The influence of residential and workday population mobility on exposure to air pollution in the UK
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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2018-12-01
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| Series: | Environment International |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S016041201830864X |
| _version_ | 1819072030495997952 |
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| author | Stefan Reis Tomáš Liška Massimo Vieno Edward J. Carnell Rachel Beck Tom Clemens Ulrike Dragosits Samuel J. Tomlinson David Leaver Mathew R. Heal |
| author_facet | Stefan Reis Tomáš Liška Massimo Vieno Edward J. Carnell Rachel Beck Tom Clemens Ulrike Dragosits Samuel J. Tomlinson David Leaver Mathew R. Heal |
| author_sort | Stefan Reis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-21T17:31:15Z |
| format | Article |
| id | doaj.art-78428d2ed6f64f128a43eac6b20dbd2e |
| institution | Directory Open Access Journal |
| issn | 0160-4120 |
| language | English |
| last_indexed | 2024-12-21T17:31:15Z |
| publishDate | 2018-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj.art-78428d2ed6f64f128a43eac6b20dbd2e2022-12-21T18:55:55ZengElsevierEnvironment International0160-41202018-12-01121803813The influence of residential and workday population mobility on exposure to air pollution in the UKStefan Reis0Tomáš Liška1Massimo Vieno2Edward J. Carnell3Rachel Beck4Tom Clemens5Ulrike Dragosits6Samuel J. Tomlinson7David Leaver8Mathew R. Heal9Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UK; University of Exeter Medical School, Knowledge Spa, Truro TR1 3HD, UK; Corresponding author at: Centre of Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UK.Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UK; School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH9 3FJ, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKFarr Institute, School of GeoSciences, University of Edinburgh, Nine, BioQuarter 9 Little France Road, Edinburgh EH16 4UX, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKCentre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UKSchool of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH9 3FJ, UKTraditional 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.http://www.sciencedirect.com/science/article/pii/S016041201830864X |
| spellingShingle | Stefan Reis Tomáš Liška Massimo Vieno Edward J. Carnell Rachel Beck Tom Clemens Ulrike Dragosits Samuel J. Tomlinson David Leaver Mathew R. Heal The influence of residential and workday population mobility on exposure to air pollution in the UK Environment International |
| title | The influence of residential and workday population mobility on exposure to air pollution in the UK |
| title_full | The influence of residential and workday population mobility on exposure to air pollution in the UK |
| title_fullStr | The influence of residential and workday population mobility on exposure to air pollution in the UK |
| title_full_unstemmed | The influence of residential and workday population mobility on exposure to air pollution in the UK |
| title_short | The influence of residential and workday population mobility on exposure to air pollution in the UK |
| title_sort | influence of residential and workday population mobility on exposure to air pollution in the uk |
| url | http://www.sciencedirect.com/science/article/pii/S016041201830864X |
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