A Bayesian Downscaler Model to Estimate Daily PM2.5 Levels in the Conterminous US

There has been growing interest in extending the coverage of ground particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5) monitoring networks based on satellite remote sensing data. With broad spatial and temporal coverage, a satellite-based monitoring network has a strong potential to compl...

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Veröffentlicht in:	International journal of environmental research and public health 2018-09, Vol.15 (9), p.1999
Hauptverfasser:	Wang, Yikai, Hu, Xuefei, Chang, Howard, Waller, Lance, Belle, Jessica, Liu, Yang
Format:	Artikel
Sprache:	eng
Schlagworte:	Air pollution Air quality Air quality assessments Artificial intelligence Bayesian analysis Calibration Data processing Land use Mathematical models Modelling Neural networks Optical analysis Outdoor air quality Particulate matter Public health Remote monitoring Remote sensing Satellites Spatial data Studies Trends
Online-Zugang:	Volltext
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