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

Wu, Hao; Reis, Stefan ORCID: https://orcid.org/0000-0003-2428-8320; 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. https://doi.org/10.1016/j.atmosenv.2016.11.014

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Official URL: http://dx.doi.org/10.1016/j.atmosenv.2016.11.014

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):	https://doi.org/10.1016/j.atmosenv.2016.11.014
UKCEH and CEH Sections/Science Areas:	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:	https://nora.nerc.ac.uk/id/eprint/515263

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.atmosenv.2016.11.014

UKCEH and CEH Sections/Science Areas:

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