Personal exposure levels to O(3), NO(x) and PM(10) and the association to ambient levels in two Swedish cities

Exposure to air pollution is of great concern for public health although studies on the associations between exposure estimates and personal exposure are limited and somewhat inconsistent. The aim of this study was to quantify the associations between personal nitrogen oxides (NO(x)), ozone (O(3)) and particulate matter (PM(10)) exposure levels and ambient levels, and the impact of climate and time spent outdoors in two cities in Sweden. Subjects (n = 65) from two Swedish cities participated in the study. The study protocol included personal exposure measurements at three occasions, or waves. Personal exposure measurements were performed for NO(x) and O(3) for 24 h and PM(10) for 24 h, and the participants kept an activity diary. Stationary monitoring stations provided hourly data of NO(x), O(3) and PM, as well as data on air temperature and relative humidity. Data were analysed using mixed linear models with the subject-id as a random effect and stationary exposure and covariates as fixed effects. Personal exposure levels of NO(x), O(3) and PM(10) were significantly associated with levels measured at air pollution monitoring stations. The associations persisted after adjusting for temperature, relative humidity, city and wave, but the modelled estimates were slightly attenuated from 2.4% (95% CI 1.8–2.9) to 2.0% (0.97–2.94%) for NO(x), from 3.7% (95% CI 3.1–4.4) to 2.1% (95% CI 1.1–2.9%) for O(3) and from 2.6% (95% 0.9–4.2%) to 1.3% (95% CI − 1.5–4.0) for PM(10). After adding covariates, the degree of explanation offered by the model (coefficient of determination, or R(2)) did not change for NO(x) (0.64 to 0.63) but increased from 0.46 to 0.63 for O(3), and from 0.38 to 0.43 for PM(10). Personal exposure to NO(x), O(3) and PM has moderate to good association with levels measured at urban background sites. The results indicate that stationary measurements are valid as measure of exposure in environmental health risk assessments, especially if they can be refined using activity diaries and meteorological data. Approximately 50–70% of the variation of the personal exposure was explained by the stationary measurement, implying occurrence of misclassification in studies using more crude exposure metrics, potentially leading to underestimates of the effects of exposure to ambient air pollution. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10661-021-09447-7.