收缩视角下黄河中游城市碳排放时空格局及其影响因素

城市收缩作为城市化进程中的一种现象,与碳排放之间的关系错综复杂。当前从多维度收缩视角来探究碳排放量驱动因素的研究鲜有。据此,从人口、社会和经济三个维度构建城市收缩评价体系,利用黄河中游四省50个城市2012-2020年面板数据,基于熵值法、夜间灯光指数及地理探测器等方法探究城市收缩对碳排放时空差异的影响。结果表明:①黄河中游资源型城市收缩现象最为严重,呈现"大分散,小聚集"特征。人口收缩占比最多,综合收缩最少。②碳排放总量在研究时段内从2327 Mt增长到3040 Mt,热点区域分布在鄂尔多斯市、乌海市、呼和浩特市、忻州市和朔州市;冷点区域从陕西省和河南省分散分布逐渐向河南省集聚。碳排放总量两极分化现象明显,高值区域数量少,数值大,且逐年增幅大;低值区域数量多,数值低,呈逐年降低趋势。成长型和成熟型资源城市是碳排放量的热点区域,同时城市收缩加剧了碳排放量;衰退型和再生型资源城市已经成为碳排放量的冷点区域,此时的城市收缩对碳排放量抑制作用加强。③城市收缩对于碳排放量的影响是复杂的,经济收缩对碳排放空间分异的解释力最强,人口收缩解释力最小,多数影响因素空间叠加后会产生双因子增强作用,且主导因素由人口和经济收缩转变为社会和经济收缩。可见,黄河中游城市碳排放时空格局及影响因素存在一定差异,因此,在制定双碳行动方案时应综合考虑这些差异,进而可提出有针对性且能适应于地区发展需要的节能减排对策。

Spatio-temporal pattern and influencing factors of carbon emissions in the middle reaches of the Yellow River from the perspective of urban shrinkage

As a phenomenon in the process of urbanization, the relationship between urban shrinkage and carbon emissions is complicated. There are few studies to explore the driving factors of carbon emissions from the perspective of multi-dimensional urban shrinkage. Thus, we constructed an urban shrinkage evaluation system from three dimensions of population, society and economy, and used the panel data of 50 cities in four provinces of the middle reaches of the Yellow River from 2012 to 2020 in this paper. The impact of urban shrinkage on spatio-temporal differences of carbon emissions is explored by the entropy method, night lighting index, and geographic detector. The results verify that,first the shrinkage phenomenon of resource-based cities along the middle reaches of the Yellow River is the most serious one, which shows the characteristics of "large dispersion and small gathering". The proportion of population shrinkage is the largest one, and the comprehensive shrinkage is the least sector. Second, the total carbon emissions increased from 2327 Mt to 3040 Mt during the study period, and the hot spots are distributed in Ordos, Wuhai, Hohhot, Xinzhou, and Shuozhou. The cold spots gradually changed from scattered distribution in Shaanxi and Henan to agglomerate in Henan Province. The total carbon emissions are polarized and the number of high-value areas is small, but the value is large, and the increase rate is larger and larger; the number of low-value areas is large, but the value is low, and the trend is decreasing year by year. Growing and mature resource cities are the hot pots of carbon emissions, and urban shrinkage aggravates carbon emissions; Declining and renewable resource cities become the cold spots of carbon emissions, inhibitory effect is strengthened. Third, the impact of urban shrinkage on carbon emissions is complex, and the influencing factors of economic contraction have the strongest explanatory power on the spatial differentiation of carbon emissions. Conversely, population shrinkage has the least explanatory force, and the spatial superposition of most influencing factors will produce a two-factor enhancement. And the dominant factors have changed from population and economic contraction to social and economic contraction. Overall, there are differences in the spatial and temporal patterns of urban carbon emissions and their influencing factors along the middle reaches of the Yellow River. Therefore, these differences should be considered so that the energy-saving and emission-reduction countermeasures can be put forward and adapted to the needs of regional development.