Environmental Health Criteria 214

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HUMAN EXPOSURE ASSESSMENT Berkeley, Ozone 168 college freshmen (aged Test-retest reliabi California, 17-21) raised in California; study to recall lif USA convenience sample; residential history long-term ozone exposure Athens; PM 25 , CO, 450 adults (aged 25-55) Mostly 1997; 48-h pe Basel; VOC, NO 2 personal air sampling; indoor, outdoor and Grenoble; approximately 1200 adults monitoring; time-ac Helsinki; with time-activity diary; diary (Fig. 19); sp Milano; random population sample; tasks Praha demographic and socio-economic status Washington, CO 700 adults aged 18-65; 1982-1983 (winter); USA representative; oversample and questionnaire; long commutes and gas resolution; 1-day s ranges; excluded smokers; time of year; day o data on age, gender, work and day status Table 15. (continued) Page 80 of 284 Location Pollutant Participant characteristics Survey characterist Denver, CO 452 adults aged 18-65; 1982-1983 (winter); Colorado, representative; oversample questionnaire; minu USA gas ranges and long commutes; resolution; 2-day s excluded smokers; data on time of year; day o age, gender, work status time of day Elizabeth/ VOCs 355 people; representative; Fall 1981; follow-u Bayonne, oversampled high-exposure in summer 1982; fol New Jersey, occupations; data on age, 49 in early 1983; 2 USA gender, race, socio-economic recall diary; activ status, and proximity to questionnaire VOC sources Portage, NO 2 , RSP 120 children; selected from 1987; retrospective Wisconsin larger (600) cohort; and prospective dia stratified by cooking fuel; 10-15-min resolutio data on gender, age, of year; day of wee parental education of day Steubenville, NO 2 , RSP 150 winter, 250 summer; 1987; retrospective Ohio selected from cohort of 600 and prospective dia children; stratified by 10-15-min resolutio cooking fuel; data on gender, of year; day of wee age, parental education time of day. Topeka, NO 2 , RSP 300 winter, 300 summer; 1988; retrospective Kansas, selected from cohort of and prospective USA 600 children; stratified by questionnaires; 10- http://www.inchem.org/documents/ehc/ehc/ehc<strong>214</strong>.htm 6/1/2007
HUMAN EXPOSURE ASSESSMENT Table 15. (continued) cooking fuel; data on gender, resolution; time of age, parental education day of week; time o Location Pollutant Participant characteristics Survey characterist California, VOCs 188 people; representative; February-March 1984 USA oversampled high-exposure follow-up: 52 in Ma occupation; data on age, 1984 and 51 in Feb gender, race, socio-economic March 1987; 24-h re status and proximity to VOC diary; activity sources questionnaire Boston, NO 2 325 (winter), 298 (summer) 1986; diary and Massachusetts, ages 8 and above; questionnaire; USA representative; stratified 15-30-min resolutio by range type; no personal sample; time of yea data of week; time of da Los Angeles NO 2 620 people ages 8 and above May 1987-May 1988; d and Orange sampled two 24-h periods; 65 questionnaire; 15-m Counties; sampled eight cycles; resolution; two-day representative; data on age, time of year; day o gender, work status time of day Albuquerque, NO 2 1000+ infants; stratified January 1988-Decembe New Mexico, by range type; data on every 2 months for USA child's health and parents' first 18 months of socio-economic and 60 min; time of yea demographic characteristics day of week; time o reporting a smoker present in the home was associated with increased indoor concentrations and personal exposures of aromatic compounds; visiting dry cleaners, self-reports of proximity to smokers, pesticide use, exposure to solvent, degreasing compounds, and odorous chemicals, and employment status in certain occupations (e.g., paint, chemical or plastics plants) were associated with increased personal exposure to several VOCs (Wallace et al., 1985, 1986, 1988). Occupational exposure may be an important component of total exposure for some individuals or sub-populations. 2. Time-activity data allow modelling of human exposure to pollutants for which personal monitors are not yet available or are very expensive, or for which exposure is a function of multiple pathways. Total exposure can be simulated from information on the time spent doing various activities and/or in specific locations, coupled with knowledge about the likely range of pollutant concentrations in each situation. For example, the models SHAPE (Ott et al., 1988), NEM (Johnson et al., 1990), SIMSYS (Sexton & Ryan, 1988), and REHEX (Hall et al., 1992) are currently being used to estimate exposure to carbon monoxide, ozone, particulates, sulfur dioxide and nitrogen dioxide. http://www.inchem.org/documents/ehc/ehc/ehc<strong>214</strong>.htm Page 81 of 284 6/1/2007
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