Ian Fisher

Onset of severe nitrification in mildly nitrifying chloraminated bulk waters and its relation to biostability

Triggers of severe nitrification in distribution systems are still not clearly understood. Recently, the biostability concept was proposed to explain the chloramine residual below which signs of nitrification would be seen. To improve understanding, mildly nitrifying bulk water samples (nitrite less than 0.010mg-N/L) from Sydney Water distribution systems were incubated at constant temperatures and periodically analysed for nitrogenous compounds and total chlorine. Total ammoniacal nitrogen in the sample was between 0.25 and 0.35mg-N/L. Severe nitrification was triggered when chloramine residuals dropped below about 0.4mg/L - the critical threshold residual. In 45 such samples, the critical threshold residual was 0.2-0.65mg/L. The biostability concept was found to be useful in explaining the residual below which net growth of microorganisms begins. However, this alone could not predict the critical threshold residual. Different means of overcoming this problem are discussed. One of these is the use of the microbial decay factor method, since microbiologically assisted chloramine decay in the samples studied was found to be mostly the result of ammonia-oxidising bacterial activity. Nitrite levels in winter were found to be poor indicators of nitrifying status. Overall the results were found to be useful in controlling nitrification and to obtain early warning of severe nitrification.

A suitable model of combined effects of temperature and initial condition on chlorine bulk decay in water distribution systems

Maintaining a chlorine residual is a major disinfection goal in many water distribution systems. A suitable general model of chlorine decay in the transported bulk water is an essential component for efficiently modelling chlorine concentration in distribution systems. The two-reactant model meets basic suitability criteria, including accurate prediction of chlorine residual over hundreds of hours, commencing with chlorine concentration 0-4 mg/L. This model was augmented with an equation that increases the decay coefficients with temperature according to Arrhenius theory. The augmented model was calibrated against decay-test data sets to obtain a single invariant set of parameters for each water. Model estimates of chlorine residuals over time closely matched decay-test data, over the usual operating ranges of initial chlorine concentration (1-4 mg/L) and temperature (3.5-28 °C). When the augmented model was fitted to partial data sets, it also predicted the data reserved for validation very well, suggesting that this model can accurately predict the combined effect of initial chlorine concentration and temperature on chlorine bulk decay in distribution systems, using a single set of invariant parameters for a given source water.

Suitability of chlorine bulk decay models for planning and management of water distribution systems

Effective disinfection planning and management in large, complex water distribution systems requires an accurate network water quality model. This model should be based on reaction kinetics, which describes disinfectant loss from bulk water over time, within experimental error. Models in the literature were reviewed for their ability to meet this requirement in real networks. Essential features were identified as accuracy, simplicity, computational efficiency, and ability to describe consistently the effects of initial chlorine dose, temperature variation, and successive rechlorinations. A reaction scheme of two organic constituents reacting with free chlorine was found to be necessary and sufficient to provide the required features. Recent release of the multispecies extension (MSX) to EPANET and MWH Softs H2OMap Water MSX network software enables users to implement this and other multiple-reactant bulk decay models in real system simulations.

Effects of stratification on chloramine decay in distribution system service reservoirs.

Water quality in chloraminated distribution systems is affected by microbial activity, particularly due to nitrifiers that accelerate chloramine decay. In summer, continuous thermal stratification increases retention time and lowers chloramine residual in some parts of a system service reservoir (tank), relative to fully mixed conditions. According to temperature and chemical indicators, cooling in winter destratifies these reservoirs naturally. Traditional (chemical) indicators of nitrification also suggest that destratification occurs with respect to microbiological activity. In contrast, the microbial decay factor (F(m)) method, which separates microbiological and chemical decay in bulk water, identifies strong microbial stratification, even in winter. F(m) can also be used to predict the exacerbated loss of chloramine residual in the following summer, which enables early intervention by system managers to minimise such loss, and so maintain an adequate residual through the distribution system.

