Impact of Emission Reductions on Exposures and Exposure Distributions: Application of a Geographic Exposure ModelEPA Grant Number: R833624
Title: Impact of Emission Reductions on Exposures and Exposure Distributions: Application of a Geographic Exposure Model
Investigators: Marshall, Julian D. , Ramachandran, Gurumurthy
Institution: University of Minnesota School of Public Health
EPA Project Officer: Nolt-Helms, Cynthia
Project Period: September 1, 2007 through October 31, 2010 (Extended to February 29, 2012)
Project Amount: $459,556
RFA: Development of Environmental Health Outcome Indicators (2006) RFA Text | Recipients Lists
Research Category: Health Effects , Health
Our objective is to quantify source-to-receptor relationships using existing data and models, thereby elucidating emission reductions strategies that target emission sources having the greatest impact on exposures and on environmental justice. We hypothesize that exposure impacts of a given emission reduction strategy vary significantly among (1) source categories, (2) locations within an urban area, and (3) times-of-day.
Our research approach employs a recently developed GIS exposure model for the South Coast Air Basin, California, that accounts for (1) individuals’ daily travel patterns for activities such as work and shopping; (2) spatially- and temporally-explicit modeled ambient concentrations for important air pollutants, including diesel particulate matter (DPM), ozone, benzene, and nitrogen oxides; and, (3) differences between ambient concentrations and exposure concentrations for microenvironments such as in-vehicles and in residences. Using this extant model and data framework, we will employ an existing model-sensitivity routine to systematically explore emission reduction for specific locations and specific times, and record the impact on (1) population-average exposures, and (2) environmental justice metrics, such as exposure inequity among racial and economic subpopulations.
Anticipated results include the following. (1) We will estimate intake fraction (i.e., the fraction of emissions that are inhaled) for major source categories, over time, and by spatial location. Higher intake fraction indicates a greater exposure reduction per emission reduction. (2) We will generate a list of locations, times, and sources that maximally (and also minimally) impact exposures and exposure distributions for the general population and specific racial and economic sub-populations. Such information offers a robust risk-focused approach to prioritizing among emission reduction strategies, and to addressing environmental justice issues. As an additional validation step, the strategies identified using this procedure will be presented to policy planners for their feedback. (3) We will generate a set of methods and exposure indicators that could usefully be applied to other urban areas.