Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain.pdf (3.21 MB)
Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain
journal contributionposted on 2022-09-16, 09:57 authored by Weiyi Wang, Daniela Fecht, Sean Beevers, John Gulliver
Short-term exposure studies have often relied on time-series of air pollution measurements from monitoring sites. However, this approach does not capture short-term changes in spatial contrasts in air pollution. To address this, models representing both the spatial and temporal variability in air pollution have emerged in recent years. Here, we modelled daily average concentrations of nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10) and ozone (O3) on a 25 m grid for Great Britain from 2011 to 2015 using a generalised additive mixed model, with penalised spline smooth functions for covariates. The models included local-scale predictors derived using a Geographic Information System (GIS), daily estimates from a chemical transport model, and daily meteorological characteristics. The models performed well in explaining the variability in daily averaged measured concentrations at 48–85 sites: 63% for NO2, 77% for PM2.5, 80% for PM10 and 85% for O3. Outputs of the study include daily air pollution maps that can be applied in epidemiological studies across Great Britain. Daily concentration values can also be predicted for specific locations, such as residential addresses or schools, and aggregated to other exposure time periods (including weeks, months, or pregnancy trimesters) to facilitate the needs of different health analyses.
MRC Centre for Environment and Health
Medical Research CouncilFind out more...
NIHR Imperial Biomedical Research Centre
National Institute for Health Research (NIHR) Health Protection Research Unit in Chemical and Radiation Threats and Hazards (NIHR-200922)
Author affiliationCentre for Environmental Health and Sustainability, School of Geography, Geology and the Environment, University of Leicester
- VoR (Version of Record)
Published inAtmospheric Pollution Research
Air pollutionAIR-POLLUTIONAREASEnvironmental SciencesEnvironmental Sciences & EcologyEpidemiologyEUROPEEXPOSUREExposure assessmentGeographic information systemLand use regressionLAND-USE REGRESSIONLife Sciences & BiomedicineNO2 CONCENTRATIONPM10PM2.5SATELLITE DATAScience & TechnologySpatio-temporal modelSPATIOTEMPORAL MODEL