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Air Quality Models: Architecture
In very recent memory, it was probably a true statement that AQMs required some type of high-performance computing resources (scientific workstations, supercomputers, etc.). With the advent of faster, less expensive chips and computer memory, many of the AQMs have been "ported", or re-written and re-compiled, to run on the newer Windows-based Pentium machines.
By way of example, we conducted a somewhat unscientific survey. From the Support Center for Regulatory Air Models (SCRAM) web page, we looked at the seven air quality regulatory models that are considered as being "preferred" by the Environmental Protection Agency. The table below shows these models, with a brief description, a checkmark if they can be run on a desktop PC (i.e., are "PC-executable"), and the type of source code the program was programmed in originally:
| Model Name |
Model Description |
PC executable? |
Source code language |
| BLP (Bouyant Line Plume ) |
a Gaussian plume dispersion model designed to handle unique modeling problems
associated with aluminum reduction plants, and other industrial sources
where plume rise and downwash effects from stationary line sources are important.
|
 |
FORTRAN |
| CALINE3 |
a steady-state Gaussian dispersion model designed to determine air pollution
concentrations at receptor locations downwind of "at-grade," "fill," "bridge,"
and "cut section" highways located in relatively uncomplicated terrain.
|
 |
FORTRAN |
| CDM2 (Climatological Dispersion Model) |
a climatological steady-state Gaussian plume model for determining long-term
(seasonal or annual) arithmetic average pollutant concentrations at any
ground-level receptor in an urban area. |
 |
FORTRAN |
| CTDMPLUS (Complex Terrain Dispersion Model Plus Algorithms for Unstable
Situations) |
a refined point source gaussian air quality model for use in all stability
conditions for complex terrain. The model contains, in its entirety, the
technology of CTDM for stable and neutral conditions. |
 |
FORTRAN |
| ISC3 (Industrial Source Complex Model) |
a steady-state Gaussian plume model which can be used to assess pollutant
concentrations from a wide variety of sources associated with an industrial
complex. This model can account for the following: settling and dry deposition
of particles; downwash; point, area, line, and volume sources; plume rise
as a function of downwind distance; separation of point sources; and limited
terrain adjustment. ISC3 operates in both long-term and short-term modes.
|
 |
FORTRAN |
| OCD (Offshore and Coastal Dispersion Model) |
a straight line Gaussian model developed to determine the impact of offshore
emissions from point, area or line sources on the air quality of coastal
regions. OCD incorporates overwater plume transport and dispersion as well
as changes that occur as the plume crosses the shoreline. Hourly meteorological
data are needed from both offshore and onshore locations. |
 |
FORTRAN |
| RAM (Gaussian-Plume Multiple Source Air Quality Algorithm) |
a steady-state Gaussian plume model for estimating concentrations of relatively
stable pollutants, for averaging times from an hour to a day, from point
and area sources in a rural or urban setting. Level terrain is assumed.
|
 |
FORTRAN |
| UAM-IV (Urban Airshed Model IV) |
an urban scale, three dimensional, grid type numerical simulation model.
The model incorporates a condensed photochemical kinetics mechanism for
urban atmospheres. UAM-IV is designed for computing ozone (O3) concentrations
under short-term, episodic conditions lasting one or two days resulting
from emissions of oxides of nitrogen (NOx), volatile organic compounds (VOC),
and carbon monoxide (CO). The model treats VOC emissions as their carbon-bond
surrogates. |
 |
FORTRAN |
While all of these codes are currently available as PC-executables, there is clearly a "price" to pay by doing so. The following table, extracted from a paper on regional air quality modeling by Khanh T. Tran and Fabrice Cuq, shows a benchmark comparision table for running the Urban Airshed Model (UAM) on various machines, beginning with a desktop PC and moving down to a high-performance computer:
Table 2. Execution Times of theUAM Test Cases
(24-Hour Runs; 54x26x4 UAM Grid)
| Computer |
UAM Test
CPU (min) |
System Features |
| 486/DX4-75 |
654 |
MS-DOS with 8 MB RAM |
| Intel Pentium 90 |
169 |
MS-DOS with 8 MB RAM |
| Intel Pentium 100 |
166 |
MS-DOS with 16 MB RAM |
| IBM RS 6000/355 |
105 |
AIX with 32 MB RAM |
| Sun SPARC 10/40 |
159 |
SunOS with 80 MB RAM |
| Sun SPARC 20/50 |
95 |
SunOS with 80 MB RAM |
| Sun SPARC 20/71 |
70 |
SunOS with 32 MB RAM |
| DEC 2100/Alpha 166 |
55 |
OSF with 64 MB RAM |
| DEC 3000/Alpha 175 |
44 |
OSF with 64 MB RAM |
| DEC 3000/Alpha 190 |
38 |
OSF with 256 MB RAM |
| SGI Power Onyx |
44 |
IRIX - 2 R8000 CPU 75 Mhz
128 MB RAM |
| The graph at the right (click to see full-sized) shows this data visually. It should be much more apparent from this bar graph that, while it is possible to run "larger" models such as the Urban Airshed Model on desktop platforms, that some serious consideration needs to be undertaken by the air quality modeler about the effective use of time and resources. |
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Given no or limited access to higher performance computing platforms such as a DEC Alpha or SGI Onyx machine, the decision is easy. If, however, these platforms are available, then the air quality modeler should look to use those platforms instead. Keep in mind that often the interfaces -- the tool tht the analyst uses to interact with the code -- may or may not be as "user-friendly" as interfaces that may have been developed for the desktop machine. These are all considerations to take into account when choosing an air quality model.
Confused? Have a question? If so, check out the Frequently Asked Questions (FAQ) page or send mail to the OS411 tutor (os411tutor@shodor.org) with your question!
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