those options. Exposure modeling is a complex process that depends on many assumptions about the future, including pollution emissions reductions resulting from the proposed regulation; changes in emissions due to factors other than the proposed regulation; meteorological conditions; the physical and chemical processes in the atmosphere affecting pollution dispersion, transformations, and deposition; and the nature and degree of pollutant contact with future human populations. As in all other stages of the benefits analysis, the assumptions and methods used in the exposure assessment should be well-justified and clearly described, with careful attention paid to assessing and communicating key sources of uncertainty.
EPA’s exposure assessment methods have evolved considerably over time, as is evident in the health benefits analyses reviewed by the committee. This evolution is due to continued improvements in modeling capabilities and to a marked increase in available air-monitoring data for many pollutants. Because the most recent EPA analysis reviewed by the committee (the benefits analysis for the heavy-duty (HD) engine and diesel-fuel rule) uses current data and exposure assessment methods, it serves as an illustrative example throughout this exposure assessment discussion.
The committee considers that the exposure assessment methods used in the analysis for the HD engine and diesel-fuel rule represent an appropriate and reasonably thorough application of available data and models. Although limitations, as noted in following sections, exist, they are primarily due to limitations of available scientific knowledge and, ultimately, the limited time and staff resources available for analysis rather than flawed analytical methods.
Exposure to air pollution has been defined as the intersection in time and space of a concentration of pollution in the air and the presence of a human being (NRC 1991; Ott 1995). For benefits analyses, exposure is typically assessed at the population level by geographically linking estimates of outdoor pollution concentrations with projected population numbers; these together represent the necessary input to population concentration-response functions for calculating health impacts. The use of ambient air concentrations to represent population exposures is justifiable when the health findings underlying the benefits analysis are similarly based on ambient concentration data and when the outdoor concentrations are correlated with personal exposures, as is the case for particulate matter (PM).