2.1 Evolution of the Eulerian Modeling Paradigm

To understand the community modeling paradigm the

CMAQ system promotes, it is important to have some

historical perspective of Eulerian air quality modeling

systems. Eulerian air quality modeling started in the early

1970s from the extension of the photochemical box model

and trace species dispersion model. To model urban air

quality, meteorological inputs were prepared using

diagnostic tools that attempt minimization of the threedimensional

divergence in the flow to avoid mass

consistency problems. The chemistry mechanisms used

were mostly intended to simulate daytime urban ozone

evolution. Urban Airshed Model (UAM) (SAI [4]) and

Caltech Air Quality Model (CIT) (McRae et al. [5]) were

two early urban-scale photochemical grid models.

Throughout the 1980s, several other similar modeling


systems were developed to study regional air quality issues.

Examples include the Regional Oxidant Model (ROM)

(Lamb [6]) for regional ozone study and the Sulfur

Transport and Emissions Model (STEM/STEM II)

(Carmichael et al. [7]) for regional acid deposition study.

Earlier versions of the Urban-Regional Model (URM)

(Kumar et al. [8]) and Comprehensive Air quality Model

with Extensions (CAMx) (Environ [9]) followed the same

approach although more recent versions utilized different

methods for meteorological data linkage. One of the

contributions of the Regional Acid Deposition Model

(RADM) system (Chang et al. [10]) was that it provided a

more succinct marriage between the meteorological and air

quality models. RADM was a well-utilized model, if not the

first public model implemented in such a way, that forced an

AQM to follow the meteorological model's grid and

dynamic structure. With the hydrostatic Mesoscale Model

Version 4 (MM4) (Anthes and Warner [11]) linked to

RADM, there was no serious dynamic representation

problem because the diagnostic equation derived from the

mass continuity equation was used to represent the vertical

motion (omega equation). However, with the advent of the

nonhydrostatic Fifth Generation Penn State University/

National Center for Atmospheric Research Mesoscale

Model (MM5) system (Grell et al. [12]), a higher-level

consistency between the meteorological and air quality

model was needed. The SARMAP Air Quality Model

(SAQM) (Chang et al. [13]) was developed from RADM

because the RADM formulation diverged from the MM5



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