| Literature DB >> 26874759 |
I Alameddine1, L Abi Esber1, E Bou Zeid2, M Hatzopoulou3, M El-Fadel4.
Abstract
This study presents a modeling framework to quantify the complex roles that traffic, seasonality, vehicle characteristics, ventilation, meteorology, and ambient air quality play in dictating in-vehicle commuter exposure to CO and PM2.5. For this purpose, a comprehensive one-year monitoring program of 25 different variables was coupled with a multivariate regression analysis to develop models to predict in-vehicle CO and PM2.5 exposure using a database of 119 mobile tests and 120 fume leakage tests. The study aims to improve the understanding of in-cabin exposure, as well as interior-exterior pollutant exchange. Model results highlighted the strong correlation between out-vehicle and in-vehicle concentrations, with the effect of ventilation type only discerned for PM2.5 levels. Car type, road conditions, as well as meteorological conditions all played a significant role in modulating in-vehicle exposure. The CO and PM2.5 exposure models were able to explain 72 and 92% of the variability in measured concentrations, respectively. Both models exhibited robustness and no-evidence of over-fitting.Entities:
Keywords: CO; In-vehicle exposure; Multivariate analysis; PM(2.5)
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Year: 2016 PMID: 26874759 DOI: 10.1016/j.scitotenv.2016.01.030
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963