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Biomedical subjects

John S Evans

Publications and source records attributed to John S Evans.

7 recordsLinked to original sources
PubMed2005

The influence of geographic location on population exposure to emissions from power plants throughout China.

This analysis seeks to evaluate the influence of emission source location on population exposure in China to fine particles and sulfur dioxide. We use the concept of intake fraction, defined as the fraction of material or its precursor released from a source that is eventually inhaled or ingested by a population. We select 29 power-plant sites throughout China and estimate annual average intake fractions at each site, using identical source characteristics to isolate the influence of geographic location. In addition, we develop regression models to interpret the intake fraction values and allow for extrapolation to other sites. To model the concentration increase due to emissions from selected power plants, we used a detailed long-range atmospheric dispersion model, CALPUFF. Primary fine particles have the highest average intake fraction (1 x 0(-5)), followed by sulfur dioxide (5 x 10(-6)), sulfate from sulfur dioxide (4 x 10(-6)), and nitrate from nitrogen oxides (4 x 10(-6)). For all pollutants, the intake fractions span approximately an order of magnitude across sites. In the regression analysis, the independent variables are meteorological proxies (such as climate region and precipitation) and population at various distances from the source. We find that population terms can explain a substantial percentage of variability in the intake fraction for all pollutants (R(2) between 0.86 and 0.95 across pollutants), with a significant modifying influence of meteorological regime. Near-source population is more important for primary coarse particles while population at medium to long distance is more important for primary fine particles and secondary particles. A significant portion of intake fraction (especially for secondary particles and primary fine particles) occurs beyond 500 km of the source, emphasizing the need for detailed long-range dispersion modeling. These findings demonstrate that intake fractions for power plants in China can be estimated with reasonable precision and summarized using simple regression models. The results should be useful for informing future decisions about power-plant locations and controls.

Air Pollutants↗
PubMed2003

Estimation of primary and secondary particulate matter intake fractions for power plants in Georgia.

Air pollution benefit-cost analyses depend on dispersion models to predict population exposures to pollutants, but it is difficult to determine the reasonableness of the model estimates. This is in part because validation with field measurements is not feasible for marginal concentration changes and because few models can capture the necessary spatial and temporal domains with adequate sophistication. In this study, we use the concept of an intake fraction (the fraction of a pollutant or its precursor emitted that is eventually inhaled) to provide insight about population exposures and model performance. We apply CALPUFF, a regional-scale dispersion model common in health benefits assessments, to seven power plants in northern Georgia, considering both direct emissions of fine particulate matter (PM2.5) and secondarily formed ammonium sulfate and ammonium nitrate particles over a domain within 500 km of Atlanta. We estimate emission-weighted average intake fractions of 6 x 10(-7) for primary PM2.5, 2 x 10(-7) for ammonium sulfate from SO2, and 6 x 10(-8) for ammonium nitrate from NOx, with no effect of SO2 on ammonium nitrate. To provide insight about model strengths and limitations, we compare our findings with those from a frequently applied source-receptor (S-R) matrix. Using S-R matrix over an identical domain, the corresponding intake fractions are 5 x 10(-7), 2 x 10(-7), 3 x 10(-8), and -2 x 10(-8), respectively, with the values approximately doubling if the domain is expanded to cover the continental United States. Evaluation of model assumptions and comparison of past intake fraction estimates using these two models illustrates the importance of assumptions about the relative concentrations of ammonia, sulfate, and nitrate, which significantly influences ammonium nitrate intake fractions. These findings provide a framework for improved understanding of the factors that influence population exposures to particulate matter.

Air Pollutants↗
PubMed2003

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↗
PubMed2002

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↗
PubMed2002

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↗
PubMed2002

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↗