温室气体
地理
人口规模
人口
面板数据
政府(语言学)
环境科学
碳纤维
环境工程
计量经济学
人口学
生态学
数学
社会学
生物
复合数
哲学
语言学
算法
作者
Kaifang Shi,Guifen Liu,Yuanzheng Cui,Yizhen Wu
标识
DOI:10.1016/j.apgeog.2022.102855
摘要
Clarifying what urban spatial structure (US) is more conducive to reducing emissions and conserving energy provides scientific references for government departments and decision-makers to optimize and realize their “carbon reduction” goal. In light of the mixed results of previous studies, our study explored the effect of monocentric US (MUS) and polycentric US (PUS) on carbon emissions in China by using panel regression models and robust test methods based on an US quantification through remotely sensed nighttime light data. According to the findings, population size regulates the effect of US on carbon emissions. For cities with a population size less than 70.71 × 104–98.58 × 104, a MUS is more conducive to reducing carbon emissions, whereas for cities with a population size large than 70.71 × 104–98.58 × 104, a PUS performs better on carbon emission reduction. Further quantitative analyses reveal that the conditional effect of population size on the US—carbon emissions relationship is dependent on the relative magnitudes of the three mediating factors, e.g., the transportation, residents' lives, and industrial production and manufacturing. Our study determines the MUS and PUS most conducive to carbon emission reduction for different population sizes, which may lay the groundwork for a low-carbon urban planning system.
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