Energy justice and gaps in sustainable development: A convergence testing and clustering study

碳足迹 趋同(经济学) 环境经济学 能源消耗 不平等 经济 可持续发展 分歧(语言学) 温室气体 自然资源经济学 计量经济学 业务 经济增长 工程类 生态学 数学 语言学 哲学 数学分析 电气工程 生物
作者
Marinko Škare,Yu Qian,Zeshui Xu,Xunjie Gou
出处
期刊:Renewable & Sustainable Energy Reviews [Elsevier]
卷期号:192: 114166-114166 被引量:22
标识
DOI:10.1016/j.rser.2023.114166
摘要

The purpose of the study is to examine the dynamics of carbon emissions inequality and its effect on energy justice, whether carbon footprints have increased or decreased across countries, sectors, and households over time. We use convergence analysis, which is a methodology that effectively reveals carbon footprint dynamics. Our database contained carbon footprint data from different sectors across 180 countries between 1980 and 2020. We account for the non-linearity of the carbon footprint convergence or divergence process over time and individual heterogeneity across countries and sectors (data pre-filtering, carbon footprint convergence testing, and club clustering). Our results demonstrate a significant disparity in carbon footprints across various sectors and countries, especially among the top 1 % of earners. The wealthiest individuals worldwide have not converged towards a common trajectory, indicating high levels of carbon footprint inequality. This investigation assumes that the carbon footprint convergence or divergence process is not linear over time, allowing for fluctuations in carbon emissions inequality. Future research may explore the factors contributing to this non-linearity and its implications for energy justice. Our findings highlight global cooperation's importance in promoting sustainable production practices and a fair distribution of energy-related responsibilities. Energy production and consumption burdens are not equitably distributed, posing a significant challenge to achieving energy justice. This study provides a comprehensive understanding of the dynamics of carbon emissions inequality and its impact on energy justice. It employs a unique methodology and a multidimensional database, providing new insights into the carbon footprint disparity across sectors and countries.
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