京津冀地区汽车运输碳排放影响因素研究

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Abstract

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.

Key words： Beijing-Tianjin-Hebei region vehicle transport carbon emissions STIRPAT model spatial econometrics model geographically weighted regression model

Received: 04 January 2018

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