Elisabeth v. Münch

Simultaneous nitrification and denitrification in bench-scale sequencing batch reactors

Two bench-scale sequencing batch reactors were fed with domestic wastewater and operated in an anaerobic-aerobic sequence for 139 d. Denitrification during the aerated react period was observed and the factors influencing the extent of simultaneous nitrification and denitrification were examined. It was found that the influence of DO on the nitrification rate during the aerated react period could be described by a Monod kinetic with a high oxygen half-saturation coefficient for autotrophic nitrifiers (KO.A) of 4.5 mg/l. The dependency of the denitrification rate on DO could be described by a mathematical switching function with a higher switching function constant than expected, meaning that the extent of aerobic denitrification was higher than usual. It was also observed that aerobic denitrification decreased with time over the aerated react period. For most of the time of reactor operation nitrite was the main NOx species in the effluent, instead of the commonly expected nitrate. This led to the conclusion that the activity of Nitrobacter species was probably inhibited in the SBRs studied. It also demonstrated the importance of measuring nitrite in the effluent to ensure that the reactor performance and the extent of aerobic denitrification was not over-estimated.

Controlled struvite crystallisation for removing phosphorus from anaerobic digester sidestreams

Enhanced biological phosphorus removal wastewater treatment plants that use anaerobic digesters for sludge treatment, have high phosphorus concentrations in the sidestreams from their sludge dewatering equipment. To remove phosphorus from such sidestreams controlled struvite crystallisation can be used. Struvite (or MAP) is a naturally occurring crystal of magnesium, ammonium and phosphate. We present operational results obtained with a continuously operated pilot-scale MAP reactor. The pilot-scale reactor (143 l) was an air agitated column reactor with a reaction and a settling zone, based on the Phosnix process of Unitika Ltd., Japan. The influent to the MAP reactor was centrate from the centrifuge that dewaters anaerobically digested sludge at the Oxley Creek wastewater treatment plant in Brisbane. We used a 60% magnesium hydroxide slurry to add the required magnesium to the process and to obtain the alkaline pH value required. The pilot-scale MAP process achieved an ortho-P removal ratio of 94% from an average influent ortho-P concentration of 61 mg/l. The reactor was operated at a pH of around 8.5. Insufficient dosing of magnesium reduced the P removal performance. There was no influence of the hydraulic residence time on the process in the range of 1-8 h. The dry MAP product had cadmium, lead and mercury concentrations well below the legal limits for fertilisers in Queensland, Australia and can be reused as a valuable slow-release fertiliser.

Mathematical modelling of prefermenters—I. Model development and verification

A dynamic mathematical model of prefermentation is presented. Prefermentation is becoming an increasingly popular unit operation in biological nutrient removal wastewater treatment plants. The aim of the prefermenter model is to provide a tool for optimisation of prefermenter design and operation. Model assumptions, equations and parameters are detailed. The major specification for the prefermenter model is that it is relatively simple, but can still describe the effects of the main design and operating parameters on volatile fatty acid (VFA) production in prefermenters. The model is verified by comparing its prediction with experimental data presented in the literature. Predicted and measured steady-state effluent VFA, soluble COD and ammonia-N concentrations are compared for varying hydraulic and solids residence times. The correspondence between experimental data and model prediction is good.

Measuring bacterial biomass-COD in wastewater containing particulate matter

Abstract The paper describes a method to determine bacterial biomass-COD in wastewater treatment systems in the presence of particulate matter. A quantitative measure of biomass-COD concentration could greatly enhance the accuracy and reliability of wastewater treatment models that rely on the component “biomass concentration”, which is usually expressed in terms of COD. Rarely is biomass-COD determined directly, despite the existence of microbiological methods for this measurement. Here, we have used a classic microbiological method, acridine orange stain direct counting (AODC), to count the number of bacteria. The average cell volume of wastewater bacteria was used to determine a conversion factor of 20 × 10−11 mg-COD/cell for calculating bacterial biomass-COD with a fast, reliable and simple method applied to wastewater samples in the presence of particulate substrate. Bacterial biomass-COD was measured in five different wastewater treatment systems and compared to the particulate COD.

