Predicting of Particle Exhaust-Emissions from Urban Road Traffic Using Artificial Neural Networks (ANNs)

Belkacem, Ines; Helali, Ali; Khardi, Salah; Slimi, Khalifa

doi:10.1007/978-3-030-84958-0_39

Cited by 3 publications

(1 citation statement)

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“…Road traffic is the main source in the degradation of the ambient air quality (Belkacem et al 2020(Belkacem et al , 2022Silva et al 2020). The total non-exhaust PM (PM2.5 and PM10) induced by light-duty vehicles worldwide will increase by 53.5% along with transport demand in 2030 as compared to 2017 (OECD 2020).…”

Section: Introductionmentioning

confidence: 99%

Investigations on vehicle non-exhaust particle emissions: real-time measurements

Belkacem

Helali

Khardi

et al. 2022

Int. J. Environ. Sci. Technol.

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Despite the potentially harmful effects on health and environmental impacts correlated with non-exhaust emissions (e.g., brake, tire and road wear and resuspension), but very limited environmental research studies have measured the contribution of vehicle non-exhaust emissions in real-world measurements and at different road segment types. Therefore, to fill this gap in academic literature, the main purpose of this study is to collect the knowledge base required to orient towards more sustainable mobility. During July 2019, continuous real-world measurements of non-exhaust particles (NEPs) were recorded over three different road segment types (urban, rural and motorway) in the city of Bron, near Lyon (France). Data were obtained using a native algorithm based on the GRIMM analyzer, series 1.108 Portable Aerosol Spectrometer. Results have confirmed abundant fine/coarse non-exhaust particle emissions which increase with the average vehicle speed and during sharp acceleration/deceleration manoeuvers. Motorway area has recorded the highest particle number concentrations as compared to urban and rural areas, which reaches 1.85 × 10 7 cm −3 due to increased vehicle speed, pavement materials and abrupt vehicle acceleration and deceleration maneuvers. In addition, the highest PM ratio was registered on motorway area and the lowest PM ratio appeared on urban road due to vehicle speed. It has been concluded that NEPs depended on the changes in driving conditions and road pavement type.

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Section: Introductionmentioning

confidence: 99%