Application of air-cathode pipe reactor to simultaneously suppress sulphate reduction and accelerate COD oxidation in synthetic wastewater

While bio-corrosion causes severe damage to sewer pipeline, removal of organics in wastewater treatment plants consume substantial energy and is costly. Accepting the electrons from degrading organics by sulphate will produce sulphide – the culprit of corrosion. In this experiment, electrodes were tested for its ability to reduce sulphide formation by transferring electrons to outside the water. Two bench-scale pipe reactors, one with and the other without electrodes were fed with acetate based synthetic wastewater (800mg/l COD) and sulphate (39 mg/l). In all cases, electrodes were found to suppress sulphate reduction; for low sulphate feed, the average reduction was 2 compared to 4 mg/l and for high sulphate feed it was 20 compared to 68 mg/l. In addition electrodes assisted higher COD removal; the average removal during low sulphate feed was 200 compared to 300 mg/l, but during high sulphate feed they were 300 compared to 450 mg/l

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

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

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