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Author:

Chen, DS (Chen, DS.) (Scholars:陈东升) | Cheng, SY (Cheng, SY.) (Scholars:程水源) | Guo, XR (Guo, XR.) | Lei, T (Lei, T.) | Zhao, XY (Zhao, XY.) (Scholars:赵欣苑) | Chen, ZH (Chen, ZH.) | Ren, ZH (Ren, ZH.)

Indexed by:

CPCI-S

Abstract:

The Models-3 Community Multiscale Air Quality (CMAQ) modeling system was integrated with the meteorological simulation tools, including (a) the Fifth-Generation NCAR / Penn State Mesoscale Model (MM5), and (b) the Advanced Regional Prediction System (ARPS). The integrated system was then applied to Beijing region to study the PM 10 concentrations in Jan 2002. Most updated and detailed emission inventories along with large amount of original pollutant source data ensured considerable prediction accuracy. The nesting technique used in the coupled modeling system provided the inner-most simulation domain with reasonable boundary conditions. The simulation outputs were compared with ground level observations from local monitoring stations and lidar records reflecting variation of PM10 concentration with height. It was found that the modeling system offered reasonable prediction accuracy, with most observed key features being captured. Examination of the high episode of PM10 indicated that the pollution in Beijing was not only from local emissions but also from regional atmospheric transport. The wind field also played a key role in the dispersion of pollutants. This study represents a first attempt to combine the meteorological models of MM5 and ARPS With CMAQ to effectively account for small-scale meteorological characteristics and complex lower boundary conditions in a semi-basin region.

Keyword:

simulation MM5 atmosphere Models-3 ARPS CMAQ air quality

Author Community:

  • [ 1 ] Beijing Univ Technol, Coll Environm & Energy Engn, Beijing 10022, Peoples R China

Reprint Author's Address:

  • 陈东升

    [Chen, DS]Beijing Univ Technol, Coll Environm & Energy Engn, Beijing 10022, Peoples R China

Email:

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Source :

Environmental Informatics, Proceedings

Year: 2005

Page: 439-448

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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