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. graphic of checkmark 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. graphic of checkmark 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. graphic of checkmark 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. graphic of checkmark 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. graphic of checkmark 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. graphic of checkmark 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.
graphic of checkmark
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.
graphic of checkmark
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. Graphic of benchmark

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.
Quick Quiz: For the UAM, what is the speedup between an IBM 486 and an SGI Power Onyx?
2 times
5 times
10 times
almost 15 times


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