Quantifying the patterns and driving forces of sulfur dioxide emissions in China through MRIO model and network analysis

Research on environmental emissions transfers is important for regional cooperation on pollution mitigation and sustainable development. However, few studies have examined the characteristics and driving factors of the sulfur dioxide (SO2) emissions transfer network. This paper utilizes a Multi-Regional Input–Output (MRIO) model to construct an industrial emissions network with sectoral information and investigates its evolutionary patterns and influencing pathways through comprehensive network analysis and a Multiple Regression Quadratic Assignment Procedure (MRQAP) model. The findings show that many western provinces in China have shifted from being net exporters to net importers of emissions. The implicit transfer network has evolved into multifaceted connections among coastal provinces and their hinterland provinces. Additionally, the study highlights a degree of path dependence in emission transfers, with key provinces in each major region maintaining significant control over the network. Developed provinces not only regulate emissions in developing regions but also influence other developed areas. While innovation levels, energy consumption structures, and environmental regulations consistently emerge as key factors influencing emissions, their mechanisms of impact vary. In contrast, factors like public satisfaction, regional resource endowment, and geographic distance have minimal effects on industrial emissions transfers. This paper underscores the importance of region- and sector-specific policy interventions to address environmental pressures and advance sustainable development goals.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2025-09-16
DOI
https://doi.org/10.1057/s41599-025-05404-8
Primary Topic
Sustainability and Ecological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Quantifying the patterns and driving forces of sulfur dioxide emissions in China through MRIO model and network analysis

Shixi Cui, Rong Wu, Shaojian Wang
Humanities and Social Sciences Communications
Sustainability and Ecological Systems Analysis
article

Quantifying the patterns and driving forces of sulfur dioxide emissions in China through MRIO model and network analysis

Shixi Cui, Rong Wu, Shaojian Wang
article en

Abstract

Research on environmental emissions transfers is important for regional cooperation on pollution mitigation and sustainable development. However, few studies have examined the characteristics and driving factors of the sulfur dioxide (SO2) emissions transfer network. This paper utilizes a Multi-Regional Input–Output (MRIO) model to construct an industrial emissions network with sectoral information and investigates its evolutionary patterns and influencing pathways through comprehensive network analysis and a Multiple Regression Quadratic Assignment Procedure (MRQAP) model. The findings show that many western provinces in China have shifted from being net exporters to net importers of emissions. The implicit transfer network has evolved into multifaceted connections among coastal provinces and their hinterland provinces. Additionally, the study highlights a degree of path dependence in emission transfers, with key provinces in each major region maintaining significant control over the network. Developed provinces not only regulate emissions in developing regions but also influence other developed areas. While innovation levels, energy consumption structures, and environmental regulations consistently emerge as key factors influencing emissions, their mechanisms of impact vary. In contrast, factors like public satisfaction, regional resource endowment, and geographic distance have minimal effects on industrial emissions transfers. This paper underscores the importance of region- and sector-specific policy interventions to address environmental pressures and advance sustainable development goals.

Humanities and Social Sciences CommunicationsVol. 12(1)
Guangdong University of Technology (CN), Sun Yat-sen University (CN), Wuhan University (CN)
National Social Science Fund of China
Openalex Percentile: Top 77%
Sustainability and Ecological Systems Analysis
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