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A method to predict air pollution based on wrf-chem model and statistical model

IP.com Disclosure Number: IPCOM000242026D
Publication Date: 2015-Jun-15
Document File: 2 page(s) / 68K

Publishing Venue

The IP.com Prior Art Database

Abstract

The Weather Research and Forecasting (WRF) model is a next generation meteorological model being developed collaboratively among several agencies. WRF-Chem is a version of WRF that also simultaneously simulates the emission, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. But for China, the pollution prediction accuracy is low, only 30%. As a result, we proposed a method that statistics and analyze pollution index data to find time and region variation tendency. Then association analysis of meteorological factors and geographic factors is used to get the relationship between pollution index and meteorological factors or geographic information. Finally, the method will genetate an air pollution predict model which take two aspects (wrf-chem can predict air pollution based on aerosol, the statistical model can predict air pollution based on weather factors, geography factors) into consideration.

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A method to predict air pollution based on wrf-chem model and statistical model
1In China, air pollution is serious, greatly impact on air quality, human health.
2
According to monitoring data to judge the city's air quality, predict the air pollution in the next few days, to provide reference for people's outdoor activities and provide suggestions for air quality control.
3
Pollution prediction accuracy is low.

Statistics and analysis pollution index time variation tendency

 collect history monitoring data, statistics and analyze the pollution index variation tendency in a day, a month, a quarter or a year
Statistics and analysis pollution index region variation tendency
collect history monitoring data, statistics and analyze the pollution index variation tendency in different monitoring regions
Establish the weather statistical model
the pollution index of time variation tendency as the dependent variable, meteorological factors (wind, temperature, humidity, pressure, etc.) as independent variable to get the relationship between pollution index and meteorological factors
Establish the geography statistical model
the pollution index of region variation tendency as the dependent variable, geographic information (Map data, population data, traffic conditions, etc.) as independent variable to get the relationship between pollution index and geographic information
Generate comprehensive statistical model
Combined with the influencing factors of geography and weather, th...