The influence of residential and workday population mobility on exposure to air pollution in the UK. (December 2018)

• Record Type: Journal Article
• Authors: Reis, Stefan; Liška, Tomáš; Vieno, Massimo; Carnell, Edward J.; Beck, Rachel; Clemens, Tom; Dragosits, Ulrike; Tomlinson, Samuel J.; Leaver, David; Heal, Mathew R.
• Is Part Of: Environment international. Volume 121(2018)Part 1
• Page Start: 803
• Page End: 813
• Publication Date: 2018-12
• Subjects: Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2018.10.005
• Languages: English
• ISSNs: 0160-4120

Abstract

Abstract: 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. Highlights: High-res air pollutant concentrations combined with residence/workplace populations Exposures to NO2, PM2.5 & O3 including workplace hours compared with residence only Population-weighted mean NO2 exposure 0.3 μg m −3 (2%) higher; less for PM2.5 and O3 Individual exposures vary substantially accounting for home and workplace location. Greatest spatio-temporal variation when considering exposure to NO2