Assessing the Spatiotemporal Characteristics, Factor Importance, and Health Impacts of Air Pollution in Seoul by Integrating Machine Learning into Land-Use Regression Modeling at High Spatiotemporal Resolutions

Previous studies have characterized spatial patterns of air pollution with land-use regression (LUR) models. However, the spatiotemporal characteristics of air pollution, the contribution of various factors to them, and the resultant health impacts have yet to be evaluated comprehensively. This stud...

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Veröffentlicht in:	Environmental science & technology 2023-01, Vol.57 (3), p.1225-1236
Hauptverfasser:	Li, Yue, Hong, Tageui, Gu, Yefu, Li, Zhiyuan, Huang, Tao, Lee, Harry Fung, Heo, Yeonsook, Yim, Steve H. L.
Format:	Artikel
Sprache:	eng
Schlagworte:	Air pollution Air quality Algorithms Anthropogenic Impacts on the Atmosphere Atmospheric models Cardiovascular diseases Diurnal Epidemiology Land pollution Land use Learning algorithms Machine learning Nitrogen dioxide Outdoor air quality Particulate matter Prediction models Quality management Regression analysis Spatial discrimination Spatial resolution
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