A population exposure model for particulate matter: case study results for PM(2.5) in Philadelphia, PA

A population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied in a case study of daily PM(2.5) exposures for the population living in Philadelphia, PA. SHEDS-PM is a probabilistic model that estimates the population distribution of total PM exposures by randomly sampling from various input distributions. A mass balance equation is used to calculate indoor PM concentrations for the residential microenvironment from ambient outdoor PM concentrations and physical factor data (e.g., air exchange, penetration, deposition), as well as emission strengths for indoor PM sources (e.g., smoking, cooking). PM concentrations in nonresidential microenvironments are calculated using equations developed from regression analysis of available indoor and outdoor measurement data for vehicles, offices, schools, stores, and restaurants/bars. Additional model inputs include demographic data for the population being modeled and human activity pattern data from EPA's Consolidated Human Activity Database (CHAD). Model outputs include distributions of daily total PM exposures in various microenvironments (indoors, in vehicles, outdoors), and the contribution from PM of ambient origin to daily total PM exposures in these microenvironments. SHEDS-PM has been applied to the population of Philadelphia using spatially and temporally interpolated ambient PM(2.5) measurements from 1992-1993 and 1990 US Census data for each census tract in Philadelphia. The resulting distributions showed substantial variability in daily total PM(2.5) exposures for the population of Philadelphia (median=20 microg/m(3); 90th percentile=59 microg/m(3)). Variability in human activities, and the presence of indoor-residential sources in particular, contributed to the observed variability in total PM(2.5) exposures. The uncertainty in the estimated population distribution for total PM(2.5) exposures was highest at the upper end of the distribution and revealed the importance of including estimates of input uncertainty in population exposure models. The distributions of daily microenvironmental PM(2.5) exposures (exposures due to time spent in various microenvironments) indicated that indoor-residential PM(2.5) exposures (median=13 microg/m(3)) had the greatest influence on total PM(2.5) exposures compared to the other microenvironments. The distribution of daily exposures to PM(2.5) of ambient origin was less variable across the population than the distribution of daily total PM(2.5) exposures (median=7 microg/m(3); 90th percentile=18 microg/m(3)) and similar to the distribution of ambient outdoor PM(2.5) concentrations. This result suggests that human activity patterns did not have as strong an influence on ambient PM(2.5) exposures as was observed for exposure to other PM(2.5) sources. For most of the simulated population, exposure to PM(2.5) of ambient origin contributed a significant percent of the daily total PM(2.5) exposures (median=37.5%), especially for the segment of the population without exposure to environmental tobacco smoke in the residence (median=46.4%). Development of the SHEDS-PM model using the Philadelphia PM(2.5) case study also provided useful insights into the limitations of currently available data for use in population exposure models. In addition, data needs for improving inputs to the SHEDS-PM model, reducing uncertainty and further refinement of the model structure, were identified.

The influence of human activity patterns on personal PM exposure: a comparative analysis of filter-based and continuous particle measurements

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM2.5 or PM10 mass measurements [using Personal Environmental Monitors (PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to approximately 10 microm. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM2.5 or PM10 mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working. The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM2.5 results for the Baltimore participants and within approximately 20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelometer did not agree as well with the PM10 mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3-2 microm). Approximately one-half (54 +/- 31%; mean +/- standard deviation from both studies) of the average daily PM2.5 exposure occurred inside residences, where the participants spent an average of 83 +/- 10% of their time. These data also showed that a significant portion of PM2.5 exposure occurred in locations where participants spent only 4-13% of their time.

The challenge of assessing children's residential exposure to pesticides

In implementing the Food Quality Protection Act (FQPA) the U.S. Environmental Protection Agency (USEPA) has adopted a policy that the exposure factors and models used to assess and predict exposure to pesticides should generally be conservative. Some elements of exposure assessments for FQPA are screening level--they are both uncertain and conservative. If more realistic assessments are to be conducted, then research is required to reduce uncertainty associated with the factors and models used in the exposure assessments. To develop the strategy for conducting this research, critical exposure pathways and factors were identified, and the quality and quantity of data associated with default assumptions for exposure factors were evaluated. Then, based on our current understanding of the pathways that are potentially most important and most uncertain, significant research requirements were identified and prioritized to improve the data available and assumptions used to assess children's aggregate exposure to pesticides. Based on the results of these efforts, four priority research areas were identified: (1) pesticide use patterns in microenvironments where children spend time, (2) temporal and spatial distribution of pesticides following application in a residential setting, (3) dermal and nondietary ingestion exposure assessment methods and exposure factors, (4) dietary exposure assessment methods and exposure factors for infants and young children. The National Exposure Research Laboratory (NERL) research strategy in support of FQPA is designed to address these priority research needs.

Use of a continuous nephelometer to measure personal exposure to particles during the U.S. Environmental Protection Agency Baltimore and Fresno Panel studies

In population exposure studies, personal exposure to PM is typically measured as a 12- to 24-hr integrated mass concentration. To better understand short-term variation in personal PM exposure, continuous (1-min averaging time) nephelometers were worn by 15 participants as part of two U.S. Environmental Protection Agency (EPA) longitudinal PM exposure studies conducted in Baltimore County, MD, and Fresno, CA. Participants also wore inertial impactor samplers (24-hr integrated filter samples) and recorded their daily activities in 15-min intervals. In Baltimore, the nephelometers correlated well (R2 = 0.66) with the PM2.5 impactors. Time-series plots of personal nephelometer data showed each participant's PM exposure to consist of a series of peaks of relatively short duration. Activities corresponding to a significant instrument response included cooking, outdoor activities, transportation, laundry, cleaning, shopping, gardening, moving between microenvironments, and removing/putting on the instrument. On average, 63-66% of the daily PM exposure occurred indoors at home (about 2/3 of which occurred during waking hours), primarily due to the large amount of time spent in that location (an average of 72-77%). Although not a reference method for measuring mass concentration, the nephelometer did help identify PM sources and the relative contribution of those sources to an individual's personal exposure.

A modeling framework for estimating children's residential exposure and dose to chlorpyrifos via dermal residue contact and nondietary ingestion

To help address the Food Quality Protection Act of 1996, a physically based probabilistic model has been developed to quantify and analyze dermal and nondietary ingestion exposure and dose to pesticides. The Residential Stochastic Human Exposure and Dose Simulation Model for Pesticides (Residential-SHEDS) simulates the exposures and doses of children contacting residues on surfaces in treated residences and on turf in treated residential yards. The simulations combine sequential time-location-activity information from children's diaries with microlevel videotaped activity data, probability distributions of measured surface residues and exposure factors, and pharmacokinetic rate constants. Model outputs include individual profiles and population statistics for daily dermal loading, mass in the blood compartment, ingested residue via nondietary objects, and mass of eliminated metabolite, as well as contributions from various routes, pathways, and media. To illustrate the capabilities of the model framework, we applied Residential-SHEDS to estimate children's residential exposure and dose to chlorpyrifos for 12 exposure scenarios: 2 age groups (0-4 and 5-9 years); 2 indoor pesticide application methods (broadcast and crack and crevice); and 3 postindoor application time periods (< 1, 1-7, and 8-30 days). Independent residential turf applications (liquid or granular) were included in each of these scenarios. Despite the current data limitations and model assumptions, the case study predicts exposure and dose estimates that compare well to measurements in the published literature, and provides insights to the relative importance of exposure scenarios and pathways.