You are here:
Approaches to characterize inequities in air pollution exposures
Citation:
Baxter, L. Approaches to characterize inequities in air pollution exposures. 2015 ISEE, Sao Paulo, Brazil, Sao Paulo, BRAZIL, August 30 - September 03, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Certain populations bear a disproportionate burden of air pollutant exposures resulting in inequity of risk. This may be due to proximity to outdoor sources such as major roadways and industry or increased prevalence of indoor sources such as cigarette smoking or gas stoves. There may also be different activity patterns for these population such as air conditioning use and the opening of windows which will influence exposures to both outdoor- and indoor-generated pollutants. Central-site monitors are often sited for regulatory purposes, so they may not be optimal for obtaining representative exposures for at-risk groups. This presentation will describe the current techniques and approaches available to better characterize exposure of at-risk populations. Air quality models and GIS-based modelling approaches can provide greater spatial and temporal resolution in ambient concentrations. Air quality models generally incorporate data on source emissions, meteorology, and atmospheric fate and transport mechanisms to increase spatial and temporal resolution. GIS-based modeling approaches combine monitoring data with available information on spatially varying characteristics, such as proximity to known emissions sources, to predict spatial patterns in ambient concentrations. To better characterize personal exposures, exposure models account for multiple factors that affect the personal exposure of individuals from both indoor and outdoor sources. Specifically, these models estimate exposures for particular individuals or groups of individuals by incorporating information on human activity and behaviors as individuals move through space and time, in addition to demographic characteristics and characteristics of the home environment.In addition to describing the current approaches, this presentation will discuss the future exposure research necessary to understand within and between-population exposure differences and how this relates to the distribution of risk.
