基于夜间灯光数据的湖南省县域碳排放时空格局及影响因素研究

研究碳排放的时空格局演变及影响因素对指导制定差异化的碳减排政策具有重要意义。基于夜间灯光数据, 在估算湖南省各县区碳排放量的基础上, 结合空间统计、空间自相关、热点分析、地理加权回归、GIS等方法研究了湖南省县域碳排放的空间分异、时空格局特征与影响因素。研究结果表明: (1)2013-2017年, 湖南省能源消费碳排放总体上呈现东高西低的空间格局, 碳排放主要集中于区域的市辖区, 县域碳排放最高点在长沙市市辖区; (2)湖南省能源消费碳排放存在较为显著的空间正相关, 全省县域尺度能源消费碳排放全局Moran's I指数整体呈现出逐年上升的趋势, 各市的市辖区在中心相互辐射, 表现出显著的集聚现象, 并形成了碳排放“高-高型”分布特征; (3)湖南省能源消费碳排放量的冷热点格局表现出湘南地区冷点扩张, 湘中地区热点扩张的演变趋势, 从2013年到2017年, 热点区与次热点区由11个升至13个, 湘中地区与其他地区的冷热点差距在逐步拉大; (4)影响湖南省县域能源消费碳排放量的4个影响因素与碳排放均表现为正相关性, 其影响程度依次为人口、人均GDP、第二产业比重与单位GDP能耗。

Spatial-temporal pattern and influence factors of county carbon emissions in Hunan Province based on nightlight data

Studying the spatiotemporal pattern evolution and influence factors of carbon emissions is a great significance to guide the formulation of differentiate carbon emission reduction policies.Based on the nightlight data,we estimated the carbon emissions of each county in Hunan Province by combining with spatial statistics,spatial autocorrelation,hot spot analysis,geographic weighted regression,GIS and other methods to study the spatial differentiation,spatial and temporal pattern characteristics and influencing factors.The results show that:(1)From 2013 to 2017,the carbon emissions of energy consumption in Hunan Province generally showed a spatial pattern of high in the east and low in the west.Carbon emissions were mainly concentrated in the regional municipal jurisdictions,and the highest point of county carbon emissions was in the municipal jurisdiction of Changsha.(2)There was a significant spatial positive correlation between the energy consumption carbon emissions of Hunan Province.The overall Moran's I index of the county-level energy consumption carbon emissions of the province showed an upward trend year by year.The municipal districts of each city radiated each other in the center,showing a significant agglomeration phenomenon,and formed the"high-high"distribution characteristics of carbon emissions.(3)The cold-hot state of energy consumption carbon emissions in Hunan Province showed the expansion of cold spots in southern Hunan and the evolution of hot spots in central Hunan.From 2013 to 2017,the number of hot spots and sub-spots rose from 11 to 13.The difference between the cold-hot spots in the central region and other regions was gradually widening. (4) The four factors that affect the carbon emission of energy consumption in Hunan Province are positively correlated with the carbon emission, and their influence degrees are population, GDP per capita, the proportion of the secondary industry in turn and energy consumption per unit GDP.