Models of chlorine kinetics in distribution systems characterize chlorine decay as a combination of first‐order decay in the bulk liquid and first‐order or zero‐order decay reactions at the pipe wall.
Proper understanding, characterization, and prediction of water quality behavior in drinking water distribution systems are critical to ensure meeting regulatory requirements and customer‐oriented expectations. This article investigates the factors leading to loss of chlorine residual in water distribution systems. Kinetic rate equations describing the decay of chlorine were developed, tested, and evaluated using data collected in field‐sampling studies conducted at several water utility sites. Results indicated that chlorine decay in distribution systems can be characterized as a combination of first‐order reactions in the bulk liquid and first‐order or zero‐order mass transfer–limited reactions at the pipe wall. Wall reaction kinetic constants were inversely proportional to pipe roughness coefficients. Wide variations in both bulk reaction constants and wall reaction constants were observed among the sites.
Concerns about water quality and possible intentional contamination of water distribution systems are making on-line monitoring an increasingly important priority for many water utilities. The city of Ann Arbor (Mich.) evaluated different water quality monitoring parameters, tested multiple manufacturers' monitoring equipment, and evaluated how to effectively locate monitoring equipment within the distribution system to address these two concerns. A suite of modeling tools was used in this case study. Total chlorine, ultraviolet absorbance at 254 nm, conductivity, and dissolved oxygen were selected for monitoring based on pilot testing. When balancing costs and benefits, four stations for monitoring water quality and four stations for monitoring contamination events were found to be sufficient for the city. Only one location was common between water quality and security sites, and the number of security monitors needed was not affected by system demands. It was confirmed that it is critical to minimize response time in order to mitigate the effects of a contamination event.
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