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| Titel |
Air Quality Monitoring and Forecasting in China |
| VerfasserIn |
Bas Mijling, Ronald van der A, Pucai Wang |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250040714
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| Zusammenfassung |
| Within the ESA-MOST Dragon 2 Programme, the AMFIC project consists of an integrated system for monitoring and forecasting tropospheric pollutants over China. Satellite data, in situ measurements and chemical transport model results are used to generate consistent air quality information over China. The system includes a data archive of the recent years, near real time data, and air quality forecasts for several days ahead, which can be find on http://www.amfic.eu. Air pollutants covered are nitrogen dioxide, sulfur dioxide, formaldehyde, carbon monoxide, methane and aerosol.
The AMFIC system has been used to evaluate the effect of the air quality measures which were taken by the Chinese authorities related to the Olympic Games and Paralympics in Beijing. Industrial activities and traffic in and around the city were reduced drastically to improve air quality. To compensate for the atypical meteorological conditions during the Olympic events, tropospheric NO2 column observations from GOME-2 and OMI are interpreted against simulations from the CHIMERE regional chemistry transport model. When compared with the pre-Olympic concentration levels, we find a NO2 reduction of 60% over Beijing and significant reductions in surrounding areas. After the Olympic period, NO2 concentrations slowly return to their pre-Olympic level.
The satellite observations and model simulations of tropospheric NO2 column concentrations are also used to constrain NOx emissions over China by using data assimilation techniques. We will present the preliminary results of these efforts. The periodical update of the bottom-up emission inventory is expected to reveal emission trends and improve the air quality forecasts for China. |
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