中国CO_2排放的空间分异与驱动因素——基于198个地级及以上城市数据的分析

The implementation of national emission reduction targets and policies requires the in-depth participation and effective execution of cities. However, there is spatial heterogeneity in the CO₂ emissions of cities, and the driving factors and their contribution degrees vary. The article comprehensively uses methods such as the emission coefficient method, the coefficient of variation method, K - means clustering and geographical detector to explore the spatial heterogeneity and driving factors of CO₂ emissions in China at the urban scale. The conclusions are as follows: ① There is an obvious spatial heterogeneity in the CO₂ emissions at the urban level in China. The spatial heterogeneity of emission intensity is relatively significant, while the spatial heterogeneity of emission amount is relatively small, and the inter - urban difference in the CO₂ emission intensity of non - resource - based cities is the largest. ② Energy intensity is the dominant driving factor for the spatial heterogeneity of CO₂ emissions in resource - based and northern cities, and the urban economic scale is the dominant driving factor for the spatial heterogeneity of CO₂ emissions in non - resource - based and southern cities. The ranking and magnitude of the determining power of other driving factors vary. ③ The industrial structure and its advanced level have a relatively small determining power on the spatial heterogeneity of CO₂ emissions in various types of cities, and the urban economic density has a relatively small determining power on the spatial heterogeneity of CO₂ emissions in resource - based and northern cities. ④ The key interaction factors affecting the spatial heterogeneity of CO₂ emissions in resource - based and northern cities all include energy intensity, while the key interaction factors affecting the spatial heterogeneity of CO₂ emissions in non - resource - based and southern cities are relatively complex, and there is no interaction factor that plays a crucial determining role in the spatial heterogeneity pattern of urban CO₂. ⑤ Some factors with weak determining power will produce a non - linear enhancement after being superimposed with other factors, which will significantly increase their determining power level on the spatial heterogeneity of urban CO₂ emissions.

国家减排目标和政策的落实需要城市的深度参与和有力执行。但是,城市的CO_2排放存在空间分异性,且驱动因素及其贡献度各有不同。文章综合运用排放系数法、变异系数法、K-means聚类和地理探测器等方法,对城市尺度的中国CO_2排放空间分异与驱动因子进行探究,结论如下:①中国城市层面的CO_2排放存在明显的空间分异,排放强度的空间分异性较为显著,而排放量的空间分异性相对较小,且以非资源型城市CO_2排放强度的城市间差异最大。②能源强度是资源型和北方城市CO_2排放空间分异的主导驱动因子,城市经济规模是非资源型和南方城市CO_2排放空间分异的主导驱动因子,其他驱动因子的决定力排序和决定力大小则各有不同。③产业结构及其高级化水平对各类城市CO_2排放空间分异的决定力均较小,城市经济密度对资源型和北方城市的CO_2排放空间分异的决定力较小。④影响资源型和北方城市CO_2排放空间分异的关键交互因子均包含能源强度,而影响非资源型和南方城市CO_2排放空间分异的关键交互因子比较复杂,不存在对城市CO_2空间分异格局起关键性决定作用的交互因子。⑤一些决定力微弱的因子在与其他因子叠加后,会产生非线性增强,会显著提高其对城市CO_2排放空间分异的决定力水平。