Development of Land Use Regression models for predicting exposure to NO2 and NOx in Metropolitan Perth, Western Australia. (December 2015)

• Record Type: Journal Article
• Authors: Dirgawati, Mila; Barnes, Rosanne; Wheeler, Amanda J.; Arnold, Anna-Lena; McCaul, Kieran A.; Stuart, Amy L.; Blake, David; Hinwood, Andrea; Yeap, Bu B.; Heyworth, Jane S.
• Is Part Of: Environmental modelling & software. Volume 74(2015:Dec.)
• Page Start: 258
• Page End: 267
• Publication Date: 2015-12
• Subjects: Land Use Regression (LUR) model -- Air pollution -- Nitrogen dioxide (NO2) -- Oxides of nitrogen (NOx); Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.07.008
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This study developed LUR models for predicting exposure to NO2 and NOx among of 12, 203 elderly men in Perth. NOx and NO2 concentrations were determined for 2-week periods in summer, autumn, and winter, from January to September 2012, at 43 sites. The LUR models were developed to predict annual average concentrations of nitric oxides based upon land use, population/household density, and traffic variables within different buffer sizes, following the procedures of the European Study of Cohort for Air Pollution Effects program. The sample mean and standard deviation of the annual average concentrations of NO2 and NOx were 10.1 ± 5.3 μg/m 3 and 18.7 ± 11.7 μg/m 3 respectively, lower than those of ESCAPE study areas. The LUR models explained 69% of the variance in NO2 and 75% variance of NOx . Both the NO2 and NOx models had similar predictors, including traffic intensity on the nearest roads, household density within-1000 m industrial activities within-5000 m, and road length within-50 m.