Found 10066 publications. Showing page 294 of 403:
PM2.5 Retrieval Using Aerosol Optical Depth, Meteorological Variables, and Artificial Intelligence
Particulate matter (PM) is one of the major air pollutants that has adverse impacts on human health. The aim of this study is to present an alternative approach for retrieving fine PM (particles with an aerodynamic diameter less than 2.5 μm, PM2.5) using artificial intelligence. Ground-based instruments, including a hand-held Microtops II sun photometer (for aerosol optical depth), a PurpleAir sensor (for PM2.5), and Rotronic sensors (for temperature and relative humidity), are used for the machine learning algorithm training. The retrieved PM2.5 reveals an adequate performance with an error of 0.08 μg m−3 and a Pearson correlation coefficient of 0.84.
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Policy Applications of the EUROTRAC Results: The Application Project. Transport and Chemical Transformation of Pollutants in the Troposphere, 3373, vol. 1
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Pollutant deposits and air quality around the North Sea and the North-East Atlantic in 2005. NILU OR
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