摘要：Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of
air pollutants at the residential address of the study population are representative for overall exposure. This
introduces potential bias in the quantification of human health effects. Our study combines new UK Census data
comprising information on workday population densities, with high spatio-temporal resolution air pollution
concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic
estimates of population exposure to NO2, PM2.5 and O3. We explicitly allocated workday exposures for weekdays
between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday
location into account had the most pronounced impact on potential exposure to NO2, with an estimated
0.3 μg m−3 (equivalent to 2%) increase in population-weighted annual exposure to NO2 across the whole UK
population. Population-weighted exposure to PM2.5 and O3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants.
We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations
due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO2 exposure for these individuals were
considerably higher than for the total UK population average when including their workday location.
Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution.
