The effect of natural and anthropogenic factors on haze pollution in Chinese cities: A spatial econometrics approach

By Haimeng Liu, Chuanglin Fang, Xiaoling Zhang, Zheye Wang, C. Bao, Fangzheng Li. 2017

305 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Health, Toxicology and Mutagenesis, Transportation

View Paper: https://www.semanticscholar.org/paper/bbfeb48b1ce456a9cd10f71e538b0b0f632fe699

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In Health, Toxicology and Mutagenesis

1. Wenwen Wang
2. Ming Zhang

Citations in the corpus

• Using the geographical detector technique to explore the impact of socioeconomic factors on PM2.5 concentrations in China (2019, methodology): “…spatial econometric models such as dynamic spatial panel model (Cheng et al., 2017), geographic weighted regression (Hu et al., 2013), spatial Durbin model (Liu et al., 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): “Moreover, numerous studies have verified that industrial structure plays a critical role in affecting air pollution (Liu, 2017; Jiang et al., 2018).”