Impact of Income, Density, and Population Size on PM 2.5 Pollutions: A Scaling Analysis of 254 Large Cities in Six Developed Countries

Moon-Jung Kim, Yu-Sang Chang and Su-Min Kim
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Moon-Jung Kim: Department of Business, Gachon University, 1342 Seongnam-daero, Sujung-gu, Seongnam 13120, Gyeonggi-do, Korea
Yu-Sang Chang: Gachon Center for Convergence Research, Gachon University, 1342 Seongnam-daero, Sujung-gu, Seongnam 13120, Gyeonggi-do, Korea
Su-Min Kim: Department of Business, Gachon University, 1342 Seongnam-daero, Sujung-gu, Seongnam 13120, Gyeonggi-do, Korea

IJERPH, 2021, vol. 18, issue 17, 1-30

Abstract: Despite numerous studies on multiple socio-economic factors influencing urban PM 2.5 pollution in China, only a few comparable studies have focused on developed countries. We analyzed the impact of three major socio-economic factors (i.e., income per capita, population density, and population size of a city) on PM 2.5 concentrations for 254 cities from six developed countries. We used the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model with three separate data sets covering the period of 2001 to 2013. Each data set of 254 cities were further categorized into five subgroups of cities ranked by variable levels of income, density, and population. The results from the multivariate panel regression revealed a wide variation of coefficients. The most consistent results came from the six income coefficients, all of which met the statistical test of significance. All income coefficients except one carried negative signs, supporting the applicability of the environmental Kuznet curve. In contrast, the five density coefficients produced statistically significant positive signs, supporting the results from previous studies. However, we discovered an interesting U-shaped distribution of density coefficients across the six subgroups of cities, which may be unique to developed countries with urban pollution. The results from the population coefficients were not conclusive, which is similar to the results of previous studies. Implications from the results of this study for urban and national policy makers are discussed.

Keywords: PM 2.5 concentrations; city income per capita; population density; population size; STIRPAT model; threshold regression; environmental Kuznet curve (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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