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AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES
Citation:
Ching, J.K S. AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES. Presented at 11th Joint Conference on the Applications of Air Pollution Meteorology with the AWMA, Long Beach, CA, January 9-14, 2000.
Impact/Purpose:
The objectives of this task are to continuously develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, which is the science implementation within the Models-3 system framework for air quality simulation. CMAQ is a multiscale and multi-pollutant chemistry-transport model (CTM) that includes the necessary critical science process modules for atmospheric transport, deposition, cloud mixing, emissions, gas- and aqueous-phase chemical transformation processes, and aerosol dynamics and chemistry. It relies on Models-3 I/O API to support machine independent data access and maintains simple interfaces among science processor modules to provide a high-level of modularity.
Description:
The current interest in fine particles and toxics pollutants provide an impetus for extending air quality modeling capability towards improving exposure modeling and assessments. Human exposure models require information on concentration derived from interpolation of observations taken from monitoring networks. Causal mechanisms for adverse health from partiuclate matter and other air pollutants are numerous, but not well understood; however it provides much of the rationale for the nation's Pmresearch portfolio (NRC 98, 99). The NRC listed 10 causal hypotheses, each relating to some physical aspect or speciation of PM, and/or toxic pollutant species. The distribution of concentration fields for different PM causal pollutants will be highly complex at neighborhood scales. However, the number of locations of samplers of typical networks in urban areas is generally sparse; also, due to the sheer myriad of PM and toxic substances, temporal sampling of physical parameters of PM, speciated PM and toxic pollutants are limited and varied varying from sub-hourly to daily or weekly samples, and/or are surmised as surrogates of the available measurements. Thus, clearly, the observed temporal and spatial concentration fields are poorly, or inadequately resolved for driving exposure models and conducting health risk assessments. Currently the EPA emissions based modeling systems. Models-3 Community Multiscale Air Quality Modeling System (CMAQ) (Byun and Ching, 1999) is capable of modeling PM 2.5 and PM-10 at horizontal resolutions of ~36km for regional to 4 km for urban scale predictions. Urban areas are sources of large amounts of pollutants that contribute to significant and inherently subgrid spatial variability of the concentration fields and to subsequent exposures. Stationary monitors will be unable to characterize this variability. Current Eulerian-based air quality models' spatial resolution is coarse and cannot resolve the fine scale details.