Spatiotemporal Patterns and Decomposition Analysis of CO2 Emissions from Transportation in the Pearl River Delta

Abstract

Controlling and mitigating CO2 emissions is a challenge for the global environment. Furthermore, transportation is one of the major sources of energy consumption and air pollution emissions. For this reason, this paper estimated CO2 emissions by the bottom-up method, and presented spatiotemporal patterns by spatial autocorrelation methods from transportation during the period 2006 to 2016. It further analyzed the impact factors of CO2 emissions in the Pearl River Delta by the Logarithmic Mean Divisa Index (LMDI)decomposition method. The results indicated that from 2006 to 2016, total CO2 emissions increased year by year. Guangzhou and Shenzhen were the major contributors to regional transportation CO2 emissions. From the perspective of different transport modes, intercity passenger transport and freight transport have always been dominant in the past 11 years. The results indicated that aviation transport was the largest contributor, and that travel by road was the second one. The CO2 emissions generated by rail and water transport were much lower than those from aviation. Private cars became the main source of urban passenger transport CO2 emissions, and their advantages kept increasing. The results indicated that the spatial agglomeration trend feature was negatively correlated, and the further the distance, the more similar the attributes. The cumulative contribution values of population, economic development, transport intensity, energy intensity and energy structure were all positive values, while the cumulative contribution values of transport structure and emission factor were negative. The findings of this study offer help for the scientific understanding of those CO2 emissions from transportation, and for adopting effective measures to reduce CO2 emissions and for the development of green transportation.