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Lee-Jane Sally Liu,¹ Ralph Delfino,^2,3 and Petros Koutrakis⁴

¹Department of Environmental Health Sciences, University of South Carolina, Columbia, SC 29208 USA; ²Department of Medicine, University of California, Irvine, CA 92697 USA; ³Graduate School of Public Health, San Diego State University, San Diego, CA 92120 USA; ⁴Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115 USA

Abstract
An ozone exposure assessment study was conducted in a Southern California community. The Harvard ozone passive sampler was used to monitor cohorts of 22 and 18 subjects for 8 weeks during the spring and fall of 1994, respectively. Ozone exposure variables included 12-hr personal O₃ measurements, stationary outdoor O₃ measurements from a continuous UV photometer and from 12-hr Harvard active monitors, and time-activity information. Results showed that personal O₃ exposure levels averaged one-fourth of outdoor stationary O₃ levels, attributable to high percentages of time spent indoors. Personal O₃ levels were not predicted well by outdoor measurements. A random-effect general linear model analysis indicated that variance in personal exposure measurements was largely accounted for by random error (59-82%) , followed by intersubject (9-18%) and between-day (9-23%) random effects. The microenvironmental model performs differently by season, with the regression model for spring cohorts exhibiting two times the R² of the fall cohorts (R² = 0.21 vs. 0.09) . When distance from the stationary monitoring site, elevation, and traffic are taken into account in the microenvironmental models, the adjusted R² increased almost twofold for the fall personal exposure data. The low predictive power is due primarily to the apparent spatial variation of outdoor O₃ and errors in O₃ measurements and in time-activity records (particularly in recording the use of air conditioning) . This study highlights the magnitude of O₃ exposure misclassification in epidemiological settings and proposes an approach to reduce exposure uncertainties in assessing air pollution health effects. Key words: active sampler, exposure assessment, ozone, passive sampler, time-activity pattern. Environ Health Perspect 105:58-65 (1997)

Address correspondence to L.-J.S. Liu, Department of Environmental Health Sciences, University of South Carolina, Health Sciences Building, Room 311, Columbia, SC 29208 USA.

This study was supported by the National Institutes of Health, NIEHS grant ES06214.

Received 19 April 1996 ; accepted 18 September 1996.