Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations.

A sequential measurement method is demonstrated for quantifying the variability in exposure concentration during public transportation. This method was applied in Hong Kong by measuring PM2.5 and CO concentrations along a route connecting 13 transportation-related microenvironments within 3-4 h. The study design takes into account ventilation, proximity to local sources, area-wide air quality, and meteorological conditions. Portable instruments were compacted into a backpack to facilitate measurement under crowded transportation conditions and to quantify personal exposure by sampling at nose level. The route included stops next to three roadside monitors to enable comparison of fixed site and exposure concentrations. PM2.5 exposure concentrations were correlated with the roadside monitors, despite differences in averaging time, detection method, and sampling location. Although highly correlated in temporal trend, PM2.5 concentrations varied significantly among microenvironments, with mean concentration ratios versus roadside monitor ranging from 0.5 for MTR train to 1.3 for bus terminal. Measured inter-run variability provides insight regarding the sample size needed to discriminate between microenvironments with increased statistical significance. The study results illustrate the utility of sequential measurement of microenvironments and policy-relevant insights for exposure mitigation and management.

Comparison of sources of variability in school age children exposure to ambient PM2.5.

School age children are particularly susceptible to exposure to ambient fine particle (PM2.5). To provide insight into factors affecting variability in ambient PM2.5 exposure, distributions of daily PM2.5 exposures for school age children are estimated for four seasons in three climatic zones of the United States using a stochastic microenvironmental exposure model, based on ambient concentration, air exchange rate, penetration factor, deposition rate, census data, meteorological data, and time pattern data. Estimated daily individual exposure varies largely among seasons, regions, and individuals. The mean ratio of ambient exposure to ambient concentration (Ea/Ca) ranges from 0.46 to 0.61 among selected regions and seasons, resulting from differences in air exchange rate. The individual Ea/Ca varies by a factor of 2 to 3 over a 95% frequency range among simulated children, resulting from variability in children's time patterns. These patterns are similar among age groups, but vary with the day of the week and outdoor temperature. Variability in exposure is larger between individuals than between groups. The high end ratio of the Ea/Ca, at the 95th percentile of inter-individual variability, is 30% to 50% higher than the mean Ea/Ca ratio. Results can be used to intepret and adjust exposure errors in epidemiology and to assist in development of exposure mitigation strategies.

Assessment of the effect of population and diary sampling methods on estimation of school-age children exposure to fine particles.

Population and diary sampling methods are employed in exposure models to sample simulated individuals and their daily activity on each simulation day. Different sampling methods may lead to variations in estimated human exposure. In this study, two population sampling methods (stratified-random and random-random) and three diary sampling methods (random resampling, diversity and autocorrelation, and Markov-chain cluster [MCC]) are evaluated. Their impacts on estimated children's exposure to ambient fine particulate matter (PM2.5 ) are quantified via case studies for children in Wake County, NC for July 2002. The estimated mean daily average exposure is 12.9 µg/m(3) for simulated children using the stratified population sampling method, and 12.2 µg/m(3) using the random sampling method. These minor differences are caused by the random sampling among ages within census tracts. Among the three diary sampling methods, there are differences in the estimated number of individuals with multiple days of exposures exceeding a benchmark of concern of 25 µg/m(3) due to differences in how multiday longitudinal diaries are estimated. The MCC method is relatively more conservative. In case studies evaluated here, the MCC method led to 10% higher estimation of the number of individuals with repeated exposures exceeding the benchmark. The comparisons help to identify and contrast the capabilities of each method and to offer insight regarding implications of method choice. Exposure simulation results are robust to the two population sampling methods evaluated, and are sensitive to the choice of method for simulating longitudinal diaries, particularly when analyzing results for specific microenvironments or for exposures exceeding a benchmark of concern.