4.7 Article

Unveiling the past, shaping the future: Analyzing three centuries of data to explore China's trajectory towards carbon neutrality

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 420, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2023.138348

Keywords

China; Carbon neutrality; EKC; Historical data; Dynamic ARDL

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China is facing immense pressure to reduce greenhouse gas emissions and achieve carbon neutrality by 2060. This study analyzes China's historical emissions path and examines the impact of economic growth, education, population growth, and political regimes on carbon neutrality. The findings suggest that the political system plays a significant role in China's environmental integrity, highlighting the need for a pro-environmental political sphere and the implementation of environmental governance.
China is under enormous pressure - at home and abroad - to mitigate its greenhouse gas (GHG) emissions, which threaten its carbon neutrality target by 2060. The historical emissions growth and the factors affecting this growth can be instrumental in designing China's carbon neutrality target by 2060. However, a study focusing on China's historical emissions is rare, creating a substantial gap in the literature. As such, this study aims to analyze China's historical emissions path and how China's carbon neutrality is affected by economic growth, education, population growth, and political regimes. These variables have been chosen based on theory and empirical literature. We employ extensive time-series data from 1850 to 2021 and deploy the novel Dynamic Autoregressive Distributed Lag (ARDL) simulation model. Carbon neutrality has been measured using greenhouse gas emissions per capita. The study finding reveals an inverted U-shaped relationship between GDP and GHG emissions, proving that Environmental Kuznets Curve (EKC) hypothesis is valid for China when participatory form of governance is considered. But the study fails to validate the EKC hypothesis when the liberal form of governance is employed. Population growth and education boost GHG emissions in the long run in the model with participatory form of governance. Contrarily, in the model with liberal form of governance, the population increases GHG emissions in the short and long run, while education increases GHG emissions only in the long run. Participatory form of governance decreases GHG emissions in the long run, but liberal one decreases GHG emissions only in the short run. Overall, the variations in the political system can have heterogenous effects on China's environmental integrity. As such, Beijing's policy should focus more on the development of a political sphere that is pro-environmental and that stresses on the implementation of environmental governance to tackle China's environmental dilemma. Our findings provide numerous policy suggestions to achieve China's carbon neutrality target by 2060.

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