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Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system
Citation:
Foroutan, H., Jeff Young, S. Napelenok, L. Ran, W. Appel, R. Gilliam, AND Jon Pleim. Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system. Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, 9(1):585-608, (2017).
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of this scheme, however, is the incorporation of a newly developed dynamic relation for the surface roughness length relevant to small-scale dust generation processes. Through this implementation, the effect of nonerodible elements on the local flow acceleration, drag partitioning, and surface coverage protection is modeled in a physically based and consistent manner. Careful attention is paid in integrating the new windblown dust treatment in the CMAQ model to ensure that the required input parameters are correctly configured. To test the performance of the new dust module in CMAQ, the entire year 2011 is simulated for the continental United States, with particular emphasis on the southwestern United States (SWUS) where windblown dust concentrations are relatively large. Overall, the model shows good performance with the daily mean bias of soil concentrations fluctuating in the range of ±1 µg m−3 for the entire year. Springtime soil concentrations are in quite good agreement (normalized mean bias of 8.3%) with observations, while moderate to high underestimation of soil concentration is seen in the summertime. The latter is attributed to the issue of representing the convective dust storms in summertime. Evaluations against observations for seven elevated dust events in the SWUS indicate that the new windblown dust treatment is capable of capturing spatial and temporal characteristics of dust outbreaks.
