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Activity Number: 33 - Statistical Methods in Public Health Research
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: International Chinese Statistical Association
Abstract #304214
Title: Path-Tracked Spatial-Temporal Prediction of PM2.5
Author(s): Lei Chen*
Companies: Peking University
Keywords: Transmission; Spatial-temporal; Air pollution; Meteorological influence

Air pollution becomes a severe issue around China recently. It is affected not only by the emission, but also by the meteorological conditions, especially the wind speed and direction. We provided a path-tracking formula that can predict the path of pollutant puffs which can reflect the transmission process of the pollution. We modeled the concentration of pollutant puffs with the generation, attenuation of pollutants and meteorological conditions during the transmission process. These transmitted pollutant puffs can be treated as samples from the pollutant field to be predicted and the concentration at any location can be predicted by interpolating by kriging method. Compared to the prediction by using observation of current hour, this model improved about 12.3% in prediction the concentration of next hour. This model also helps us understand the pollutant process and how meteorological variables work in the process. This model can also be used to interpolate the missing value.

Authors who are presenting talks have a * after their name.

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