Department of Environmental Engineering

An extremely thermophilic, xylanolytic, spore-forming and strictly anaerobic bacterium, strain DTU01T, was isolated from a continuously stirred tank reactor fed with xylose and household waste. Cells stained Gram-negative and were rod-shaped (0.5–2 µm in length). Spores were terminal with a diameter of approximately 0.5 µm. Optimal growth occurred at 70 °C and pH 7, with a maximum growth rate of 0.1 h−1. DNA G+C content was 34.2 mol%. Strain DTU01Tcould ferment arabinose, cellobiose, fructose, galactose, glucose, lactose, mannitol, mannose, melibiose, pectin, starch, sucrose, xylan, yeast extract and xylose, but not cellulose, Avicel, inositol, inulin, glycerol, rhamnose, acetate, lactate, ethanol, butanol or peptone. Ethanol was the major fermentation product and a maximum yield of 1.39 mol ethanol per mol xylose was achieved when sulfite was added to the cultivation medium. Thiosulfate, but not sulfate, nitrate or nitrite, could be used as electron acceptor. On the basis of 16S rR...

An extreme thermophilic ethanol-producing strain was isolated from an ethanol high-yielding mixed culture, originally isolated from a hydrogen producing reactor operated at 70 W C. Ethanol yields were assessed with increasing concentrations of xylose, up to 20 g/l. The ability of the strain to grow without nutrient addition (yeast extract, peptone and vitamins) was also assessed. The maximum ethanol yield achieved was 1.28 mol ethanol /mol xylose consumed (77% of the theoretical yield), at 2 g/l of initial xylose concentration. The isolate was able to grow and produce ethanol as the main fermentation product under most of the conditions tested, including in media lacking vitamins, peptone and yeast extract. The results indicate that this new organism is a promising candidate for the development of a second generation bio-ethanol production process.

I de senere år er interessen for at spare på grundvandsressourcen steget. Der er også et ønske blandt myndigheder og græsrødder om at finde metoder til i større omfang at håndtere spildevand lokalt. Det er derfor af stor interesse at undersøge muligheder for at f. eks. bruge gråt spildevand til toiletskyl og tøjvask, og dermed erstatte den del af drikkevandet, som ikke anvendes til drikkevandsformål med sekunda vand og samtidig undgå centraliseret rensning af en del af spildevandet.

The Activated Sludge Model No. 2d (ASM2d) presents a model for biological phosphorus removal with simultaneous nitrification-denitrification in activated sludge systems. ASM2d is based on ASM2 and is expanded to include the denitrifying activity of the phosphorus accumulating ...

In activated sludge processes an increased sludge age is associated with a decreased sludge production. This phenomenon is generally interpreted as a result of endogenous respiration processes. In the activated sludge models cell lysis (or decay) is incorporated. The lysis is ...

The paper examines the present trends within wastewater handling and treatment. The trend is towards the extremes, either local low-tech treatment or centralized advanced treatment plants. The composition of the wastewater will change and it will be regarded as a ...

The Activated Sludge Model No. 2 is introduced as a further development of Activated Sludge Model No. 1. Model No. 2 introduces phosphorus accumulating organisms (PAO) and allows us to simulate the behaviour of biological nutrient removal activated sludge systems. ...

In this study, the metabolism of glycogen storage and consumption in mixed cultures under aerobic conditions is described. The experimental results are used to calibrate a metabolic model, which as sole stoichiometric variables has the efficiency of oxidative phosphorylation (␦) and maintenance requirement in units of adenosine triphosphate (m ATP ). Using the experimental data and values from the literature we show that ␦ and m ATP are strongly coupled and that the values determined for glycogen and poly-␤-hydroxybutyrate (PHB) metabolism are similar. We also demonstrate that storage of glycogen and subsequent growth occur without significant loss of energy, as compared with direct growth on glucose. For kinetic modeling, Monod kinetics is used most commonly in activated sludge models to describe the rate of microbial transformation. Monod kinetics, however, does not provide a good description of the data obtained. Second-order kinetics gives a better description of the rate of glycogen degradation. Formation and consumption of glycogen appears to be much faster than for PHB.

