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dc.contributor.authorGoonetilleke, Ashantha-
dc.date.accessioned2026-04-07T09:28:59Z-
dc.date.available2026-04-07T09:28:59Z-
dc.date.issued2016-09-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0269749116304304-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/20926-
dc.description.abstractAmong urban stormwater pollutants, hydrocarbons are a significant environmental concern due to their toxicity and relatively stable chemical structure. This study focused on the identification of hydrocarbon contributing sources to urban road dust and approaches for the quantification of pollutant loads to enhance the design of source control measures. The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification. Study outcomes identified non-combusted lubrication oils, non-combusted diesel fuels and tyre and asphalt wear as the three most critical urban hydrocarbon sources. The site specific variabilities of contributions from sources were replicated using three mathematical models. The models employed predictor variables of daily traffic volume (DTV), road surface texture depth (TD), slope of the road section (SLP), effective population (EPOP) and effective impervious fraction (EIF), which can be considered as the five governing parameters of pollutant generation, deposition and redistribution. Models were developed such that they can be applicable in determining hydrocarbon contributions from urban sites enabling effective design of source control measures.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCivil engineeringen_US
dc.subjectStormwater qualityen_US
dc.subjectUrban road dusten_US
dc.subjectHydrocarbonsen_US
dc.subjectSource identificationen_US
dc.subjectSource contributionsen_US
dc.titleSources of hydrocarbons in urban road dust: Identification, quantification and predictionen_US
dc.typeArticleen_US
Appears in Collections:Department of Civil Engineering

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