Assessing the spatiotemporal patterns and drivers of pollutant-carbon reduction synergistic efficiency in the Yangtze River Delta region

As one of China’s leading manufacturing hubs, the Yangtze River Delta Region (YRDR) faces the challenge of jointly reducing pollutant and carbon emissions. This study employs an integrated framework by incorporating methods of super-efficiency slacks-based measure data envelopment analysis, kernel density estimation, social network analysis, and geographical detector to examine the spatiotemporal patterns and divers of pollutant-carbon synergistic efficiency (PCSE) in the YRDR from 2013 to 2021. Results indicate that the PCSE exhibited an upward trend, increasing at an average rate of 0.026 annually and reaching 0.665 by 2021. Notably, post-2018 witnessed accelerated improvement, with an average annual increase rate of 0.060. Spatially, the 27 central cities accounted for 64.7% of the whole regional increment in PCSE. Economically advanced cities like Shanghai and Suzhou (in Jiangsu), maintained persistently high PCSE values and the 14 peripheral cities (e.g., Huainan and Huaibei) remained low. Social network analysis shows enhanced inter-city connectivity, trending towards greater balance and resilience, with Shanghai and Suzhou (in Jiangsu) emerging as pivotal hubs in the network. Technological progress, economic development, and road infrastructure expansion are the primary drivers of PCSE enhancement. These findings underscore the need to enhance inter-city collaborative development, advance industrial restructuring in resource-dependent cities, and prioritize scientific and technological innovation to accelerate synergistic efficiency and support sustainable development.

Authors

Institutions

Publication Details

Journal
Discover Sustainability
Published
2025-12-12
DOI
https://doi.org/10.1007/s43621-025-02402-3
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the spatiotemporal patterns and drivers of pollutant-carbon reduction synergistic efficiency in the Yangtze River Delta region

Li Sun, Dong Liu, Huawei Li, Jiaxi Tian et al.
Discover Sustainability
Efficiency Analysis Using DEA
article

Assessing the spatiotemporal patterns and drivers of pollutant-carbon reduction synergistic efficiency in the Yangtze River Delta region

Li Sun, Dong Liu, Huawei Li, Jiaxi Tian, Mengjia Xu, C. Suo, Jie Sun
article en

Abstract

As one of China’s leading manufacturing hubs, the Yangtze River Delta Region (YRDR) faces the challenge of jointly reducing pollutant and carbon emissions. This study employs an integrated framework by incorporating methods of super-efficiency slacks-based measure data envelopment analysis, kernel density estimation, social network analysis, and geographical detector to examine the spatiotemporal patterns and divers of pollutant-carbon synergistic efficiency (PCSE) in the YRDR from 2013 to 2021. Results indicate that the PCSE exhibited an upward trend, increasing at an average rate of 0.026 annually and reaching 0.665 by 2021. Notably, post-2018 witnessed accelerated improvement, with an average annual increase rate of 0.060. Spatially, the 27 central cities accounted for 64.7% of the whole regional increment in PCSE. Economically advanced cities like Shanghai and Suzhou (in Jiangsu), maintained persistently high PCSE values and the 14 peripheral cities (e.g., Huainan and Huaibei) remained low. Social network analysis shows enhanced inter-city connectivity, trending towards greater balance and resilience, with Shanghai and Suzhou (in Jiangsu) emerging as pivotal hubs in the network. Technological progress, economic development, and road infrastructure expansion are the primary drivers of PCSE enhancement. These findings underscore the need to enhance inter-city collaborative development, advance industrial restructuring in resource-dependent cities, and prioritize scientific and technological innovation to accelerate synergistic efficiency and support sustainable development.

Discover SustainabilityVol. 7(1)
North China University of Water Resources and Electric Power (CN), Nanjing University of Information Science and Technology (CN), Ministry of Ecology and Environment (CN), Nanjing Institute of Environmental Sciences (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 55%
Efficiency Analysis Using DEA
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.