Spatial linkage analysis of the impact of regional economic activities on PM2.5 pollution in China

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Using the geographical detector technique to explore the impact of socioeconomic factors on PM2.5 concentrations in China (2019, methodology): “, 2017), spatial lag model (SLM) and spatial errors model (SEM) (Hao and Liu, 2016; Ma et al., 2016) for correlation analysis.”
Quantifying the spatial heterogeneity influences of natural and socioeconomic factors and their interactions on air pollution using the geographical detector method: A case study of the Yangtze River Economic Belt, China (2019, unknown): “…states hat population density, industrial production M AN US CR IP T AC CE PT ED activities, fossil fuel consumption, and automobile exhaust are the primary sources of air pollution (Hixson et al., 2012; Lin and Wang, 2016; Ma et al., 2016; Wu et al., 2016; Cheng et al., 2017; Jiang et al., 2018).”