The Coordinated Effects of CO2 and Air Pollutant Emission Changes Induced by Inter-Provincial Trade in China

Abstract

Inter-provincial trade leads to changes in CO2 and air pollutant emissions. However, there is a research gap regarding the coordinated effects (co-effects) between embodied CO2 and air pollutant emissions in trade. Understanding co-effects in inter-provincial trade is a prerequisite for driving the green transformation of trade and achieving coordination between pollution and carbon reduction. Here, we calculated provincial-level CO2 and air pollutant emission leakage in 2012 and 2017 based on a modified input–output model and, for the first time, investigated the co-effects between CO2 and air pollutant emission leakage caused by emissions transfers in China. Three types of co-effects, categorized as co-benefits, trade-offs, and co-damage, were discovered and defined to reveal the provincial differences. Furthermore, combined with structural decomposition analysis (SDA), we calculated the interannual variation in trade-induced emissions and identified the key driving factors of provincial-level co-effects from 2012 to 2017. Optimizing the energy structure has led to the greatest co-benefits, while changes in the industrial structure and emission coefficients have led to limited co-benefits in specific provinces. Variations in trade volume have led to co-damages across all provinces, and changes in emission coefficients have led to trade-offs in the majority of provinces. The case analysis confirmed that identifying and adjusting the key driving factors of co-effects can promote the transformation from co-damage and trade-offs to co-benefits. The findings implied a new approach for the reduction in pollution and carbon through inter-provincial trade.

Analysis of Influencing Factors and Prediction of the Peak Value of Industrial Carbon Emission in the Sichuan-Chongqing Region

“…To estimate overall agriculture net carbon emissions, Zhang and Cai employed the economywater-carbon coefficient technique, the IPCC carbon emissions accounting method, and the environmental input-output model [4]. Using an enhanced input-output model, Qi et al estimated CO 2 and air pollutant emission leakages at the provincial level in China in 2012 and 2017 based on dispersed dyes' carbon footprint [5]. Li et al evaluated the possible environmental damage caused by carbon emissions from the textile industry [6].…”