Understanding the distribution and drivers of PM<sub>2.5</sub> concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression.

Su, Zhangwen; Lin, Lin; Chen, Yimin; Hu, Honghao

Understanding the distribution and drivers of PM_2.5 concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression.

Su, Zhangwen; Lin, Lin; Chen, Yimin; Hu, Honghao.

Affiliation

Su Z; College of Applied Chemical Engineering, Zhangzhou Institute of Technology, Zhangzhou, 363000, China. FujianSZW@126.com.
Lin L; Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20740, USA.
Chen Y; College of Applied Chemical Engineering, Zhangzhou Institute of Technology, Zhangzhou, 363000, China.
Hu H; College of Applied Chemical Engineering, Zhangzhou Institute of Technology, Zhangzhou, 363000, China.

Environ Monit Assess ; 194(4): 284, 2022 Mar 16.

Article in En | MEDLINE | ID: mdl-35296936

Subject(s)

Air Pollutants; Air Pollution; Air Pollutants/analysis; Air Pollution/analysis; Environmental Monitoring; Particulate Matter/analysis; Rivers

Key words

PM2.5 drivers; Random Forest; Spatial autocorrelation; Spatial distribution; Yangtze River Delta

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Air Pollutants / Air Pollution Type of study: Clinical_trials / Prognostic_studies Language: En Journal: Environ Monit Assess Journal subject: SAUDE AMBIENTAL Year: 2022 Type: Article Affiliation country: China

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