An adaptive grid version of CMAQ for improving the resolution of plumes

Developmental Biology

Fernando Garcia–Menendez¹  Aika Yano¹  M. Talat Odman¹  Yongtao Hu¹ 

[1]School of Civil and Environmental Engineering, Georgia Institute of Technology,311 Ferst Drive, Atlanta, GA 30332-0512, USA$$

关键词: Adaptive mesh refinement;    Modeling of plumes;    Air quality;    Biomass burning;    Particulate matter;   

DOI  :  10.5094/APR.2010.031

学科分类：农业科学（综合）

来源: Dokuz Eylul Universitesi * Department of Environmental Engineering

【 摘 要 】

Atmospheric pollutant plumes are not well resolved in current air quality models due to limitations in grid resolution. Examples of these include power plant and biomass burning plumes. Adequate resolution of these plumes necessitates multiscale air quality modeling at much finer scales than currently employed and we believe that adaptive grids could be the best approach to accurate fine–scale modeling of air pollution dynamics and chemistry. An adaptive grid version of the CMAQ model with all necessary functions for tracking gaseous pollutants and particulate matter has been developed. The model incorporates a dynamic, solution–adaptive grid algorithm and a variable time step algorithm into CMAQ, while retaining the original functionality, concept of modularity, and grid topology.

The adaptive model was evaluated by comparing its performance to that of the standard, static grid CMAQ in simulating particulate matter concentrations from a biomass burning air pollution incident affecting a large urban area. The adaptive grid model significantly reduced numerical diffusion, produced better defined plumes, and exhibited closer agreement with monitoring site measurements. The adaptive grid also allows impacts at specified locations to be attributed to a specific pollutant source and provides insight into air pollution dynamics unattainable with a static grid model. Potential applications of adaptive grid modeling need not be limited to air quality simulation, but could be useful in meteorological and climate models as well.

【 授权许可】

Unknown   

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