What is it about?
The design of effective pollution mitigation strategies is challenging due to the lack of reliability in stormwater quality modelling outcomes. Current modelling approaches do not adequately replicate the interdependencies between pollutant processes and their influential factors. Using Bayesian Network modelling, this research study characterised the influence of vehicular traffic on the build-up of the sixteen US EPA classified priority PAHs.
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Why is it important?
The research study discussed in this paper aimed to characterize the influence of vehicular traffic on the build-up of different PAH species, and to characterise this influence in relation to the type of land use. Accordingly, a BN modelling approach was employed to quantify the interdependencies between vehicular traffic and the build-up of PAHs that can exert significant impacts on human health. The use of BNs enabled the investigation of the influence of traffic on PAH build-up far beyond the typical perspective of traffic as a source of PAHs.
Perspectives
The novel modelling approach adopted facilitated the characterisation of the influence of traffic as a source of origin and also as a key factor that influences the re-distribution of PAHs, with positive or negative relationship between traffic volume and PAH build-up.
Professor Ashantha Goonetilleke
Queensland University of Technology
Read the Original
This page is a summary of: Influence of traffic on build-up of polycyclic aromatic hydrocarbons on urban road surfaces: A Bayesian network modelling approach, Environmental Pollution, December 2017, Elsevier,
DOI: 10.1016/j.envpol.2017.10.125.
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