Development of a land use regression model for daily NO 2 and NO x concentrations in the Brisbane metropolitan area, Australia

Citation data:

Environmental Modelling & Software, ISSN: 1364-8152, Vol: 95, Page: 168-179

Publication Year:
2017
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DOI:
10.1016/j.envsoft.2017.06.029
Author(s):
Md Mahmudur Rahman, Bijan Yeganeh, Sam Clifford, Luke D. Knibbs, Lidia Morawska
Publisher(s):
Elsevier BV
Tags:
Computer Science, Environmental Science
article description
Land use regression models are an established method for estimating spatial variability in gaseous pollutant levels across urban areas. Existing LUR models have been developed to predict annual average concentrations of airborne pollutants. None of those models have been developed to predict daily average concentrations, which are useful in health studies focused on the acute impacts of air pollution. In this study, we developed LUR models to predict daily NO 2 and NO x concentrations during 2009–2012 in the Brisbane Metropolitan Area (BMA), Australia's third-largest city. The final models explained 64% and 70% of spatial variability in NO 2 and NO x, respectively, with leave-one-out-cross-validation R 2 of 3–49% and 2–51%. Distance to major road and industrial area were the common predictor variables for both NO 2 and NO x, suggesting an important role for road traffic and industrial emissions. The novel modeling approach adopted here can be applied in other urban locations in epidemiological studies.

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