京津冀地区汽车运输碳排放影响因素研究

以空间相关性和空间异质性为基础，构建SLM-STIRPAT、SEM-STIRPAT和GWR-STIRPAT模型，对京津冀地区汽车运输碳排放进行测算和影响因素分析.结果表明：京津冀地区汽车运输碳排放存在显著空间相关性和空间异质性.人口对汽车运输碳排放呈正向影响；人均GDP对货运碳排放和总量碳排放呈正向影响，对客运碳排放呈负向影响，城镇化水平对汽车运输碳排放呈负向影响.第三产业增加值对客运碳排放和总量碳排放呈正向影响，对货运碳排放呈负向影响，人口对张家口市汽车运输碳排放影响最为显著；人均GDP对秦皇岛市和沧州市的汽车运输碳排放影响最为显著；城镇化水平对秦皇岛市的汽车运输碳排放影响最为显著；第三产业增加值对秦皇岛市的汽车运输碳排放影响最为显著.

Study on the driving factors of vehicle transport carbon emissions in Beijing-Tianjin-Hebei region

Based on the spatial correlation and spatial heterogeneity, the SLM-STIRPAT model, SEM-STIRPAT model and GWR-STIRPAT model were constructed to measure and analyze the driving factors of vehicle transport carbon emissions in Beijing-Tianjin-Hebei region. The results showed that:There were significant spatial correlation and spatial heterogeneity in vehicle transport carbon emissions in Beijing-Tianjin-Hebei region. The population size and had a positive impact on the vehicle transport carbon emissions. The per capita GDP had a positive impact on the vehicle freight transport and total vehicle transport carbon emissions, had a negative impact on the passenger transport carbon emissions. The urbanization level had a positive impact on the vehicle transport carbon emissions. The added value of the tertiary industry had a positive impact on the vehicle passenger transport and total vehicle transport carbon emissions, had a negative impact on vehicle freight transport carbon emissions. Population size had the most significant impact on vehicle transport carbon emissions in Zhangjiakou. The per capita GDP had the most significant impact on vehicle transport carbon emissions in Qinhuangdao and Cangzhou. The urbanization level had the most significant impact on the vehicle transport carbon emissions in Qinhuangdao. The added value of the tertiary industry had the most significant impact on the vehicle transport carbon emissions in Qinhuangdao.