Optimal sensor placement for detecting organophosphate intrusions into water distribution systems.

Water Res

Faculty of Civil and Environmental Engineering, Technion - Israel Institute of Technology, Haifa 32000, Israel. Electronic address:

Published: April 2015

AI Article Synopsis

  • Placement of water quality sensors is crucial for reducing risks of contamination in water distribution systems, with this study focusing on organophosphate contaminants and their effects on public health.
  • The methodology integrates water chemistry, reaction kinetics, and statistical models to estimate the number of affected people by predicting interactions between organophosphates and free chlorine.
  • Three organophosphates (chlorpyrifos, malathion, and parathion) are analyzed, and the study showcases a genetic algorithm approach to optimize sensor placement and minimize public impact through simulated events and sensitivity analyses.

Article Abstract

Placement of water quality sensors in a water distribution system is a common approach for minimizing contamination intrusion risks. This study incorporates detailed chemistry of organophosphate contaminations into the problem of sensor placement and links quantitative measures of the affected population as a result of such intrusions. The suggested methodology utilizes the stoichiometry and kinetics of the reactions between organophosphate contaminants and free chlorine for predicting the number of affected consumers. This is accomplished through linking a multi-species water quality model and a statistical dose-response model. Three organophosphates (chlorpyrifos, malathion, and parathion) are tested as possible contaminants. Their corresponding by-products were modeled and accounted for in the affected consumers impact calculations. The methodology incorporates a series of randomly generated intrusion events linked to a genetic algorithm for minimizing the contaminants impact through a sensors system. Three example applications are explored for demonstrating the model capabilities through base runs and sensitivity analyses.

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Source
http://dx.doi.org/10.1016/j.watres.2015.01.024DOI Listing

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