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Spatial Variation of the Effect of Multidimensional Urbanization on PM(2.5) Concentration in the Beijing–Tianjin–Hebei (BTH) Urban Agglomeration

Atmospheric PM(2.5) pollution has become a prominent environmental problem in China, posing considerable threat to sustainable development. The primary driver of PM(2.5) pollution in China is urbanization, and its relationship with PM(2.5) concentration has attracted considerable recent academic int...

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Detalles Bibliográficos
Autores principales: Huang, Qianyuan, Chen, Guangdong, Xu, Chao, Jiang, Weiyu, Su, Meirong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624147/
https://www.ncbi.nlm.nih.gov/pubmed/34831832
http://dx.doi.org/10.3390/ijerph182212077
Descripción
Sumario:Atmospheric PM(2.5) pollution has become a prominent environmental problem in China, posing considerable threat to sustainable development. The primary driver of PM(2.5) pollution in China is urbanization, and its relationship with PM(2.5) concentration has attracted considerable recent academic interest. However, the spatial heterogeneity of the effect of urbanization on PM(2.5) concentration has not been fully explored. This study sought to fill this knowledge gap by focusing on the Beijing–Tianjin–Hebei (BTH) urban agglomeration. Urbanization was decomposed into economic urbanization, population urbanization, and land urbanization, and four corresponding indicators were selected. A geographically weighted regression model revealed that the impact of multidimensional urbanization on PM(2.5) concentration varies significantly. Economically, urbanization is correlated positively and negatively with PM(2.5) concentration in northern and southern areas, respectively. Population size showed a positive correlation with PM(2.5) concentration in northwestern and northeastern areas. A negative correlation was found between urban land size and PM(2.5) concentration from central to southern regions. Urban compactness is the dominant influencing factor that is correlated positively with PM(2.5) concentration in a major part of the BTH urban agglomeration. On the basis of these findings, BTH counties were categorized with regard to local policy recommendations intended to reduce PM(2.5) concentrations.