The role of renewable energy, fossil fuel consumption, urbanization and economic growth on CO2 emissions in China

This study investigates the relationship between renewable energy, fossil fuel consumption, economic growth, urbanization and CO2 emissions in China via the commonly used Autoregressive Distributed Lag (ARDL) model under the Environmental Kuznets Curve (EKC) hypothesis examining the period from 1990 to 2020. The aim of this work is to test the role of long- and short-term dynamics of renewable energy consumption in reducing CO2 emissions in China. The findings strongly support the existence of an inverted U-shaped relationship between CO2 emissions and GDP per capita, both in the long and short term. Not surprisingly, fossil fuel use increases the level of CO2 emissions in China. We show that a 1% increase in fossil fuel consumption per capita increases the CO2 emission per capita by 0.235% in the long term. The role of renewable energy consumption in reducing CO2 emissions might result from a cumulative effect. A 1% increase in renewable energy consumption per capita decrease the CO2 emissions per capita by 0.259% in the long run, while our findings reveal that the rapid development of the renewable energy industry in China contemporarily increases CO2 emissions and 1% renewable energy consumption increase the CO2 emissions by 0.285% to 0.288% in the short term. Our conclusions suggest that China's energy policy should further encourage the use of renewable power sources in the energy mix and further increase awareness of the increased short-term levels of carbon emissions associated with the rapid development of the renewable energy industry in China. (C) 2021 The Author(s). Published by Elsevier Ltd.