Imperial College London
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DrDanielaFecht

Faculty of Medicine, School of Public Health

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 3314d.fecht

 
 
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Location

 

529Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Wang:2022:10.1016/j.apr.2022.101506,
author = {Wang, W and Fecht, D and Beevers, S and Gulliver, J},
doi = {10.1016/j.apr.2022.101506},
journal = {Atmospheric Pollution Research},
pages = {101506--101506},
title = {Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain},
url = {http://dx.doi.org/10.1016/j.apr.2022.101506},
volume = {13},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Wang,W
AU  - Fecht,D
AU  - Beevers,S
AU  - Gulliver,J
DO  - 10.1016/j.apr.2022.101506
EP  - 101506
PY  - 2022///
SN  - 1309-1042
SP  - 101506
TI  - Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain
T2  - Atmospheric Pollution Research
UR  - http://dx.doi.org/10.1016/j.apr.2022.101506
UR  - https://www.sciencedirect.com/science/article/pii/S130910422200188X?via%3Dihub
UR  - http://hdl.handle.net/10044/1/98374
VL  - 13
ER  -
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