Eulerian air quality models have a lower limit for grid spacing constrained by parameterization validity.
the verdict
INSUFFICIENT LEANING
refutedsupported
the weight of evidence
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The evidence partially discusses how Eulerian air quality models face limitations with grid resolution and sub-grid scale processes due to assumptions of instantaneous mixing, but does not fully establish that parameterization validity acts as a hard lower limit for grid spacing.
Abstract Traditional Eulerian air quality models are unable to accurately simulate sub-grid scale processes, such as the near-source transport and chemistry of point source plumes, because they assume instantaneous mixing of the emitted pollutants within the grid cell containing the release, and neglect the turbulent segregation effects that limit the near-source mixing of emitted pollutants with the background atmosphere (e.g., Kramm and Meixner, 2000 ). Observations by Dlugi et al. (2010) show that the segregation of chemically reactive species can slow effective second-order reaction rates by as much as 15%, due to inhomogeneous mixing of the reactants. This limitation of traditional grid models applies to both “off-line” models, in which externally derived meteorology is used to drive the chemistry model, and newer “on-line” models, such as the Weather Research and Forecasting model with Chemistry (WRF/Chem), that simulate the emissions, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. While a number of approaches have been used in the past to address this limitation, the approach that has been most effectively used in operational models is the plume-in-grid (PinG) approach, in which a reactive plume model is embedded within the grid model to resolve sub-grid scale plumes. This paper describes the implementation of such a PinG treatment in WRF/Chem, based on a similar extension to the U.S. EPA Community Multi-
Evaluation of CMAQ Applications at Neighborhood Scales | US EPA
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Evaluation of CMAQ Applications at Neighborhood Scales
Introduction
Related CMAQ Evaluation Links
Model Evaluation Framework
Incremental Evaluation of New CMAQ Versions
Improving PM 2.5 Chemistry in CMAQ
Air Quality Model Evaluation International Initiative (AQMEII)
Dynamic Evaluation and Trend Analysis
Eulerian air quality models, such as CMAQ, discretize large simulation domains into smaller sized grid cells in order to better represent spatial heterogeneities. In theory, smaller-sized grid cells provide a truer representation of fine-scale processes and near-field impacts. While utilizing larger grid cells has the advantage of minimizing computation resources, it does have several disadvantages.
Since Eulerian air quality models instantly dilute point emissions across the entire volume of the grid cell, decisions on grid resolution should be made with consideration of the spatial scale of the air quality problem, meteorology, and emissions being modeled while also recognizing the increased computation resources required as grid cell size is decreased. The smaller the dimensions of the grid cells used, the more representative the model may be of the actual point source emissions. Additionally, meteorological fields (e.g. wind and temperature) are also likely to be better represented with smaller grid cells, particularly in areas with diverse and complex geography (e.g. coastal and mountainous regions).
Examples of Fine-Scale CMAQ Applications:
2011 Baltimore-Washington D.C. DISCOVER-AQ Campaign
2013 San Joaquin Valley (SJV) California DISCOVER-AQ Campaign
2014 Colorado Front Range DISCOVER-AQ/FRAPPE Campaig
Everything we examined (2)
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