Assessment of probable causes of chlorine decay in water distribution systems of Gaborone city, Botswana

Abstract

Assessment of probable causes of chlorine decay in water distribution systems of Gaborone city, Botswana Gaborone city water distribution system (GCWDS) is rapidly expanding and has been faced with the major problems of high water losses due to leakage, water shortages due to drought and inadequate chlorine residuals at remote areas of the network. This study investigated the probable causes of chlorine decay, due to pipe wall conditions and distribution system water quality in the GCWDS. An experimental approach, which applied a pipe-loop network model to estimate biofilm growth and chlorine reaction rate constants, was used to analyse pipe wall chlorine decay. Also, effects of key water quality parameters on chlorine decay were analysed. The water quality parameters considered were: natural organic matter (measured by total organic carbon, TOC; dissolved organic carbon, DOC; and ultraviolet absorbance at wavelength 254, UVA-254, as surrogates), inorganic compounds (iron and manganese) and heterotrophic plate count (HPC). Samples were collected from selected locations in the GCWDS for analysis of water quality parameters. The results of biofilm growth and chlorine reaction rate constants revealed that chlorine decay was higher in pipe walls than in the bulk of water in the GCWDS. The analysis of key water quality parameters revealed the presence of TOC, DOC and significant levels of organics (measured by UVA-254), which suggests that organic compounds contributed to chlorine decay in the GCWDS. However, low amounts of iron and manganese (< 0.3 mg/L) indicated that inorganic compounds may have had insignificant contributions to chlorine decay. The knowledge gained on chlorine decay would be useful for improving water treatment and network operating conditions so that appropriate chlorine residuals are maintained to protect the network from the risks of poor water quality that may occur due to the aforementioned problems.

Comparison of commercial disinfectants and an in loco-produced solution: free residual chlorine decay in human supply waters

“…After all these substances are oxidized, the FRC will tend to decay more slowly. This behavior is consistent with what is observed in other studies available in the literature (Gallandat et al 2019;Nono et al 2019).…”

“…Due to the diversity of water characteristics, FRC species react with various substances such as iron, manganese, ammonia (inorganic matter) and organic matter in general, which causes two stages of decay of their concentrations: first reacting with inorganic material and then with organic material (Vieira et al 2004;Gallandat et al 2019;Nono et al 2019).…”

Residential Water Softeners Release Carbon, Consume Chlorine, and Require Remediation after Hydrocarbon Contamination

“…One study showed that carbon compounds leached from resins were transformed into nitrosamines when in contact with free chlorine . Organic carbon is important because it can prompt greater disinfection byproduct concentrations, , promote disinfectant decay, , and support microbial regrowth. , …”

“…One study showed that carbon compounds leached from resins were transformed into nitrosamines when in contact with free chlorine. 26 Organic carbon is important because it can prompt greater disinfection byproduct concentrations, 52,53 promote disinfectant decay, 54,55 and support microbial regrowth. 56,57 A styrene monomer was extracted into methylene chloride from the PUR resin, but styrene was not extracted from the other resins (Figure SI-6).…”

Optimal Water Quality Simulation of the Proposed Water Distribution System for the University of Kashmir Using EPANET 2.2 and Leakage Modelling of the Network Using EPANET Extension—WaterNetGen

“…A water quality model has to be an optimal solution, like that of the hydraulic model, to achieve the maximum efficiency of the performance of a WDS [3]. Important water quality parameters like concentration of chlorine, decay of chlorine in the system [4,5] and water age [6] have to be modelled, so as to ascertain that the quality of the water is as per the standards [7]. Standard values of these parameters are vital for the optimality of the water quality model, indicating that these parameters are the decision variables for the optimal model, with the standard ranges of these variables as constraints.…”