Air quality (AQ) simulation models for PM 2.5 (by mass, constituent speciation, as well as size distribution and number) and for many individual species and classes of air toxics pollutants provide a basis for implementation of National Ambient Air Quality Standards (NAAQS) and a tool for performing risk based assessments and developing environmental management strategies. These (and other) air pollutants exhibit different degrees of spatial and temporal variability especially in urban areas and in different geographical-climatic regimes. In this study, we explore the specific role of Models-/Community Multi-scale Air Quality (CMAQ) modeling system to drive human exposure models at neighborhood scales. Refinements needed to allow CMAQ predictions of the concentration fields to 1.3 km grid resolution require incorporating urban scale building data and land surface information and the parameterizations for urban building morphologies and land use patterns into its meteorological processor.

This paper will describe the parametric formulations that allow the incorporating of urban building and vegetation data into the meteorological processor for modeling the momentum drag, turbulence, and surface energy budgets at grid resolution of the order of 1 km. We have chosen to model Houston TX to support studies and air quality assessments of ozone, PM and air toxics. Houston exhibits a varied distribution of land uses and building morphological structures; thus, the transport and dispersion in these various land uses will be strongly affected by these morphological structures, especially in the surface boundary layers. Consequently, the predicted air quality will be influenced by these refinements. Results will be presented and discussed to show the sensitivity of the introduction of these modeling refinements.