Sustainability of Climate Change and Disaster Management Based on Greenhouse Gas Emissions Towards <scp>SDG13</scp>: Dynamic Analysis and Regional Comparison in China

ABSTRACT Greenhouse gas (GHG) emissions continue to affect the climate; extreme weather events frequently exacerbate global climate risks, leading to significant reflections on climate change and sustainable development due to immense losses from natural disasters. This paper develops a dynamic three‐stage network directional distance function (DDF) data envelopment analysis (DEA) model. The model is used to evaluate the efficiency of China's Sustainable Development Goal 13 (SDG13) and assess the efficiency across three stages: greenhouse gas (GHG) emissions, climate change, and disaster management. The innovation of this paper is that, compared to previous studies, the selected variables align more closely with the targets of SDG13, and the model is more systematic. Additionally, based on efficiency performance, provinces are categorized into four warning levels, and a comparative analysis is conducted by grouping the 30 provinces into seven geographic regions. This approach offers a more robust foundation for policymaker decision‐making. Results indicate that China's SDG13 efficiency is concerning; GHG emissions perform best, followed by climate change, with disaster management being the weakest. Regionally, North and East China excel in green and low‐carbon development and disaster management, while Northwest China demonstrates the poorest performance. The evaluation of Total‐Factor Efficiency for key indicators revealed that CO 2 and PM 2.5 emission efficiencies are relatively acceptable. However, indicators reflecting the capacity to respond to extreme weather and natural disasters, such as the population affected and economic loss, demonstrate significant vulnerabilities.

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Publication Details

Journal
Sustainable Development
Published
2025-02-27
DOI
https://doi.org/10.1002/sd.3404
Citations
1
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
2.11

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article

Sustainability of Climate Change and Disaster Management Based on Greenhouse Gas Emissions Towards SDG13: Dynamic Analysis and Regional Comparison in China

Mingle Chen, Yung‐ho Chiu, Yanan Sun, Tao Shi-gui et al.
1 citations
Sustainable Development
Efficiency Analysis Using DEA
2.11
article

Sustainability of Climate Change and Disaster Management Based on Greenhouse Gas Emissions Towards SDG13: Dynamic Analysis and Regional Comparison in China

Mingle Chen, Yung‐ho Chiu, Yanan Sun, Tao Shi-gui, Li Ji, Tai‐Yu Lin, Yali Yin
article en
1 citations

Abstract

ABSTRACT Greenhouse gas (GHG) emissions continue to affect the climate; extreme weather events frequently exacerbate global climate risks, leading to significant reflections on climate change and sustainable development due to immense losses from natural disasters. This paper develops a dynamic three‐stage network directional distance function (DDF) data envelopment analysis (DEA) model. The model is used to evaluate the efficiency of China's Sustainable Development Goal 13 (SDG13) and assess the efficiency across three stages: greenhouse gas (GHG) emissions, climate change, and disaster management. The innovation of this paper is that, compared to previous studies, the selected variables align more closely with the targets of SDG13, and the model is more systematic. Additionally, based on efficiency performance, provinces are categorized into four warning levels, and a comparative analysis is conducted by grouping the 30 provinces into seven geographic regions. This approach offers a more robust foundation for policymaker decision‐making. Results indicate that China's SDG13 efficiency is concerning; GHG emissions perform best, followed by climate change, with disaster management being the weakest. Regionally, North and East China excel in green and low‐carbon development and disaster management, while Northwest China demonstrates the poorest performance. The evaluation of Total‐Factor Efficiency for key indicators revealed that CO 2 and PM 2.5 emission efficiencies are relatively acceptable. However, indicators reflecting the capacity to respond to extreme weather and natural disasters, such as the population affected and economic loss, demonstrate significant vulnerabilities.

Sustainable DevelopmentVol. 33(4)
Nanjing Normal University (CN), Soochow University (TW), Nantong University (CN), Nanjing Audit University (CN), Xi’an Jiaotong-Liverpool University (CN), National Cheng Kung University (TW)
National Office for Philosophy and Social Sciences
Climate action
Openalex Percentile: Top 16%
Efficiency Analysis Using DEA
2.11
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