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Updated: Sep 21, 2026

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
A review and analysis of personal and ambient PM2.5 measurements: Implications for epidemiology studies
Steven R Boomhower1, Christopher M Long2, Wenchao Li2
1Gradient, One Beacon Street, Boston, MA, 02108, USA; Harvard Division of Continuing Education, Harvard University, Cambridge, MA, 02138, USA.
Background:
In epidemiology studies, ambient measurements of PM2.5 are often used as surrogates for personal exposures. However, it is unclear the degree to which ambient PM2.5 reflects personal exposures.
Objective:
In order to examine potential sources of bias in epidemiology studies, we conducted a review and meta-analysis of studies to determine the extent to which short-term measurements of ambient PM2.5 levels are related to short-term measurements of personal PM2.5 levels.
Methods:
We conducted a literature search of studies reporting both personal and ambient measurements of PM2.5 published in the last 10 years (2009-2019) and incorporated studies published prior to 2009 from reviews.
Results:
Seventy-one studies were identified. Based on 17 studies reporting slopes, a meta-analysis revealed an overall slope of 0.56 μg/m3 (95% CI: [0.39, 0.73]) personal PM2.5 per μg/m3 increase in ambient PM2.5. Slopes for summer months were higher (slope = 0.73, 95% CI: [0.64, 0.81]) than for winter (slope = 0.46, 95% CI: [0.36, 0.57]). Based on 44 studies reporting correlations, we calculated an overall personal-ambient PM2.5 correlation of 0.63 (95% CI: [0.55, 0.71]). Correlations were stronger in studies conducted in Canada (r = 0.86, 95% CI: [0.67, 0.94]) compared to the USA (r = 0.60, 95% CI: [0.49, 0.70]) and China (r = 0.60, 95% CI: [0.46, 0.71]). Correlations also were stronger in urban areas (r = 0.53, 95% CI: [0.43, 0.62]) vs. suburban areas (r = 0.36, 95% CI: [0.21, 0.49]).
Significance:
Our results suggest a large degree of variability in the personal-ambient PM2.5 association and the potential for exposure misclassification and measurement error in PM2.5 epidemiology studies.
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