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Analysis of Discriminating Factors in Human Activities That Affect Exposure

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Abstract: Accurately modeling exposure to particulate matter (PM) and other pollutants ultimately involves the utilization of human location-activity databases to assist in understanding the potential variability of microenvironmental exposures. This paper critically considers and statistically tests key factors thought to be important in explaining the choices people make in where they spend time. Three aggregate locations were analyzed: outdoors, indoors, and in-vehicles for two different sample groups. As part of an initial study, a year-long (longitudinal) sample of one individual was compared with a cross-sectional sample of 169 individuals from USEPA's Consolidated Human Activity Database (CHAD) similar to the longitudinal sample in terms of age, work status, education, and residential type. The sample groups were remarkably similar in the time spent per day in the tested locations, although there were differences in participation rates (percentage of days in a particular location). Time spent outdoors exhibits the most relative variability of any location tested, and in-vehicle time being the next. The factors found to be most important in explaining daily time usage in both sample groups are seasons, season/temperature combinations, precipitation levels, and day-type (work/non-work is the most distinct, but weekday/weekend is also significant). Season, season/temperature, and day-type are also important for explaining time spent indoors, however none of the variables tested are consistent in explaining in-vehicle time in either the cross-sectional or longitudinal samples. The design and results of this study were applied to an analysis of CHAD in its entirety, comprised of 22,968 person days of location-activity data from 12 individual human activity pattern studies. In addition to the above factors, study effects were considered along with a detailed analysis of the effect various attribute-based sample pools have in human exposure cohort development. There were significant differences between studies that can potentially introduce bias when considering time spent in specific locations and, when studies are considered inclusively to a sample pool, could potentially add error to exposure estimates.

Given these findings, we recommend that PM and other exposure modelers subdivide their population activity data into at a minimum temperature, precipitation, and day-type cohorts as these factors are important discriminating variables affecting where people spend their time. Temperature and precipitation levels are also important factors in modifying PM concentrations, and without considering meteorological influence on both human activities and concentrations would further contribute to erroneous exposure estimates. Furthermore, exposure modelers using CHAD also need to consider study selection carefully since not all of the individual studies in CHAD collected the same information.

This work has been funded by the United States Environmental Protection Agency. It has been subjected to Agency review and approved for publication.
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Citation:Graham, S. E., and T. R. Mccurdy. Analysis of Discriminating Factors in Human Activities That Affect Exposure. Presented at 2003 Carolinas Society of Environmental Toxicology and Chemistry Annual Meeting, Charleston, SC, April 2-4, 2003.
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Contact: Liz Hope - (919) 541-2785 or hope.elizabeth@epa.gov
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Division: Human Exposure & Atmospheric Sciences Division
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Branch: Exposure Modeling Research Branch
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Product Type: Abstrct/Oral
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Presented: 04/02/2003
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Related Entries:
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Bullet Item Human Exposure Activity Patterns
spacer Relationship Reason:   A Project of the Product
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Last Updated on Monday, October 22, 2007
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