Source-to-dose analysis of population exposures to PM. Case study: City of Philadelphia
V.M. Vyas, Q. Sun, A. Chandrasekar, S.W. Wang, P. Shade, P.G. Georgopoulos
(EOHSI, UMDNJ - R.W. Johnson Medical School and Rutgers University);
J. Burke, J. Xue, H. Ozkaynak (US EPA - NERL)
This work is an application of a computational framework that links together models and databases developed by US EPA NERL and by EOHSI; it is implemented within the Modeling Environment for Total Risk studies (MENTOR). The objective is to obtain a comprehensive and internally consistent source-to-dose population analysis for enhancing the understanding of exposures and associated health risk from fine airborne particulate matter (PM). The present study considers PM exposures in the City of Philadelphia, focusing on a pollution episode that occurred from 11 July to 25 July, 1999. The analysis presented here covers the entire sequence of modeling steps from atmospheric and indoor emissions of primary particles and gaseous precursors to estimation of inhaled dose through lung deposition. It provides a prototype assessment of source-to-dose PM dynamics for an urban population.
The outdoor source term was characterized using atmospheric emissions data from the USEPA National Emissions Trends (NET) inventory. The emissions were processed through the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System, for input to the USEPA Community Multiscale Air Quality (CMAQ) model. Meteorological inputs for CMAQ were prepared using the National Center for Atmospheric Research (NCAR) MM5 Version 3 model. MM5 utilized as inputs surface and upper-atmosphere data archived at NCAR. MM5 and CMAQ runs were performed for the Eastern USA, for nested grids with higher resolution over the Philadelphia region.
In order to link the modeling estimates of outdoor concentrations to population exposure models, the CMAQ results were used to calculate localized ambient PM values for the 367 census tracts of the City of Philadelphia, using the MENTOR module for Spatiotemporal Random Field (STRF) interpolation. The STRF method combines spatial and temporal information to provide more accurate estimates of interpolated concentrations than those resulting from purely spatial or purely temporal methods, thus reducing uncertainty associated with the estimates.
The localized outdoor concentration estimates were used as input to the USEPA-NERL PM-SHEDS (Stochastic Human Exposure and Dose Simulation) model. PM-SHEDS estimates total exposures of selected subpopulations to indoor and outdoor particulate matter. The model incorporates demographic characteristics of the population with outdoor concentration distributions, outdoor-indoor ventilation rates, time-activity diaries, and indoor concentration distributions. It accounts for measurement uncertainty as well as natural variability in input parameters, and it provides as output distributions of exposures attributable to different sources.
Finally, dose estimates were obtained by utilizing the output of PM-SHEDS in the population inhalation dosimetry module of MENTOR. This inhalation model uses dosimetry equations that account for anatomic, metabolic, and physical variability, and provides integrated doses for different regions of the lung; its formulation incorporates parameterizations derived from information sources that include the International Commission on Radiological Protection (ICRP) Publication 66 and the Los Alamos National Laboratory's HUMTRN model.
Disclaimer: This abstract has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.