中国在气候变化和多重环境问题协同治理方面取得的进展。

IF 2.2 Q2 MULTIDISCIPLINARY SCIENCES PNAS nexus Pub Date : 2024-08-21 eCollection Date: 2024-09-01 DOI:10.1093/pnasnexus/pgae351
Jianxun Yang, Zhan Zhao, Wen Fang, Zongwei Ma, Miaomiao Liu, Jun Bi
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引用次数: 0

摘要

推进气候变化与环境危机的协同控制对于实现全球可持续发展目标至关重要。本研究评估了 2009 年至 2020 年中国省级层面对气候变化和四个环境问题的协同治理水平。研究结果表明,中国在减缓碳排放、减少空气污染物和保护水资源方面的协同努力取得了重大进展。然而,在固体废弃物管理和生态系统保护方面仍有改进空间,自 2015 年以来,协同治理的整体进展有所放缓。利用随机森林模型,我们确定了对气候变化和环境协同治理有重大影响的社会经济因素,如能源强度、服务业发展、电子设备制造和交通。此外,我们还揭示了一些因素与环境子系统绩效之间的非线性关系,包括高原效应(如黑色金属冶炼的产出)和 U 型模式(如金属产品制造的产出),这可能归因于终端处理能力的限制和供应链网络的复杂性。此外,通过分层聚类分析,我们将各省分为四组,并为政策制定者提供有针对性的建议,以提高各自地区的协同治理水平。本研究建立的框架还可为寻求制定切实可行且符合国情的解决方案以降低气候和环境风险的国家提供宝贵的参考。
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China's progress in synergetic governance of climate change and multiple environmental issues.

Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room for improvement in managing solid waste and protecting ecological systems and overall progress in synergetic governance has slowed since 2015. Employing a random forest model, we identify socio-economic factors with great influence on synergetic climate change and environmental governance, such as energy intensity, service sector development, electronic equipment manufacturing, and transportation. Additionally, we reveal nonlinear relationships between some factors and performance of environmental subsystems, including both plateau effects (e.g. output in the smelting of ferrous metals) and U-shaped patterns (e.g. output in the manufacturing of metal products), possibly attributed to constraints in end-of-pipe treatment capacities and complexities in supply chain networks. Furthermore, through hierarchical clustering analysis, we classify provinces into four groups and provide tailored recommendations for policymakers to enhance synergetic governance levels in their respective regions. The framework established in this study also serves as a valuable reference for countries seeking to develop practical and context-specific solutions to mitigate climate and environmental risks.

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