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Challenges and Opportunities Facing Emerging Economies

Urbanization, Air Quality, and the Panel Threshold Effect in China Based on Kernel Density Estimation

, &
Pages 3575-3590 | Published online: 19 Sep 2019
 

ABSTRACT

The dynamic evolution of urbanization was analyzed in panel data for 30 provinces in China from 2000 to 2014, by using kernel density estimation across China’s regions. Using STIRPAT modeling, the study also analyzed the effects of economic growth and urbanization on PM2.5 with respect to the eastern, central, and western regions, and the entire nation. Different relationships were found among regions. The economic growth, population, energy consumption structure, industrialization, and FDI were the key factors influencing air quality. Verification of the EKC curve indicated that the central region was linear, and the other regions had an inverted N-shape. The dynamic evolution of urbanization and the air quality were also analyzed with a panel threshold regression model. Urbanization in China has a triple threshold for air quality as an economic growth threshold. There were significant double thresholds in the eastern, central, and western regions. In view of the above analysis, policies and recommendations are proposed regarding how to change the mode of economic development and narrow the urbanization gap among regions to reduce air pollutant emissions and facilitate sustainable development.

Acknowledgments

This work is supported by a project of the National Social Science Foundation of China (approved: 19BGL196), a project of the National Social Science Foundation of China (approved: 19BJL033),a project of National Natural Science Foundation of China (approved: 71573110), a key project of Philosophy and Social Science of Jiangsu, China (approved: 2018SJZDI054), a project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).

Additional information

Funding

This work was supported by the a key project of Philosophy and Social Science of Jiangsu, China [2018SJZDI054];National Social Science Foundation of China [19BGL196,19BJL033];National Natural Science Foundation of China [71573110];a project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions;

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