Development and application of a method for quantifying factors affecting chloramine decay in service reservoirs

Service reservoirs play an important role in maintaining water quality in distribution systems. Several factors affect the reservoir water quality, including bulk water reactions, stratification, sediment accumulation and wall reactions. It is generally thought that biofilm and sediments can harbour microorganisms, especially in chloraminated reservoirs, but their impact on disinfectant loss on disinfectant loss has not been quantified. Hence, debate exists as to the extent of the problem. To quantify the impact, the reservoir acceleration factor (F(Ra)) is defined. This factor represents the acceleration of chloramine decay arising from all causes, including changes in retention time, assuming that the reservoir is completely mixed. Such an approach quantifies the impact of factors, other than chemical reactions, in the bulk water. Data from three full-scale chloraminated service reservoirs in distribution systems of Sydney, Australia, were analysed to demonstrate the generality of the method. Results showed that in two large service reservoirs (404 x 10(3) m(3) and 82 x 10(3) m(3)) there was minimal impact from biofilm/sediment. However, in a small reservoir (3 x 10(3) m(3)), the biofilm/sediment had significant impact. In both small and large reservoirs, the effect of stratification was significant.

Comment on "using Bayesian statistics to estimate the coefficients of a two-component second-order chlorine bulk decay model for a water distribution system" by Huang, J.J., McBean, E.A. Water Res. (2007).

HuangandMcBean(2007)rightlypointedoutthatanaccuratemodelofchlorinedecayinbulkwaterplaysanimportantrolein meeting disinfection goals in water distribution systems.Thedevelopmentofatwo-componentsecond-ordermodelofchlorine decay in bulk water was a significant step in thelogical progression towards more accurate representation ofthe many complex processes contributing to such decay. It istherefore important to ensure that this and related develop-ments are attributed correctly to those who made them. It isevenmoreimportanttoensurethattheanalyticalsolutiontothis model is correct, because many other models have beenbased upon it, asHuang and McBean (2007)recognised.

A comprehensive bulk chlorine decay model for simulating residuals in water distribution systems

Abstract Chlorine decay models provide efficient ways to develop disinfection strategies for water distribution systems, provided they account separately for bulk and wall decay, and accurately describe decay with a single set of coefficients. The augmented two-reactant (2RA) model is shown to be the simplest model to accurately describe effects of rechlorination dose/timing on bulk chlorine decay, in combination with effects of initial concentration and temperature over long periods. The two-reactant (2R) and variable reaction-coefficient (VRC) models provided predictions of comparable accuracy under higher and successive rechlorination doses at constant temperature. However, the 2RA model provides a more general basis for strategy development, as the VRC model cannot describe the effect of temperature variation. The minimal data-set required for 2RA calibration was similar for all cases considered. The 2RA model is readily applied by incorporation into system modelling software such as the multi-species extension (MSX) to EPANET software.

Comment on “A Variable Rate Coefficient Chlorine Decay Model”

We commend Jonkergouw et al. (1) for adopting the goal of developing a chlorine decay model that is practical for “...day-to-day water distribution network modelling purposes and chlorine dosing optimisation studies” in the sense that the model coefficients are independent of loading conditions (initial and rechlorination doses).

Thermal stratification in drinking water service reservoirs

Abstract Thermal stratification occurs in most natural water bodies, however, its occurrence in drinking water service reservoirs has not been thoroughly investigated in the past. In order to facilitate the use of a lumped model to simulate the mixing and water quality within reservoirs, temperature monitoring studies have been conducted in some reservoirs in Sydney. The results showed that thermal stratification developed in most reservoirs studied, and through the use of the JETLAG model, it has been concluded that stratification can significantly affect mixing in the reservoirs, and hence needs to be incorporated into any reservoir simulation models.

A selection framework for NOM removal process for drinking water treatment

AbstractNOM (natural organic matter) is increasing in water resources worldwide and is becoming more difficult to treat. Drinking water guidelines are becoming more stringent so NOM removal is becoming more critical and requires consideration as a major treatment process, rather than just a polishing step on top of turbidity removal. In this study, a review of available methodologies to determine the required degree of NOM removal was undertaken. It is demonstrated that chlorine decay and THM (trihalomethane) formation modelling of laboratory-treated water samples provides a sound guide to determine the level of NOM removal needed for a given situation. The level of NOM removal needed is linked to a specific distribution system at given water temperature and water age profile. A sample of raw water treated by a given NOM removal process is tested for chlorine decay rates and THM formation kinetics, and these results are used to evaluate the performance of a distribution system with a given configuration. ...