This review paper focuses on modelling of wastewater treatment plants (WWTP). White-box modelling is widely applied in this field, with learning, design and process optimisation as the main applications. The introduction of the ASM model family by the IWA task group was of great importance, providing researchers and practitioners with a standardised set of basis models. This paper introduces the nowadays most frequently used white-box models for description of biological nitrogen and phosphorus removal activated sludge processes. These models are mainly applicable to municipal wastewater systems, but can be adapted easily to specific situations such as the presence of industrial wastewater. Some of the main model assumptions are highlighted, and their implications for practical model application are discussed. A step-wise procedure leads from the model purpose definition to a calibrated WWTP model. Important steps in the procedure are: model purpose definition, model selection, data collection, data reconciliation, calibration of the model parameters and model unfalsification. The model purpose, defined at the beginning of the procedure, influences the model selection, the data collection and the model calibration. In the model calibration a process engineering approach, i.e. based on understanding of the process and the model structure, is needed. A calibrated WWTP model, the result of an iterative procedure, can usually be obtained by only modifying few model parameters, using the default parameter sets as a starting point. Black-box, stochastic grey-box and hybrid models are useful in WWTP applications for prediction of the influent load, for estimation of biomass activities and effluent quality parameters. These modelling methodologies thus complement the process knowledge included in white-box models with predictions based on data in areas where the white-box model assumptions are not valid or where white-box models do not provide accurate predictions. Artificial intelligence (AI) covers a large spectrum of methods, and many of them have been applied in applications related to WWTPs. AI methodologies and white-box models can interact in many ways; supervisory control systems for WWTPs are one evident application. Modular agent-based systems combining several AI and modelling methods provide a great potential. In these systems, AI methods on one hand can maximise the knowledge extracted from data and operator experience, and subsequently apply this knowledge to improve WWTP control. White-box models on the other hand allow evaluating scenarios based on the available process knowledge about the WWTP. A white-box model calibration tool, an AI based WWTP design tool and a knowledge representation tool in the WWTP domain are other potential applications where fruitful interactions between AI methods and white-box models could be developed. 

Reliable performance evaluation of wastewater treatment plants (WWTPs) can be done by simulating the plant behavior over a wide range of influent disturbances, including series of rain events with different intensity and duration, seasonal temperature variations, holiday effects, etc. Such simulation-based WWTP performance evaluations are in practice limited by the long simulation time of the mechanistic WWTP models. By moderate simplification (avoiding big losses in prediction accuracy) of the mechanistic WWTP model only a limited reduction of the simulation time can be achieved. The approach proposed in this paper combines an influent disturbance generator with a mechanistic WWTP model for generating a limited sequence of training data (4 months of dynamic data). An artificial neural network (ANN) is then trained on the available WWTP input-output data, and is subsequently used to simulate the remainder of the influent time series (20 years of dynamic data) generated with the influent disturbance generator. It is demonstrated that the ANN reduces simulation time by a factor of 36, even when including the time needed for the generation of training data and for ANN training. For repeated integrated urban wastewater system simulations that do not require repeated training of the ANN, the ANN reduces simulation time by a factor of 1300 compared to the mechanistic model. ANN prediction of effluent ammonium, BOD 5 and total suspended solids was good when compared to mechanistic WWTP model predictions, whereas prediction of effluent COD and total nitrogen concentrations was a bit less satisfactory. With correlation coefficients R 2 > 0.95 and prediction errors lower than 10%, the accuracy of the ANN is sufficient for applications in simulation-based WWTP design and simulation of integrated urban wastewater systems, especially when taking into account the uncertainties related to mechanistic WWTP modeling.

An experimental procedure was developed for the respirometric determination of bacterial storage yield as defined in the Activated Sludge Model No. 3. The proposed approach is based on the oxygen utilization rate ͑OUR͒ profile obtained from a batch test and correlates the area under the OUR curve to the amount of oxygen associated with substrate storage. Model simulation was used to evaluate the procedure for different initial experimental conditions. The procedure was tested on acetate. The same storage yield value of 0.76 gCOD/gCOD was calculated for two experiments, starting with different F/M ratios of 0.12 and 0.64 gCOD/g cellCOD.

