2011—2020年碳排放的时空特征与驱动力：来自中国十九个城市群的实证证据

摘要

Urban agglomerations, which are critical hubs of population density and industrial activity, face escalating carbon emissions challenges that threaten global climate goals. Despite their significance, comparative analyses of emission drivers across different tiered areas including national, regional, and sub-regional urban agglomerations remain scarce. We first investigated spatiotemporal emission patterns and clustering characteristics across five national, six regional, and eight sub-regional urban agglomerations in the first five years (20112015) and the next five years (20162020) utilizing global and local spatial autocorrelation techniques. We then quantified the response of carbon emissions across these urban agglomerations to multiple socioeconomic drivers using three spatial econometric models. The carbon emissions of the Yangtze River Delta (YRD), Central Plains (CP), and Hohhot-Baotou-Ordos-Yulin (HBOY) urban agglomerations were the highest at the national, regional, and sub-regional levels, respectively. The average growth rates of regional urban agglomerations exhibited upward trends after 2016, whereas the growth rates for national and sub-regional urban agglomerations gradually moderated over time. At the spatial level, higher total carbon emissions were recorded in the middle and southern cities of the HBOY urban agglomeration, the eastern and southwestern cities of the Beijing-Tianjin-Hebei (BTH) urban agglomeration, the eastern cities of the YRD urban agglomeration, and the southern cities of the Chengdu-Chongqing (CC) urban agglomeration. All nineteen urban agglomerations exhibited strong spatial dependence with significant clustering characteristics in the first five years and the next five years. Energy intensity and environmental pollution were significantly positively associated with the variability of carbon emissions across 19 urban agglomerations in China over ten years. Economic scale and government intervention showed significant positive associations primarily in the first five years. The negative association of trade openness with carbon emissions became increasingly prominent in the first five years. These findings emphasize the importance of formulating effective carbon reduction policies based on the unique characteristics of urban agglomerations and tailoring them to the local conditions. In addition, this integrated approach provides spatially nuanced insights for targeted policy design, supporting China’s national climate goals and global climate action.