Pannullo, F., Lee, D. , Waclawski, E. and Leyland, A. H. (2015) Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland. Atmospheric Environment, 118, pp. 227-235. (doi: 10.1016/j.atmosenv.2015.08.009) (PMID:26435684) (PMCID:PMC4567077)
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Abstract
It has been well documented that air pollution adversely affects health, and epidemiological pollutionhealth studies utilise pollution data from automatic monitors. However, these automatic monitors are small in number and hence spatially sparse, which does not allow an accurate representation of the spatial variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide (NO2) diffusion tubes are also used to measure concentrations, and due to their lower cost compared to automatic monitors are much more prevalent. However, even combining both data sets still does not provide sufficient spatial coverage of NO2 for epidemiological studies, and modelled concentrations on a regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling approach to using all three sources of NO2 data to make fine scale spatial predictions for use in epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO2 concentrations from both automatic monitors and diffusion tubes against modelled NO2 concentrations from an atmospheric dispersion model in order to predict fine scale NO2 concentrations across our West Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of NO2 compared to using the automatic monitors alone, and we use it to predict NO2 concentrations across West Central Scotland in 2006.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Lee, Professor Duncan and Pannullo, Miss Francesca and Leyland, Professor Alastair |
Authors: | Pannullo, F., Lee, D., Waclawski, E., and Leyland, A. H. |
College/School: | College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Journal Name: | Atmospheric Environment |
Publisher: | Pergamon Press |
ISSN: | 1352-2310 |
ISSN (Online): | 1873-2844 |
Copyright Holders: | Copyright © 2015 The Authors |
First Published: | First published in Atmospheric Environment 118:227-235 |
Publisher Policy: | Reproduced under a Creative Commons License |
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