京津冀地区经济社会要素与碳排放的时空耦合关系

碳排放受区域发展水平、产业结构、消费模式等经济社会多要素的综合影响。开展区域经济社会要素与碳排放的时空耦合关系研究,不仅有助于揭示区域内部各要素空间格局对碳排放的影响机制,而且对于制定差别化的经济、环境和产业政策,推动区域低碳协调和均衡发展也具有重要的实践意义。基于京津冀地区2005—2020年的相关统计数据,采用区域重心模型、空间关联性分析方法、地理集中度、不一致指数、空间自相关分析等方法,探讨了区域人口、经济、消费水平、第二产业、贫困度、碳排放量等经济社会要素的重心转移特征和地理集中度,并对各要素与碳排放的空间关系进行了分析。结果表明：(1)2005—2020年京津冀地区各经济社会要素均不同程度偏离区域几何中心,各要素在空间上长期处于不均衡状态,但随着时间推移,不均衡状态有所减缓。(2)研究期内,各经济社会要素的重心移动轨迹具有明显的阶段性,京津冀地区各要素重心格局易于波动,碳排放与其他要素重心空间耦合性呈现波动式变化。(3)人口因素是影响碳排放量增长的主要因素。贫困度、第二产业比重、经济发展水平的灰色关联度数值也都较高,贫困度、第二产业比重、经济发展水平也是碳排放量增长的主要驱动...

Spatial-temporal coupling relationship between economic and social factors and carbon emissions in Beijing-Tianjin-Hebei region

Carbon emissions are comprehensively influenced by multiple economic and social factors such as regional development level, industrial structure, and consumption pattern. Studying the spatio-temporal coupling relationship between regional economic and social factors and carbon emissions not only helps to reveal the influence mechanism of the spatial pattern of each factor within the region on carbon emissions, but also has important practical significance for formulating the differentiated economic, environmental and industrial policies and promoting regional low-carbon coordinated and balanced development. Based on the relevant statistical data of Beijing-Tianjin-Hebei region from 2005 to 2020, the regional center of gravity model, spatial correlation analysis method, geographic concentration, inconsistency index, and spatial autocorrelation analysis were used to explore the characteristics and geographic concentration of regional population, economy, consumption level, secondary industry, poverty, carbon emission and other economic and social factors of center of gravity shift, and the spatial relationship between each factor and carbon emissions was analyzed. The results show that (1) all economic and social factors in Beijing-Tianjin-Hebei region deviated from the regional geometric center to different degrees from 2005 to 2020, and each factor was in a long-term spatial imbalance, but the imbalance has been slowed down over time. (2) During the study period, the trajectory of the center of gravity of each economic and social factor had obvious phases, the pattern of the center of gravity of each factor in the Beijing-Tianjin-Hebei region was easy to fluctuate, and the spatial coupling of carbon emissions and the center of gravity of other factors showed fluctuating changes. (3) Demographic factors are the main factors affecting the growth of carbon emissions. The gray correlation values of poverty, the proportion of secondary industry, and the level of economic development are also high. Poverty, the proportion of secondary industry, and the level of economic development are also the main drivers of carbon emission growth. (4) The geographic concentration of each factor in the counties (cities and districts) of Beijing-Tianjin-Hebei region mostly shows a spatial distribution pattern of low in the north and high in the south, and mainly shows the difference between "core-periphery". (5) The imbalance index of each factor in the Beijing-Tianjin-Hebei region gradually increased from 2005 to 2020, and the spatial distribution of each factor and carbon emission gradually changed towards spatial balance, and this trend of change passed the spatial autocorrelation test, so that the regional collaborative development helped carbon emission reduction.