Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

The spatial correlation network evolution and influencing factors of industrial carbon emission efficiency in China

Bibliographic Data

ID6455879
AuthorsZ Wang (0000-0002-1285-9803), Xinmei Wang (0009-0002-2131-5741), Zhipeng Fan (0000-0003-0629-3476), Chao Feng (0000-0003-2327-1981), Xiaoling Qiu (0000-0002-0172-5199), Wei He (0000-0001-8290-7981)
Year2025
Volume9
Pages100767-100767
Publication date2025-06-01
Open AccessYes
TypeARTICLE
VenueSustainable Futures (JOURNAL)
Journal identifiersISSN: 2666-1888
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.sftr.2025.100767
OpenAlexW4410935416
LanguageEN
Citations received1
References cited39

Clarifying the spatial correlation network (SCN) evolution characteristics and influencing factors of industrial carbon emission efficiency (ICEE) is of great significance for improving ICEE, achieving the ''dual carbon policy'' goals, and promoting coordinated regional development. This research examines 30 Chinese provinces and cities, utilizing Social Network Analysis (SNA) to explore the spatial network evolution of industrial carbon emission efficiency (CICEE) between 2011 and 2022.The QAP model explores the factors driving network formation. The findings are as follows:1. CICEE shows an overall upward trend, with high-value regions mainly concentrated in coastal areas, displaying obvious SCN characteristics. 2. The network's node roles have shifted notably, transitioning from bidirectional outflow plates (BOP) to main inflow (IP) and outflow plates (OP). The CICEE network's spatial correlation has strengthened, with connections increasing from 235 to 244 and network density rising from 0.2701 to 0.2805. The network structure is gradually evolving toward a stable state, although hierarchical patterns remain prominent. Regions such as Beijing, Shanghai, and Jiangsu have consistently occupied core positions within the network, and spatial correlation relationships primarily exist among major regions.3. The formation of the SCN of CICEE is significantly influenced by factors such as industrial structure, openness to the outside world, industrialization level, economic development level, transportation infrastructure, and spatial adjacency relationships. Based on the research findings, this study proposes regional cooperation strategies for low-carbon management. The results provide references for improving CICEE and facilitating collaborative emission reductions among regions

Carbon fibers · China · Composite material · Correlation · Economic geography · Geography · Geometry · Energy, Environment, Economic Growth · Environmental Impact and Sustainability · Environmental Science · Materials Science · Mathematics

  • How to improve the environmental friendliness of the thermal power industry

    Open Access•Yuting Fu, Changhui Yang et al.•Sustainable Cities and Society•2025

  • The human imperative of stabilizing global climate change at 1.5°C

    Open Access•Ove Hoegh-Guldberg, Daniela Jacob et al.•Science•2019

  • China's agricultural green total factor productivity based on carbon emission

    Open Access•Dongdong Liu, Xiaoyan Zhu et al.•Journal of Cleaner Production•2021

  • Global Carbon Budget 2023

    Open Access•Pierre Friedlingstein, Mike O’Sullivan et al.•Earth System Science Data•2023

  • Industrial agglomeration, technological innovation and carbon productivity

    Open Access•Xiping Liu, Xiaoling Zhang•Resources Conservation and…•2021

  • How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China

    Open Access•Jun Zhao, Qingzhe Jiang et al.•Energy Economics•2022

  • Global Carbon Budget 2022

    Open Access•Pierre Friedlingstein, Mike O’Sullivan et al.•Earth System Science Data•2022

  • Spatial Evolutionary Characteristics and Influencing Factors of Urban Industrial Carbon Emission in China

    Open Access•Xinyu Zhang, Mufei Shen et al.•International Journal of…•2022

  • The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation

    Open Access•Fei Ma, Yixuan Wang et al.•International Journal of…•2019

  • Spatial correlation network structure characteristics of carbon emission efficiency and its influencing factors at city level in China

    Open Access•Zhongrui Sun, Xianhong Cheng et al.•Environment Development and…•2023

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae