闽三角地区碳排放时空差异及影响因素研究

以闽三角地区为研究对象，以2005~2017年为研究期，构建城市尺度的碳排放清单，应用对数平均迪氏指数分解方法从时间维度的纵向比较和典型年份城市横向比较两个维度开展了驱动因素的分解分析及评价，探讨了闽三角碳排放变化影响因素的时空差异.结果显示：研究期内闽三角CO₂排放增长较快，从2005年的74.08Mt增加到2017年169.48Mt，增幅为128.75%.其中，泉州贡献最大，占比为67.93%.碳排放变化趋势分析来看，产业结构和经济增长为导致闽三角地区碳排放量增长的主要因素，累计贡献度分别为30.38%和12.21%，能源结构为抑制碳排放的重要影响因素，累计贡献度为-45.76%.时空差异上看，能源结构效应在研究期内均表现为抑制效应，最大贡献率为52.95%；而产业结构效应均表现为促进效应，最大贡献率为33.85%.在研究期内，漳州市碳减排力度最大，最大净减排148.27Mt.而泉州市经济增长和产业结构效应贡献率较大，未来仍具有较大的减排空间.厦门市经济增长和产业结构效应贡献率均低于参考值，且在研究期内变动幅度较小，碳减排压力较低.研究结果深化了闽三角地区碳排放的时空格局及影响因素的科学认识，为闽三角地区及相似城市群的减排治理提供了有益借鉴.

A spatial-temporal decomposition analysis of CO2 emissions in Fujian Southeast Triangle Region

In the present study, the carbon emissions inventory at city level is first constructed for Fujian Southeast Triangle Region during the period 2005~2017. The temporal and spatial differences of CO₂ emissions changes and main driving factors of emissions are explored by using the Logarithmic Mean Divisia Index Method. Empirical results show that:During the period 2005~2017, the CO₂ emissions has increased rapidly, from 74.08 Mt in 2005 to 169.48 Mt in 2017, an increase of 128.75%. Among them, Quanzhou City is the top carbon emitter, representing high to 67.93%. In terms of the emissions change trend, the industrial structure and economic growth are the main factors leading to the increase in carbon emissions in Fujian Southeast Triangle Region, contributing to 30.38% and 12.21%, respectively. While the energy structure is an important factor in controlling carbon emissions, contributing to -45.76%. In terms of temporal and spatial differences, the energy structure effect exhibits an inhibitory effect, with a maximum contribution rate of 52.95%. While the industrial structure effect exhibits a promotion effect, with a maximum contribution rate of 33.85%. During the study period, there exists the largest reduction amount of carbon emissions in Zhangzhou City, with a maximum net emission reduction of 148.27 Mt. The contribution rates of economic growth and industrial structure effects in Quanzhou City are relatively high, indicating that there is still a great potential for emissions reduction in the future. The contribution rates of economic growth and industrial structure effects in Xiamen City are both lower than the reference value, and their fluctuations are relatively small, showing that the pressure of carbon emissions reduction is rather low. These results have deepened the scientific understanding of the spatial and temporal pattern and driving factors of carbon emissions in Fujian Southeast Triangle Region, and also provided some valuable recommendations for the government to abate emissions in this region or similar urban agglomerations.