Identification and control of the pollutant load in Sewer Network (SNs) is one of the priorities for utilities to reduce the impact on water bodies and to individuate the presence of pathogens to prevent their further spread, sometimes through interventions on a social scale. This goal can be achieved essentially through the development of a monitoring system. This paper proposes a backtracking methodology for efficiently planning a monitoring system in SNs assuming steady state conditions during the analysis. The methodology is based on the calculation of the impact coefficient, which is related to the dilution and decay of contaminants and pathogens in the network, to evaluate the impact of each possible contaminated node on a downstream one in terms of concentration. This information supports the identification of candidate monitoring points, i.e., where to place measurement sensors to ensure complete coverage and control of the network. An additional analysis has been performed considering unsteady conditions for comparing the impact coefficient values averaged over 24 hours and those of the steady state methodology. Results shown similar value between steady-state and unsteady conditions, thus justifying the use of steady-state conditions for the proposed methodology, also for real practical applications, with a significant improvement in terms both of simplicity and computational time saving.

Impact coefficient evaluation for sensor location in sewer systems

Valeria Guadagno;Angelo Leopardi;
2023-01-01

Abstract

Identification and control of the pollutant load in Sewer Network (SNs) is one of the priorities for utilities to reduce the impact on water bodies and to individuate the presence of pathogens to prevent their further spread, sometimes through interventions on a social scale. This goal can be achieved essentially through the development of a monitoring system. This paper proposes a backtracking methodology for efficiently planning a monitoring system in SNs assuming steady state conditions during the analysis. The methodology is based on the calculation of the impact coefficient, which is related to the dilution and decay of contaminants and pathogens in the network, to evaluate the impact of each possible contaminated node on a downstream one in terms of concentration. This information supports the identification of candidate monitoring points, i.e., where to place measurement sensors to ensure complete coverage and control of the network. An additional analysis has been performed considering unsteady conditions for comparing the impact coefficient values averaged over 24 hours and those of the steady state methodology. Results shown similar value between steady-state and unsteady conditions, thus justifying the use of steady-state conditions for the proposed methodology, also for real practical applications, with a significant improvement in terms both of simplicity and computational time saving.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/99884
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