Comparative evaluation of population exposure modeling approaches for reactive and nonreactive air pollutants
S.S. Isukapalli1, J.E. Langstaff2, D.J. Lucken3, P.G. Georgopoulos1
1Environmental & Occupational Health Sciences Institute, Piscataway, NJ; 2USEPA Office of Air Quality Planning and Standards, Research Triangle Park, NC; 3USEPA Office of Research and Development, Research Triangle Park, NC
Computational models for estimating population inhalation exposures to various types of reactive and inert air pollutants typically utilize random "virtual individuals" defined so as to match the demographic characteristics of the population that is modeled, and provide distributions of exposures that incorporate estimates of uncertainty and variability. Currently there are very limited data for evaluating population exposure models. Therefore, comparative evaluation of different population exposure models offers a means for obtaining insight into model uncertainties as well as for identifying areas that need further research.
Two population-based inhalation exposure modeling systems are comparatively evaluated here: the APEX (Air Pollutants Exposure Model), and MENTOR-1A (Modeling ENvironment for TOtal Risk studies in a "One Atmosphere" [1A] setting). Both APEX and MENTOR-1A provide exposure estimates for the study population, defined by concentration and breathing rates for each individual exposure event at an activity event level and also at an hourly resolution. They use different formulations starting from the processes to calculate outdoor concentrations, human activity patterns, indoor sources, and intakes/uptakes of the pollutants. A case study is presented involving the modeling of exposures to the general population in the urban Philadelphia, PA region for the entire year 2001 with APEX and MENTOR-1A. The exposure analysis focuses on ozone, formaldehyde, and benzene, reflecting a range of properties spanning different reactivities and different natures of formation (primary versus secondary). Results from the two models operating under different assumptions at different stages of modeling are evaluated and major differences and their causes are discussed.
This work is funded in part by the USEPA (Cooperative Agreement CR-83162501) and the American Chemistry Council (ACC). Viewpoints expressed here are the responsibility of the authors and do not necessarily reflect views of the USEPA, the ACC, or their contractors.