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| Titel |
A new Dynamic Dust-emission rate (DDR) scheme base on Satellite remote sensing data for air quality model |
| VerfasserIn |
Yu Jia Tang, Ling Jun Li, Yi Ming Zhou, Da Wei Zhang, Wen Jun Yin, Meng Zhang, Bao Guo Xie, Nianliang Cheng |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250148010
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| Publikation (Nr.) |
 EGU/EGU2017-12235.pdf |
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| Zusammenfassung |
| Dust produced by wind erosion is a major source of atmospheric dust pollutions which have impacts on air quality, weather and climate. It is difficult to calculate dust concentration in the atmosphere with certainty unless the dust-emission rate can be estimated with accuracy. Hence, due to the unreliable estimation of dust-emission rate flux from ground surface, the dust forecast accuracy in air quality models is low. The main reason is that the parameter that describes the dust-emission rate in the regional air quality model is constant and cannot reflect the reality of surface dust-emission changes. A new scheme which uses the vegetation information from satellite remote sensing data and meteorological condition provided by meteorological forecast model is developed to estimate the actual dust-emission rete from the ground surface. The results shows that the new scheme can improve dust simulation and forecast performance significantly and reduce the root mean square error by 25%~68%.
The DDR scheme can be coupled with any current air quality model (e.g. WRF-Chem, CMAQ, CAMx) and produce more accurate dust forecast. |
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