Development of an analytical solution for the parallel second order reaction scheme for chlorine decay modelling

Chlorine is broadly used for water disinfection at the final stage of water treatment because of its high performance to inactivate pathogenic microorganisms, its lower cost compared to other well-known disinfectants and its simple operational needs. However, reaction of chlorine with a wide range of organic and inorganic substances in water causes its decay and formation of chlorinated by-products, which are in some cases carcinogenic and harmful to human health. The major challenge is balancing the risk from these with the cost of operation needed to mitigate the impact. These challenges highlights the importance of having a robust modelling approach for chlorine decay in bulk water as a pre-required step to model the chlorine decay and formation of its by-products in the whole distribution system.In this study, initially, a comprehensive literature review was conducted to investigate and evaluate all existing modelling approaches for chlorine decay prediction especially in bulk water. Among all existing modelling schemes, three models were paid more attention due to their popularity and/or fundamentally valid background. They are first order model, second order model and parallel second order model.During the literature review, comparing the effectiveness of the second order model (SOM) proposed by Clark (1998) with the parallel second order model (PSOM) offered by Kastl et al., (1999), the author found that these two models are both fundamentally sound, although the PSOM had better capability in terms of data fitting, and representing the chlorine decay behaviour is much better than SOM. However, non-existence of analytical solution for PSOM was found to be the major negative point for wide adaptation of PSOM compared to SOM.Trying to understand the basic principles of both models, it was understood that the formulation of SOM was genuine and the researchers who claimed that Clark (1998) made a mistake in deriving the analytical solution were proved wrong. This resulted in having the first publication as a comment in Water Research (Fisher et al., 2010b; Appendix A3).Further study was performed on how SOM was formulated and attempts were made to apply the same methodology to PSOM in order to arrive at an analytical solution. Consequently, making a reasonable assumption, an analytical solution for the parallel second order model was formulated and evaluated against the existing numerical method.As the case study of this research, initially, the previous chlorine decay data from Pilbara Water Treatment Plant was fitted to a first order reaction scheme and it was proved that the data did not comply with it. This was an expected result and the need for other model was validated. For further analysis, fresh water samples were collected from Pilbara Water Treatment Plant to perform chlorine decay tests.Temperature effect on the behaviour of chlorine decay in the bulk water was investigated by integrating Arrhenius equation with PSOM. Three methods of temperature analysis were compared and the best one was recommended for practical application. It was shown that the model was capable enough to properly display the chlorine decay profile when temperature varies.The thesis consists of eight chapters. In chapter 1, a brief description of the research background and the overall objectives of the research are given. Chapter 2 focuses on providing a comprehensive literature review about all involved aspects as well as chlorine decay modelling background. Chapter 3 discusses the methodology and analytical methods for conducting laboratory experiments. Chapter 4 gives a prove that the first order decay model does not show accurate results for chlorine decay prediction and the parallel second order model is much more accurate in predicting chlorine concentration. In Chapter 5, the main part of this research, an analytical solution for the parallel second order model is developed. Chapter 6 evaluates the effectiveness of the parallel second order model against the first and second order model. Within chapter 7, temperature effect on the chlorine decay behaviour and the selected modelling approach is evaluated and chapter 8 gives a brief conclusion and recommendation

Chlorine Decay Modelling to Predict Disinfectant and Disinfectant by-Products (DBPs) Formation in Water Distribution System

The objective of this research project is to understand chlorine decay and formation of disinfectant by-products (DBPs) using existing popular chlorine decay models. Performance of various chlorine decay models for different waters was investigated. Defining main performance criteria, popular models were modified to produce more reliable predictions. Nominated chlorine decay models were compared against defined criteria. Best chlorine decay model was endorsed. Finally, chlorine decay and formation of DBPs in a water distribution system was modelled as a case study

Chlorine decay prediction in bulk water using the parallel second order model: An analytical solution development

All distributed drinking water receives some form of disinfection and a minimum disinfectant residual should be maintained at the customer tap. The most popular disinfectant is chlorine. Chlorine reacts with compounds in water and hence decays. Description of chlorine decay is often difficult, due to a complex set of reactions and an initial fast reaction followed by a slower reaction. Before any attempt could be made to understand the decay characteristics in the distribution system, chlorine decay in bulk water has to be correctly described. The parallel second order reaction model was found to be one of the most suitable models for this purpose. However, widespread use of this model is hindered by its complexity, most importantly the non-existence of an analytical solution. In this paper, an analytical solution for this model was developed by initially assuming that the ratio (α) of slow and fast reaction rate coefficients is small. The estimated parameters and the chlorine residuals predicted by the numerical analysis and the proposed solution were compared for the chlorine decay data sets obtained from the literature as well as laboratory analysis. The results showed that the proposed analytical solution was very accurate for the prediction of chlorine decay behaviour in all samples

