Characteristics and determinants of personal exposure to typical air pollutants: A pilot study in Beijing and Baoding, China

Personal exposure to fine particulate matter (PM2.5), nitrogen oxides (NOx, NO2 and NO), ozone (O3) and sulfur dioxide (SO2) was repeatedly measured among fourteen office workers in Beijing and Baoding, China in summer, autumn and winter of 2019. Time-activity patterns were simultaneously recorded. Determinants of personal air pollution exposure were investigated for each pollutant via a linear mixed effect model. The personal concen-trations of PM2.5, NO2, NO and O3 were higher in autumn and winter than those in summer. A decreasing trend was found in the personal PM2.5 level for a typical indoor population in Beijing, indicating that particulate pollution was effectively controlled in Beijing and its surrounding area. The personal levels of PM2.5, NO2, and O3 were weakly correlated with those monitored at ambient stations and were lower than the respective ambient levels except for PM2.5 in summer and NO2 in winter. This pilot study showed that the indoor air environment, ambient pollution, traffic-related variables and temperature were significant exposure sources for office workers. Our study highlighted the significance of controlling traffic emissions and improving the workplace air quality to protect the health of office workers. More importantly, we demonstrated the feasibility of model development for personal air pollution exposure prediction.

Automated summary

Personal exposure to PM2.5, NOx, NO2, O3, and SO2 was measured among office workers in Beijing and Baoding across different seasons in 2019. The study found higher concentrations of PM2.5, NO2, NO, and O3 in autumn and winter compared to summer. The indoor air environment, ambient pollution, traffic-related variables, and temperature were identified as significant sources of exposure for office workers. Controlling traffic emissions and improving workplace air quality were highlighted as important measures to protect the health of office workers. The study also demonstrated the feasibility of developing models for predicting personal air pollution exposure.