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John S Evans

Publications and source records attributed to John S Evans.

5 recordsLinked to original sources

Use of expert judgment in exposure assessment: part 2. Calibration of expert judgments about personal exposures to benzene.

The recent movement of regulatory agencies toward probabilistic analyses of human health and environmental risks has focused greater attention on the quality of the estimates of variability and uncertainty that underlie them. Of particular concern is how uncertainty--a measure of what is not known--is characterized, as uncertainty can play an influential role in analyses of the need for regulatory controls or in estimates of the economic value of additional research. This paper reports the second phase of a study, conducted as an element of the National Human Exposure Assessment Survey (NHEXAS), to obtain and calibrate exposure assessment experts judgments about uncertainty in residential ambient, residential indoor, and personal air benzene concentrations experienced by the nonsmoking, nonoccupationally exposed population in U.S. EPA's Region V. Subjective judgments (i.e., the median, interquartile range, and 90% confidence interval) about the means and 90th percentiles of each of the benzene distributions were elicited from the seven experts participating in the study. The calibration or quality of the experts' judgments was assessed by comparing them to the actual measurements from the NHEXAS Region V study using graphical techniques, a quadratic scoring rule, and surprise and interquartile indices. The results from both quantitative scoring methods suggested that, considered collectively, the experts' judgments were relatively well calibrated although on balance, underconfident. The calibration of individual expert judgments appeared variable, highlighting potential pitfalls in reliance on individual experts. In a surprising finding, the experts' judgments about the 90th percentiles of the benzene distributions were better calibrated than their predictions about the means; the experts tended to be overconfident in their ability to predict the means. This paper is also one of the first calibration studies to demonstrate the importance of taking into account intraexpert correlation on the statistical significance of the findings. When the judgments were assumed to be independent, analysis of the surprise and interquartile indices found evidence of poor calibration (P<0.05). However, when the intraexpert correlation in the study was taken into account, these findings were no longer statistically significant. The analysis further found that the experts' judgments scored better than estimates of Region V benzene concentrations simply drawn from earlier studies of ambient, indoor and personal benzene levels in other U.S. cities. These results suggest the value of careful elicitation of expert judgments in characterizing exposures in probabilistic form. Additional calibration studies need to be undertaken to corroborate and extend these findings.

Air Pollution, Indoor↗

Policy uses of particulate exposure estimates.

This paper reviews the uses of particulate exposure estimates for science and policy. We propose a set of normative factors to guide the selection and application of various approaches for exposure assessment. For exposure estimates intended for use in support of the development or air pollution regulations or selection of control strategies, the proposed criteria include--compatibility with policy scope and scale, cost-effectiveness, characterization of uncertainty, political and institutional feasibility, and sensitivity to framing. For exposure assessment in support of epidemiological research, key criteria are-compatability with the specific hypothesis being tested, and compatibility with the temporal and spatial scale of analysis. The various major approaches for estimation of exposure--direct and indirect measurement, empirical and physical modeling--are catalogued and compared with these proposed criteria.

Air Pollutants↗

Exposure efficiency: an idea whose time has come?

Exposure efficiency, the fraction of material released from a source that is eventually inhaled or ingested, is arguably the simplest of all possible descriptions of the link between pollutant emissions and population exposures. This paper, prepared in late 1999 for the SGOMSEC Workshop, notes that several groups of researchers independently developed the concept of exposure efficiency in the late 1980s and early 1990s but argues that the potential importance of exposure efficiency in risk analysis and life cycle assessment has only recently been appreciated. The paper reviews the history of the concept; discusses and summarizes previous estimates of exposure efficiency for particulate matter and other air pollutants; presents new values for fine particulate matter emitted from power plants and mobile sources in the United States; and illustrates how preliminary estimates of exposure efficiency might be developed. The authors assert that in order for the concept of exposure efficiency to achieve its full potential exposure efficiency estimates for a wide variety of pollutants and sources must be developed and that both the results and methods must be made widely available and accessible to the community of risk assessors and life cycle analysts.

Air Pollutants↗

A regression-based approach for estimating primary and secondary particulate matter intake fractions.

One of the common challenges for life cycle impact assessment and risk assessment is the need to estimate the population exposures associated with emissions. The concept of intake fraction (a unitless term representing the fraction of material or its precursor released from a source that is eventually inhaled or ingested) can be used when limited site data are available or the number of sources to model is large. Although studies have estimated intake fractions for some pollutant-source combinations, there is a need to quickly and accurately estimate intake fractions for sources and settings not previously evaluated. It would be expected that limited source or site information could be used to yield intake fraction estimates with reasonable accuracy. To test this theory, we developed regression models to predict intake fractions previously estimated for primary fine particles (PM2.5) and secondary sulfate and nitrate particles from power plants and mobile sources in the United States. Our regression models were able to predict pollutant-specific intake fractions with R2 between 0.53 and 0.86 and equations that reflected expected relationships (e.g., intake fraction increased with population density, stack height influenced the intake fraction of primary but not secondary particles). Further analysis would be needed to generalize beyond this case study and construct models applicable across source categories and settings, but our analysis demonstrates that inclusion of a limited number of parameters can significantly reduce the uncertainty in population-average exposure estimates.

Air Pollutants↗