Better cities better lives: How low-carbon city pilots can lower residents’ carbon emissions

温室气体 中国 气候变化 碳纤维 消费(社会学) 全球变暖 自然资源经济学 业务 环境科学 地理 经济 社会学 生态学 社会科学 材料科学 考古 复合数 复合材料 生物
作者
Xiangyang Li,Hua Xing
出处
期刊:Journal of Environmental Management [Elsevier]
卷期号:351: 119889-119889 被引量:2
标识
DOI:10.1016/j.jenvman.2023.119889
摘要

Cities generate substantial carbon emissions while facing serious climate challenges. The construction of low-carbon cities is a vital measure to cope with climate change. China has implemented three batches of low-carbon city pilots since 2010, with advocating low-carbon lifestyles and consumption patterns for residents as an indispensable component. However, there is limited research on the impact of pilot cities on carbon emissions of residents, as well as a lack of theoretical guidance and accurate data. Based on 281 prefectural-level cities in China, this study established the difference-in-differences model to evaluate the impact of low-carbon city pilots on residents' carbon emissions. By introducing the Attitudes, Behaviours, and Circumstances theory as the analytical framework and compiling a direct carbon emission inventory of residents, this study attempts to fill the research gap. The results indicate that low-carbon city pilots could lower residents' carbon emissions by 7.3% annually, with a gradual strengthening trend over time. This study presents and validates three influencing mechanisms of the pilot policy, including improving green attitudes, advocating low-carbon behaviours, and optimizing living circumstances. The heterogeneity analysis demonstrates that the eastern and central regions with higher levels of economic development have generated significant policy effects. Although both the northern and southern pilot cities have lowered residents’ carbon emissions, the former has exhibited a stronger policy effect. Based on these findings, this study proposes several policy recommendations: innovate attitudinal guidance, nudge behavioural choices, shape external circumstances, and combine local characteristics.
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