Quantitative fluorescence in situ hybridization (FISH) and the combination of FISH with microautoradiography (MAR) were used in order to study the long-term population dynamics (2.5 years) and the in situ physiology in two parallel activated sludge pilot systems with enhanced biological phosphorus removal (EBPR). The two systems received the same influent wastewater, but were differently operated (with and without nitrogen removal, respectively). Both systems showed a significant P removal that increased when different substrates (phosphorus (P), acetate and glucose, respectively) were added to the influent wastewater. Rhodocyclus-related bacteria were present in both systems in significant numbers (ranging from 4 to 28%) throughout the whole period. This supports the hypothesis that these bacteria occur in significant numbers in different types of well-operating EBPR activated sludge processes. However, we observed a lower correlation (<0.5) for the amount of Rhodocyclus-related bacteria to the P content in activated sludge than previous studies (>0.9). The Actinobacteria were the only additional group of bacteria which showed a similar degree of correlation to the P content in activated sludge as the Rhodocyclus-related bacteria -but only for the system without nitrogen removal. Significant amounts (≤ 12%) of glycogen-accumulating bacteria (GAOs) were detected in the system with nitrogen removal (but not in the other system), but had no, in contrast to previous observations, apparent negative effect on the overall EBPR performance. FISH-MAR indicated that a significant part of the Betaproteobacteria (part of them identified as Rhodocyclus-related bacteria) as well as the Actinobacteria were able to take up 33 P i, [ 3 H]-acetate and [ 3 H]-glucose under anaerobic-aerobic conditions. The contribution of anoxic 33 P i uptake under alternating anaerobic-anoxic conditions was significantly lower. Interestingly, not all Rhodocyclus-related bacteria showed uptake of these three radioactive substrates. This may be due to differences in metabolic state, physiological potential or genotype, not detectable by the present probe set for Rhodocyclus-related bacteria. Comparison of the 33 P i , [ 3 H]-acetate and [ 3 H]-glucose uptake by activated sludge after different fixation and incubation procedures showed that a part of the observed 33 P i uptake may have been caused by a combination of a biological and chemical or biologically induced chemical P adsorption.

Respirometric analysis of domestic sewage together with textile, dairy, meat processing, tannery and confectionery wastewaters were carried out for the experimental assessment of the readily biodegradable COD. The accuracy and the reliability of the experimental procedure was tested using synthetic sewage and different wastewater mixtures. The merit of OUR and NUR measurements was investigated in parallel aerobic and anoxic batch reactors. The OUR data was analysed with specific emphasis to identify the lower plateau associated with the hydrolysis of slowly biodegradable substrate. The NUR data was corrected for nitrite formation to provide an accurate account of electron aeceptor consumption. The respirometric procedure and especially the effect of the initial substrate to biomass F/M (CTI/XTI) ratio was investigated using model simulation of the respirometry curve together with the collected experimental data.

A Model Parameter estimation Wastewater Xenobiotic organic compound a b s t r a c t The perspective of this work is to develop a model, which can be used to better understand and optimize wastewater treatment plants that are able to remove xenobiotic organic compounds (XOCs) in combination with removal of traditional pollutants. Results from dynamic experiments conducted with the endocrine disrupting XOC bisphenol-A (BPA) in an activated sludge process with real wastewater were used to hypothesize an ASM-based process model including aerobic growth of a specific BPA-degrading microorganism and sorption of BPA to sludge. A parameter estimation method was developed, which simultaneously utilizes steady-state background concentrations and dynamic step response data, as well as conceptual simplifications of the plant configuration. Validation results show that biodegradation of BPA is sensitive to operational conditions before and during the experiment and that the proposed model structure is capable of capturing important characteristics of the observed BPA removal, thus increasing the potential for generalizing knowledge obtained from plant specific experiments. (E. Lindblom). A v a i l a b l e a t w w w . s c i e n c e d i r e c t . c o m j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / w a t r e s 0043-1354/$ -see front matter ª

Wastewater from the fertiliser industry is characterised by high chloride concentration, normally varying between 60 and 76 g/ l. Experiments with biological denitrification were performed in laboratory-scale 'fill and draw' reactors with synthetic fertiliser wastewater, with chloride concentrations up to 96.7 g Cl/l at 37°C; the pH was controlled in the range 6.8 to 7.2. Potassium acetate was added as carbon source for the suspended cultures. The results of the experiments showed that biological denitrification was feasible at the extreme environmental conditions prevailing in undiluted fertiliser wastewater. However, the extreme conditions affected the denitrification rates. The volumetric rates were reduced by a factor of ten between chloride levels of 4.8 to 96.7 g/l. The results from the performed tests can also be applied to other wastewaters with similar characteristics as that of the fertiliser industry, i.e. with high salinity. As an example, the pharmaceutical and aquacultural industries can be mentioned.

The U.S. EPA QUAL2 model is currently the standard for river water quality modelling. While QUAL2 is adequate for the regulatory situation for which it was developed (the U.S. wasteload allocation process), there is a need for a more comprehensive framework for research and teaching. Moreover, QUAL2 and similar models do not address a number of practical problems such as stormwater flow events, nonpoint source pollution, and transient streamflow. Limitations in model formulation affect the ability to close mass balances, to represent sessile bacteria and other benthic processes, and to achieve robust model calibration. Mass balance problems aris e from failure to account for mass in the sediment as well as in the water column and due to the fundamental imprecision of BOD as a state variable.