Impact of Income, Density, and Population Size on PM2.5 Pollutions : A Scaling Analysis of 254 Large Cities in Six Developed Countries

Despite a large number of studies on multiple socioeconomic factors influencing urban PM2.5 pollutions in China, only a few comparable studies appeared for developed countries. We analyzed the impact of three major socioeconomic factors of city income per capita, population density of city, and population size of city to PM2.5 concentrations for 254 cities from six developed countries. We used the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) 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 but one income coefficients carried negative signs, supporting the applicability of Environmental Kuznet Curve. In contrast, the five density coefficients also produced statistically significant positive signs, supporting the results from the previous studies. However, we discovered an interesting “U” shaped distribution of density coefficients across the six subgroups of cities which may be unique in urban pollution from developed countries. The results from population coefficients were not conclusive, similar to the result from the previous studies. Implications from the results of this study for urban and national policy makers are discussed