Exploring the spatial spillover effects of industrialization and urbanization factors on pollutants emissions in China's Huang-Huai-Hai region
By Man Li, Chen Li, Ming Zhang. Journal of Cleaner Production, 2018
127 citations recorded by the source corpus.
Abstract The diffusion effect makes air pollution become a regional problem. The purpose of this paper is to explore the spatial spillover effects of most pollutants emissions and identify industrialization and urbanization factors affecting emissions from spatial econometric perspective. In recent years, air pollution in China's Huang-Huai-Hai region is the most serious in the whole nation. Based on the geographical weight matrix introduced in this paper, the spatial Durbin model (SDM) is employed to explore the direct and spatial spillover effects of industrialization and urbanization factors on 7 pollutant emissions in 53 cities of China's Huang-Huai-Hai region over the period 2009–2014. The results show that CO is the main pollutant component, followed by SO 2 , and NO x in 53 cities. The spatial autocorrelation strengthen of each pollutant in all cities is as the order: BC > PM 2.5 >CO > PM 10 > NH 3 > SO 2 > NO x . There are significant spatial aggregation effects of emissions of pollutants except NO x . Furthermore, the direct effects of per capita GDP, non-agricultural industries and urban residents' per capita consumption on pollutants emissions are the biggest on the whole. The direct effect of per capita GDP on each pollutant emissions is entirely negative, while that of non-agricultural industries is positive on the whole. The spatial spillover effects of above three factors on pollutants emissions are the largest; the spatial spillover effect of non-agricultural industries is positive, while that of per capita GDP is negative. According to the results, some policy implications are provided to control regional air pollution.
Subfields: Economics and Econometrics, Environmental Engineering, Health, Toxicology and Mutagenesis
View Paper: https://www.semanticscholar.org/paper/63aa10400ca105ac71b1d914dd5fd63107a1285f
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Citations in the corpus
- Does industrial upgrading promote eco-efficiency? ─A panel space estimation based on Chinese evidence (2021, background): “However, many studies have demonstrated that industrial upgrading is spatially interconnected, which means that local industrial upgrading influence that of other areas, and vice versa (Brun et al., 2002; Ciccarelli and Fachin, 2017; Li et al., 2018; Wu et al., 2020).”
- Using the geographical detector technique to explore the impact of socioeconomic factors on PM2.5 concentrations in China (2019, background): “5 concentrations were mostly derived from urban ground air quality monitoring sites (Djalalova et al., 2010; Zhou et al., 2018) or emission inventory database (Guan et al., 2014; Li et al., 2018).”