A survey of prefermenter design, operation and performance in Australia and Canada

We have compiled recent data from nine full-scale prefermenters in Australia and Canada. Using this data, we compare their design, operation and performance. The design parameters of importance are the prefermenter configuration, the fraction of total flow that is fed to the prefermenter, the prefermenter volume and the hydraulic and solids residence time (HRT and SRT). With respect to prefermenter performance, we use the rate of volatile fatty acid (VFA) production to compare prefermenter efficiency. A number of other performance indicators are also used to compare the output of the prefermenters (for example total mass of VFA produced). All side-stream prefermenters compared in this study have relatively similar rates of VFA production (typically 14 to 28 mg/L/h), which indicates that they all perform with similar efficiencies, regardless of their respective type.

Estimating VFA concentrations in prefermenters by measuring pH

Abstract We present a fundamental relationship between the pH, volatile fatty acid (VFA) concentration and alkalinity in prefermenters. Once the relationship is established, wastewater treatment plant operators can estimate on-line the VFA concentration in a prefermenter at any time from pH measurements. Parameters in the model can either be measured at some reference point for the wastewater in question, such as the prefermenter inlet, or be established by measuring the pH and VFA values at two different points (e.g. influent to and effluent from a prefermenter). Using this relationship, the VFA concentration can then be estimated for any measured pH value, without knowing the alkalinity in the system. The analysis relies on a number of simplifying assumptions, which can be relaxed at the expense of a more complicated predictive model and additional chemical analyses. We have collated pH and VFA data from four different prefermentation systems and show that the correspondence between model prediction and measured values is good. The measured pH values and VFA concentrations are related to each other via the alkalinity of the wastewater. The relationship can be used to monitor prefermenter performance (with respect to VFA production rates) from pH measurements alone, without the need to measure VFA concentrations. It can also be applied to simple or model-based control strategies for prefermentation processes.

Mathematical modelling of prefermenters—II. Model applications

This paper investigates several potential applications of a recently developed dynamic mathematical prefermenter model. Three case studies are presented. In the first case study, the model is used to analyse and optimise the performance of a prefermenter. The full-scale complete-mix prefermenter in Penrith. Australia. is used as an example. The model call predict the optimal residence time with respect to maximal mass of volatile fatty acids and soluble COD produced per day. The second study focuses on the effect of different feed types on prefermenter performance under different operating conditions. Four different feed types are defined for this case study, the main difference being their total COD concentrations. According to the simulation results, in-line prefermenters should generally be operated at a longer solids residence time than side-stream prefermenters for maximal rates of volatile fatty acids production. Optimal hydraulic retention limes predicted by the model are considerably lower than what is currently used in practice for side-stream prefermenters. In the third case study the model is used to predict the dynamic behaviour of a prefermenter after a sudden disturbance. Experimental results from a pilot-scale activated primary tank undergoing dynamic transients and the corresponding simulation results are shown. The disturbances were initiated by adding glucose to the feed and by a step change in hydraulic residence lime. The three case studies illustrate that the prefermenter model is a versatile tool for optimising the design and operation of prefermenters

The impact of microbiological tools on mathematical modelling of biological wastewater treatment

Biological systems are being used to treat an increasing range of complex wastes; domestic and industrial wastewaters containing nutrients and refractory organic compounds, soil sites and groundwater contaminated by organics, and organic solid residues. These treatment processes rely on micro-organisms and, more than ever before, must deliver higher quality outcomes at higher levels of reliability to protect the environment. At the same time, pressures to deliver cost-effective treatment have increased. The challenge for these biological treatment technologies and the associated engineering is to achieve the environmental and economic goals simultaneously. Mathematical modelling is an essential component in developing a detailed understanding of such processes, as well as design guidelines and suitable operating and control strategies. This paper provides a brief summary of the development of mathematical models for biological waste treatment systems, why they have become increasingly complex and how certain microbiological tools can provide the experimental means to validate more complex segregated and structured models of biological behaviour. With a number of specific modelling examples in the field of wastewater treatment, we illustrate the potential of these modern microbiological tools and their implications for gaining an improved understanding of biological waste treatment.