Achieve scaleable dynamics and thermodynamics

with a fully compressible form of the governing

equations and a flexible coordinate system;

Use a unified governing set of equations that is

capable of dealing with air quality as well as

weather forecasting;

Maintain cell-based mass conservation by utilizing

proper state variables (i.e., density and entropy,

rather than pressure and temperature) and

representation of the governing equations in the

conservation form rather than in the advective

form; and

Implement general physical parameterizations that

are designed for a wide spectrum of spatial and

temporal scales.

It is anticipated that WRF will ultimately be coupled with

CMAQ in both the off-line and on-line modes as WRF

development matures.

4. EMISSION MODELING

Eulerian air quality models depend on preprocessed

emission data to describe primary air pollutant inputs in the

atmosphere and therefore they are called emission-based

models (EBMs). As such, emission modeling is one of the

critical components of the Models-3 CMAQ system.

Initially, CMAQ modeling depended on the Models-3

Emission Processing and Projection System (MEPPS)

(Benjey and Moghari [40], Benjey et al. [41]). More

recently, EPA replaced MEPPS with the Sparse Matrix

Operator Kernel Emissions (SMOKE) modeling system

[http://www.emc.mcnc.org/products/smoke/] for the

preparation of area, mobile, point, and biogenic emission

data (Houyoux and Vukovich [25]). SMOKE provides

gridded, temporalized (usually hourly), and speciated

emission data. SMOKE not only deals with individual

chemical species but also accommodates lumped (grouped)

species consistent with the gas phase chemical mechanisms

contained in the CMAQ model. The matrix-based internal

data structure of SMOKE allows rapid processing of

emissions factor applications with simple sparse matrix

 

 

 

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