Literature DB >> 31610446

Pareto law-based regional inequality analysis of PM2.5 air pollution and economic development in China.

Kai Cao1, Wenting Zhang2, Shaobo Liu3, Bo Huang4, Wei Huang5.   

Abstract

Regional inequality has caused large social and economic problems in China. Numerous researchers have sought to understand the status of economic inequality in the past decades. However, studies are lacking on other aspects of regional inequality, particularly when multiple facets must be considered. In this study, we have innovatively proposed a Pareto law-based method that can help assess multiple dimensions of regional inequality simultaneously. With this approach, we can rank multiple aspects of inequality and provide robust, reasonable goals for different groups of administrative districts. The proposed approach was successfully implemented by using Chinese data for 2015 and 2016, a period during which China was experiencing both severe PM2.5 pollution and economic regional inequality. The results indicate that (1) Shanghai and Shenzhen represent the optimal condition of economic development; (2) different from the spatial distribution of economic inequality alone, inequality was higher in central China for both economic development and PM2.5 air quality; (3) in the context of severe economic inequality in China, the tradeoff between economic development and air quality will result in a relatively equitable condition. In addition, the proposed method is open-ended and can be extended to incorporate more aspects of regional inequality. This approach appears to possess substantial potential for integration into decision-making regarding regional inequality.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Keywords:  China; GDP; PM(2.5); Regional inequality

Mesh:

Substances:

Year:  2019        PMID: 31610446     DOI: 10.1016/j.jenvman.2019.109635

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Does environmental regulation reduce China's haze pollution? An empirical analysis based on panel quantile regression.

Authors:  Congxin Li; Guozhu Li
Journal:  PLoS One       Date:  2020-10-28       Impact factor: 3.240

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.