The United Nations’ 2030 Agenda for Sustainable Development emphasizes the crucial role of water management in human activities, yet the transportation sector has often overlooked water as a valuable resource. This paper delves into the potential of analysing road runoff waters, particularly in understanding pollutant generation and adopting mitigation measures. The methodology, developed in coherence with FHWA approaches, allows for the calculation of pollutant concentrations in road runoff waters following rainfall events. Results from a multi-case scenario highlight significant differences in pollutant generation between urban, extra-urban, and rural roads. Sensitivity analyses reveal the impact of rainfall intensity, drainage length, and traffic volume on pollutant concentrations. The study underscores the need for multidisciplinary approaches in infrastructure design and maintenance, considering ecological factors and regulatory mandates.

Predictive Model to Assess Pollution from Road Runoff Waters as a Tool to Increase Sustainable Mobility / Corazza, Maria Vittoria; Moretti, Laura; Di Mascio, Paola; Del Serrone, Giulia; Cera, Luciano. - (2024), pp. 1-6. (Intervento presentato al convegno 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) tenutosi a Roma; Italia) [10.1109/eeeic/icpseurope61470.2024.10751284].

Predictive Model to Assess Pollution from Road Runoff Waters as a Tool to Increase Sustainable Mobility

Corazza, Maria Vittoria;Moretti, Laura;Di Mascio, Paola;Del Serrone, Giulia;Cera, Luciano
2024

Abstract

The United Nations’ 2030 Agenda for Sustainable Development emphasizes the crucial role of water management in human activities, yet the transportation sector has often overlooked water as a valuable resource. This paper delves into the potential of analysing road runoff waters, particularly in understanding pollutant generation and adopting mitigation measures. The methodology, developed in coherence with FHWA approaches, allows for the calculation of pollutant concentrations in road runoff waters following rainfall events. Results from a multi-case scenario highlight significant differences in pollutant generation between urban, extra-urban, and rural roads. Sensitivity analyses reveal the impact of rainfall intensity, drainage length, and traffic volume on pollutant concentrations. The study underscores the need for multidisciplinary approaches in infrastructure design and maintenance, considering ecological factors and regulatory mandates.
2024
2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
run-off waters; sustainable mobility; infrastructure
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Predictive Model to Assess Pollution from Road Runoff Waters as a Tool to Increase Sustainable Mobility / Corazza, Maria Vittoria; Moretti, Laura; Di Mascio, Paola; Del Serrone, Giulia; Cera, Luciano. - (2024), pp. 1-6. (Intervento presentato al convegno 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) tenutosi a Roma; Italia) [10.1109/eeeic/icpseurope61470.2024.10751284].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1727503
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