Geospatial driving factor analysis on the synergy between air  pollution control and carbon mitigation in China

Man Guo; Baozhang Chen; Nicholas Hamm

doi:10.5281/zenodo.10928029

Geospatial driving factor analysis on the synergy between air pollution control and carbon mitigation in China

Research output: Contribution to conference › Paper › peer-review

Abstract

Facing air pollution and carbon mitigation challenges, China actively pursues a “win-win” strategy for simultaneous reductions. This study evaluates synergistic governance performance between air pollution control and carbon mitigation in China under policy influence. It takes a GIS approach, based on spatial data analysis. Results show no significant improvement in synergistic governance performance under guidance of the major policies like "Clean Air Action" and "Blue Sky Defense". The relative activities during COVID-19 pandemic further hindered national effectiveness. Drivers exhibited spatial variations, while temporal heterogeneity remained relatively stable. These findings provide scientific insights that offer guidance for policymakers tackling environmental challenges.

Original language	English
DOIs	https://doi.org/10.5281/zenodo.10928029
Publication status	Published - 10 Apr 2024
Event	32nd Annual GIS Research UK Conference - University of Leeds, Leeds, United Kingdom Duration: 9 Apr 2024 → 12 Apr 2024 Conference number: 32nd

Conference

Conference	32nd Annual GIS Research UK Conference
Abbreviated title	GISRUK
Country/Territory	United Kingdom
City	Leeds
Period	9/04/24 → 12/04/24

Keywords

Synergistic effect evaluation
Ordering degree
Coupling coordination degree
Driving factors
GWR (Geographically Weighted Regression)

Access to Document

10.5281/zenodo.10928029Licence: CC BY

Cite this

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title = "Geospatial driving factor analysis on the synergy between air pollution control and carbon mitigation in China",

abstract = "Facing air pollution and carbon mitigation challenges, China actively pursues a “win-win” strategy for simultaneous reductions. This study evaluates synergistic governance performance between air pollution control and carbon mitigation in China under policy influence. It takes a GIS approach, based on spatial data analysis. Results show no significant improvement in synergistic governance performance under guidance of the major policies like {"}Clean Air Action{"} and {"}Blue Sky Defense{"}. The relative activities during COVID-19 pandemic further hindered national effectiveness. Drivers exhibited spatial variations, while temporal heterogeneity remained relatively stable. These findings provide scientific insights that offer guidance for policymakers tackling environmental challenges.",

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doi = "10.5281/zenodo.10928029",

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T1 - Geospatial driving factor analysis on the synergy between air pollution control and carbon mitigation in China

AU - Guo, Man

AU - Chen, Baozhang

AU - Hamm, Nicholas

N1 - Conference code: 32nd

PY - 2024/4/10

Y1 - 2024/4/10

N2 - Facing air pollution and carbon mitigation challenges, China actively pursues a “win-win” strategy for simultaneous reductions. This study evaluates synergistic governance performance between air pollution control and carbon mitigation in China under policy influence. It takes a GIS approach, based on spatial data analysis. Results show no significant improvement in synergistic governance performance under guidance of the major policies like "Clean Air Action" and "Blue Sky Defense". The relative activities during COVID-19 pandemic further hindered national effectiveness. Drivers exhibited spatial variations, while temporal heterogeneity remained relatively stable. These findings provide scientific insights that offer guidance for policymakers tackling environmental challenges.

AB - Facing air pollution and carbon mitigation challenges, China actively pursues a “win-win” strategy for simultaneous reductions. This study evaluates synergistic governance performance between air pollution control and carbon mitigation in China under policy influence. It takes a GIS approach, based on spatial data analysis. Results show no significant improvement in synergistic governance performance under guidance of the major policies like "Clean Air Action" and "Blue Sky Defense". The relative activities during COVID-19 pandemic further hindered national effectiveness. Drivers exhibited spatial variations, while temporal heterogeneity remained relatively stable. These findings provide scientific insights that offer guidance for policymakers tackling environmental challenges.

KW - Synergistic effect evaluation

KW - Ordering degree

KW - Coupling coordination degree

KW - Driving factors

KW - GWR (Geographically Weighted Regression)

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DO - 10.5281/zenodo.10928029

M3 - Paper

T2 - 32nd Annual GIS Research UK Conference

Y2 - 9 April 2024 through 12 April 2024

ER -