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- W2267956608 abstract "Abstract For over 20 years, the Potential Source Contribution Function (PSCF) has been used by the aerosol research community to identify areas around an air-quality receptor location that are associated with high levels of pollutant emissions. PSCF uses particle back trajectories associated with multiple times as well as measured levels of a pollutant at each time, linking high-measurement days with specific back trajectories. For a given rectangular area ( s ) on a map, the probability p ( s ) that the area contains an important source of the pollutant of interest is estimated with p ˆ s = X s / n s , where n ( s ) is the number of back trajectories that trace back through that area and X ( s ) is the number of those back trajectories that are associated with a high day for the pollutant. Results are generally illustrated with a PSCF plot in which p ( s ) is plotted at each area (or pixel) on the map. However, the PSCF exhibits high pixelwise volatility and strong spatial discontinuity, particularly for high resolutions. We propose a modified potential source map that exploits both prior knowledge about p ( s ) and a filtered kriging approach that accounts the heterogeneous measurement error variances. Results are illustrated using air quality data from the EPA St. Louis–Midwest Supersite." @default.
- W2267956608 created "2016-06-24" @default.
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- W2267956608 date "2016-04-01" @default.
- W2267956608 modified "2023-09-27" @default.
- W2267956608 title "Optimally smoothed maps of pollution source potential via particle back-trajectories and filtered kriging" @default.
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- W2267956608 doi "https://doi.org/10.1016/j.chemolab.2016.02.002" @default.
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