Identifying the effects of industrial land expansion on PM2.5 concentrations: A spatiotemporal analysis in China

• Published in: Ecological indicators 2022-08, Vol.141, p.109069, Article 109069
• Main Authors: Li, Qiao, Chen, Wei, Li, Meng, Yu, Qianyu, Wang, Yanan
• Format: Article
• Language: English
• Subjects: China; Industrial land expansion; PM2.5 concentrations; Regional differences
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2022.109069

•Use the balanced panel data of 324 cities in China from 2007 to 2016.•Investigate the changes of industrial land expansion and PM2.5 concentrations.•The impact of industrial land expansion on PM2.5 concentrations is estimated.•Socioeconomic and meteorological factors play a key role in PM2.5 concentrations.•Suggestions on land and industrial policies are put forward for different regions. Industrial land is a prerequisite for industrial development and a crucial factor in promoting local economic growth. However, while promoting industrial development, industrial land expansion has produced much environmental pollution, but its impact has not been effectively evaluated. Based on the balanced panel data of 324 cities in China from 2007 to 2016, the effect of industrial land expansion on PM2.5 concentrations is studied using a spatial econometric model. The results show the evident regional heterogeneity of industrial land expansion. The eastern region has the largest expansion scale. Additionally, since 2013, the scale of industrial land expansion has decreased. The vast cities in the central and eastern regions have relatively high PM2.5 concentrations, especially in the North China Plain. Furthermore, the overall PM2.5 concentrations show a downward trend; however, a noticeable interannual fluctuation has been observed. Besides, the industrial land expansion has significantly promoted increased PM2.5 concentrations, both nationally and regionally. The most significant impact is in the eastern region, and the smallest impact is in the central region. Population density (POPD), road density (RORD), and temperature (TEM) positively correlate with PM2.5 concentrations, whereas economic development levels (EDL), industrial structure upgrading (ISU), vegetation coverage (NDVI), and precipitation (PRE) have varying effects on PM2.5 concentrations in each region.