Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland

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)

[img] Text
108898.pdf - Published Version
Available under License Creative Commons Attribution.

1MB

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
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

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
656601Measuring Health, Variations in Health and Determinants of HealthAlastair LeylandMedical Research Council (MRC)MC_UU_12017/5IHW - MRC/CSO SPHU
727651SPHSU Core Renewal: Measuring and Analysing Socioeconomic Inequalities in Health Research ProgrammeAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13IHW - MRC/CSO SPHU