Abstract
Clean and efficient use of coal in China entered the implementation stage in 2015, and a series of policies were established to promote the sustainable development of clean coal technologies (CCTs). However, the long-term effects of the clean coal technology policies (CCTPs) have not been evaluated, and the outbreak of coronavirus disease 2019 (COVID-19) would bring great uncertainty regarding the effectiveness evaluation. Employing deep learning approaches and spatial autocorrelation analysis, the present work intended to explore the air quality variation before and after the implementation of CCTPs, and investigate the association between air quality and socioeconomic factors to explore the internal mechanism of air quality improvement. Results showed that after implementing CCTPs, the air quality index (AQI) had an average reduction of 18.82%, and the identical drop in air pollution in 2018 implied a 2-year time lag of CCTPs. Additionally, emission reduction and deindustrialization were explored as two promising ways to improve air quality while promoting energy transformation. The findings indicated that the Chinese government ought to pay more attention to long-term plans; industrial restructuring and environmental protection should be insisted upon to realize sustainable energy development. By providing a perspective on air quality improvement after the policies are implemented, this study can lead practitioners and academia to a comprehensive and objective view of clean coal policies.
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