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探究碳排放强度的必要和充分条件:比较分析。

Exploring necessary and sufficient conditions for carbon emission intensity: a comparative analysis.

机构信息

Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.

Faculty of Economics, and Centre for Business and Economics Research (CeBER), University of Coimbra, Coimbra, Portugal.

出版信息

Environ Sci Pollut Res Int. 2023 Sep;30(43):97319-97338. doi: 10.1007/s11356-023-29260-8. Epub 2023 Aug 17.

Abstract

This research investigates the factors influencing carbon emission intensity in 94 countries during 2018 using two qualitative methods: necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The study covers variables related to economics, human geography, energy, and institutions, showing significant variations among them. The NCA model identifies economic complexity and fossil energy consumption as necessary conditions for high-carbon emission intensity. On the other hand, the fsQCA model reveals sufficient conditions for both high- and low-carbon emission intensity, presenting different causal combinations of variables. For high-carbon emission intensity, nine causal solutions are identified, emphasizing the roles of economic growth, urbanization, fossil energy consumption, and institutional quality. Reducing carbon emission intensity requires addressing economic complexity and reducing reliance on fossil energy consumption. Policymakers should focus on sustainable economic development, environmentally friendly urbanization, and transitioning to renewable energy sources. This research's originality lies in its qualitative approach, going beyond traditional regression methods to explore necessary and sufficient conditions for carbon emission intensity. It offers valuable insights into the complex interplay of variables, providing multiple causal configurations for both high- and low-carbon emission intensity.

摘要

本研究使用两种定性方法

必要条件分析(NCA)和模糊集定性比较分析(fsQCA),调查了 2018 年 94 个国家的碳排放强度影响因素。研究涵盖了与经济、人类地理学、能源和制度相关的变量,这些变量之间存在显著差异。NCA 模型确定了经济复杂性和化石能源消费是高碳排放强度的必要条件。另一方面,fsQCA 模型揭示了高碳和低碳排放强度的充分条件,呈现了不同的变量因果组合。对于高碳排放强度,确定了九个因果解决方案,强调了经济增长、城市化、化石能源消费和制度质量的作用。降低碳排放强度需要解决经济复杂性问题并减少对化石能源的依赖。政策制定者应关注可持续经济发展、环境友好型城市化和向可再生能源转型。本研究的创新性在于其定性方法,超越了传统的回归方法,探索了碳排放强度的必要和充分条件。它深入了解了变量之间的复杂相互作用,为高碳和低碳排放强度提供了多种因果配置。

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