Spatial heterogeneity analysis of CO2 emissions in China’s thermal power industry: GWR model

Lei Wen,Fang Liu

doi:10.1051/e3sconf/202126001005

Abstract

The thermal power industry is a major contributor to China's CO2 emissions, and its absolute emissions are still increasing year by year. Hence, this paper introduced a geographically weighted regression model to explore the spatial heterogeneity of different driving factors for this industry's CO2 emissions. The empirical results show that standard coal consumption is a decisive factor affecting thermal power industry's CO2 emissions, and its response to the western region is at the forefront. The average utilization hours of thermal power equipment in the central region exert a profound impact, while the western region devotes a lot to the installed capacity, and these two variables have great potential for CO2 emission mitigation. However, the urbanization level and per capita electricity consumption have a slight effect on CO2 emissions. These findings furnish constructive reference and policy implications to achieve emission abatement targets of different regions.

Highlights

On account of the rapid economic growth and enormous energy consumption, China overtook the United States in 2006 to become the world's biggest emitter of CO2 discharges [1]
Through the China Electric Power Yearbook over the period 2005-2017, we found the total electricity consumption, average utilization hours of thermal power equipment, standard coal consumption, and thermal power installed capacity in 30 provinces [9]
In order to ensure that there are no multiple collinearity and redundant independent variables in the geographically weighted regression (GWR) model, it is necessary to check the multicollinearity of the selected variables

Summary

Introduction

On account of the rapid economic growth and enormous energy consumption, China overtook the United States in 2006 to become the world's biggest emitter of CO2 discharges [1]. The power generation accounts for the maximum share in fuel consumption and CO2 emissions. The thermal power as an important part of power supplies, it is of vital importance to discuss the drivers of this industry's CO2 emissions. Many scholars have attempted to make an in-depth study on the power sector's CO2 emission through the analysis of contributing factors. The researches mainly focus on the index decomposition analysis (IDA) method and econometric model. Some scholars have realized the importance of spatial effect and have begun to fully study spatial econometric methods. GWR model has gained increasing popularity on CO2 emissions and its driving forces [3, 4]. There is no report on the application of GWR model in thermal power sector's CO2 emissions

Methods

Results

Conclusion