Retraction Note: China’s 2060 Carbon-neutrality Agenda: The Nexus Between Energy Consumption and Environmental Quality (Environmental Science and Pollution Research, (2022), 29, 37, (55728-55742), 10.1007/S11356-022-19456-9)

Abstract

This study examined the nexus between energy consumption and environmental quality in light of China’s 2060 carbon-neutrality agenda utilizing annual frequency data from 1971 to 2018. In order to obtain valid and reliable outcomes, more robust econometric techniques were employed for the analysis. From the results, all the variables were first differenced stationary and cointegrated in the long-run. The elastic effects of the predictors on the explained variable were explored through the ARDL, FMOLS, and the DOLS techniques, and from the discoveries, energy utilization worsened environmental quality in the country via more CO2 emissions. Also, industrialization and urbanization deteriorated the country’s environmental quality; however, technological innovations improved ecological quality in the nation. On the causal connections between the variables, a unidirectional causality from energy consumption to CO2 effluents was discovered. Also, feedback causalities between industrialization and CO2 secretions, and between urbanization and CO2 exudates were disclosed. However, there was no causality between technological innovations and CO2 emanations. Based on the findings, the study recommended among others that, since energy consumption pollutes the environment, the country should transition to the utilization of renewable energies. Also, the government should allocate more resources to the renewable energy sector. This will help increase the portion of clean energy in the country’s total energy mix. Furthermore, research and development that are linked to the utilization of green energies should be supported by the government. Data constraints were the main limitation of this exploration. Therefore, in the future, if more data become available, similar explorations could be conducted to check the robustness of our study’s outcomes.