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)

Huang and McBean (2007) rightly pointed out that an accurate model of chlorine decay in bulk water plays an important role in meeting disinfection goals in water distribution systems. The development of a two-component second-order model of chlorine decay in bulk water was a significant step in the logical progression towards more accurate representation of the many complex processes contributing to such decay. It is therefore important to ensure that this and related developments are attributed correctly to those who made them. It is even more important to ensure that the analytical solution to this model is correct, because many other models have been based upon it, as Huang and McBean (2007) recognised

Evaluation of second order and parallel second order approaches to model temperature variation in chlorine decay modelling

All drinking water receives some form of disinfection and a minimum residual should remain at the customer’s tap. Most popular disinfectant of all is chlorine. Chlorine reacts with compounds in water and hence leads to decay. Temperature is one of the important factors that control the rate of decay. Annual water temperature variations of more than 20°C are common in distribution systems, so that dosing needs to be adjusted substantially between seasons to maintain residuals within desired limits. Arrhenius equation has been successfully used to estimate the temperature effects on chlorine decay reactions, especially when temperature is below 30°C. The temperature dependence parameter estimated is activation energy (E)/universal gas constant (R). A number of chlorine decay tests were conducted, by varying temperature from 15–50°C. Resulting chlorine measurements were input into AQUASIM, data fitting was performed using the parallel second order model (PSOM) proposed by Kastl et al. [1] and second order model (SOM) proposed by Clark [2]. The model parameters for all modelling approaches were estimated using AQUASIM. PSOM has two reactants and two respective decay coefficients. Results showed that PSOM fitted the data very well when either single or two E/Rs were used. On the contrary, the SOM did not show a good fit to the experimental chlorine decay profile for the same data sets. The results, therefore, indicated PSOM is more convenient to describe chlorine decay profile over a wide range of temperature

Expediting COD removal in microbial electrolysis cells by increasing biomass concentration

Microorganisms catalyse the reaction and in this study, mainly the effect of different concentration of biomass on COD removal was investigated. Three sets of two-compartment reactors were established. The cation exchange membrane (CEM) was employed in each reactor and 0.5. V of electricity was supplied. Graphite rod employed in cathodic part and a combination of graphite rod and graphite granules were used in anodic chamber. The highest rate of COD removal (40. 2.0. ppm/h) was achieved in the reactor which had initial VSS at 6130. mg/l, whereas the slowest rate of 23. 1.2. ppm/h in the reactor started with 3365. mgVSS/l. Some ammonia removal was also noticed during the operation. Further understanding and improvement is needed to be competitive against traditional wastewater treatment processes

Modelling chlorine residual and trihalomethane profiles in water distribution systems after treatment including pre-chlorination

Accurate, efficient distribution system models predict profiles of chlorine and trihalomethane concentrations using chemical reactions. Constant coefficients defining reaction-rates are typically derived from laboratory decay-tests conducted days after sampling from a particular water treatment plant (WTP). The problem is any post-filter chlorine residual due to pre-chlorination will have reacted completely beforehand. Consequently, the derived reaction-model will not accurately represent water exiting the WTP filters. Two methods to include these missing reactions were successfully developed. They have similar accuracy but the second method is less efficient as it adds a third reactant and requires estimation of two more coefficients. Both require an additional decay-test at the WTP, commencing immediately after sampling. Due to pre-chlorination, the linear increase in total trihalomethane (TTHM) formation with increasing chlorine demand (after primary disinfection) commences at some positive TTHM concentration. The TTHM concentration measured at the laboratory must be reduced by that resulting from the post-filter residual reactions, to accurately represent TTHMs leaving the WTP. Where treatment does not involve pre-chlorination, some downstream chlorine demand does not produce TTHMs. This was accurately modelled by identifying a fraction of fast reactant as non-productive. The work extends applicability and improves accuracy of chlorine/trihalomethane modelling of distribution systems

Effectiveness of parallel second order model over second and first order models

The chlorine decay is usually described by the first order model (FOM) due to its easiness, although its weaknesses are well known. In this work, two better models, second order model (SOM) and parallel second order model (PSOM), are compared for their accuracy to predict chlorine residuals for a single dosing scenario. Results showed that SOM model provided a better prediction compared to FOM. However, SOM had two important shortcomings. Firstly, it overly predicted residuals in the lower end of chlorine decay curve, implying false sense of security in achieving secondary disinfection goals. Secondly, when higher initial dose was practiced, chlorine residual prediction was poorer. PSOM on the other hand provided the best fit for the experimental data in the initial as well as the later part of the decay curve for any doses. Compared to SOM which had two parameters, PSOM is more complex as it uses four parameters. Comparing to the advantages, complexity of PSOM is not an issue as EPANET-MSX can be used for full scale system simulation