linkage of the industries, as well as the carbon emission forward and backward linkage. The impact of industry input and output on the urban economy and the resulting carbon emission problems are discussed, and industries are divided into encouraged and restricted industries. Using a multi-objective programming model, the expected final demand, changes in final demand, and expected carbon emissions of these industries under the ‘Dual Carbon’ Goal, with the target of maintaining the same economic growth rate and promoting carbon reduction, are analyzed. The results show that most industries in Guangdong Province need to reduce final demand, including the highest carbon-emitting industries and industries that are relatively restricted by scale in development. The policy implications of optimizing the industrial structure to reduce carbon emissions are provided.
Audience Academic
Author Cheng, Jing
Cai, Changhong
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SubjectTerms 21st century
Air quality management
Atmospheric carbon dioxide
Carbon dioxide
Climate change
Coal
Economic development
Economic growth
Economic structure
Emissions
Energy consumption
Environmental aspects
GDP
Gross Domestic Product
Industrial organization
Manufacturing
Mathematical optimization
Multiple criteria decision making
Object-oriented programming
Optimization
Regional differences
Sustainable development
Technology application
Title The Optimization of Industrial Structure Under the ‘Dual Carbon’ Goal via Multi-Objective Programming Model: Evidence from Guangdong Province, China
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