nerc.ac.uk

Effect of monitoring network design on land use regression models for estimating residential NO2 concentration

Wu, Hao; Reis, Stefan; Lin, Chun; Heal, Mathew R.. 2017 Effect of monitoring network design on land use regression models for estimating residential NO2 concentration. Atmospheric Environment, 149. 24-33. 10.1016/j.atmosenv.2016.11.014

Before downloading, please read NORA policies.
[img]
Preview
Text
N515263JA.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (2MB) | Preview

Abstract/Summary

Land-use regression (LUR) models are increasingly used to estimate exposure to air pollution in urban areas. An appropriate monitoring network is an important component in the development of a robust LUR model. In this study concentrations of NO2 were simulated by a dispersion model at ‘virtual’ monitoring sites in 54 network designs of varying numbers and types of site, using a 25 km2 area in Edinburgh, UK, as an example location. Separate LUR models were developed for each network. The LUR models were then used to estimate NO2 concentration at all residential addresses, which were evaluated against the dispersion-modelled concentration at these addresses. The improvement in predictive capability of the LUR models was insignificant above ∼30 monitoring sites, although more sites tended to yield more precise LUR models. Monitoring networks containing sites located within highly populated areas better estimated NO2 concentrations across all residential locations. LUR models constructed from networks containing more roadside sites better characterised the high end of residential NO2 concentrations but had increased errors when considering the whole range of concentrations. No particular composition of monitoring network resulted in good estimation simultaneously across all residential NO2 concentration and of the highest NO2 levels. This evaluation with dispersion modelling has shown that previous LUR model validation methods may have been optimistic in their assessment of the model's predictive performance at residential locations.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1016/j.atmosenv.2016.11.014
CEH Sections: Dise
ISSN: 1352-2310
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: land-use regression model, dispersion model, exposure assessment
NORA Subject Terms: Ecology and Environment
Health
Atmospheric Sciences
Date made live: 29 Nov 2016 10:57 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/515263

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...