Assessing the pollution convergence across Chinese cities by considering ecological indicators: A continuous distribution dynamics approach

Jianxin Wu; Ziwei Feng; Sajid Anwar

doi:10.1016/j.ecolind.2021.107552

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Assessing the pollution convergence across Chinese cities by considering ecological indicators: A continuous distribution dynamics approach

Journal article

Open access

Peer reviewed

Assessing the pollution convergence across Chinese cities by considering ecological indicators: A continuous distribution dynamics approach

Jianxin Wu, Ziwei Feng and Sajid Anwar

Ecological Indicators, Vol.126, pp.1-11

2021

DOI: https://doi.org/10.1016/j.ecolind.2021.107552

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Abstract

PM2.5 concentration

distribution dynamics

poverty-environment trap

conditioning analysis

We employ a nonparametric distribution dynamics approach to examine the long-run trend of particulate matter (PM2.5) air pollution in China. Analysis of the data from 288 Chinese prefectural and above (PAA) level cities over the 2001–2019 period shows evidence of convergence in the estimated long-run distribution of air pollution, which is consistent with Environmental Kuznets Curve hypothesis (EKC). However, presence of strong persistence suggests that convergence process takes considerable time. Conditioning analysis shows that China’s environment policy since 2013 has been successful in driving the air pollution in several cities to converge to a lower level. Furthermore, we uncover a poverty-environment trap in the estimated long-run distribution. Our analysis highlights the need for targeted environmental policies in heterogeneous city clusters in China. Lessons learned from China’s experience can also be useful to policy makers in other developing countries.

Details

Title: Assessing the pollution convergence across Chinese cities by considering ecological indicators: A continuous distribution dynamics approach
Authors: Jianxin Wu (Author) - Jinan University
Ziwei Feng (Author) - Jinan University
Sajid Anwar (Author) - University of the Sunshine Coast, Queensland, School of Business and Creative Industries
Publication details: Ecological Indicators, Vol.126, pp.1-11
Publisher: Elsevier BV
Date published: 2021
DOI: 10.1016/j.ecolind.2021.107552
ISSN: 1872-7034; 1470-160X
Copyright note: © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Organisation Unit: School of Business and Creative Industries; Indigenous and Transcultural Research Centre; University of the Sunshine Coast, Queensland; USC Business School - Legacy
Language: English
Record Identifier: 99521808402621
Output Type: Journal article

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Web Of Science research areas: Biodiversity Conservation; Environmental Sciences

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