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Wilson C.A.,Greeley and Hansen Inc. | Novak J.,Virginia Polytechnic Institute and State University | Takacs I.,Dynamita | Wett B.,University of Innsbruck | Murthy S.,District of Columbia Water and Sewer Authority
Water Research | Year: 2012

Advanced anaerobic digestion processes aimed at improving the methanization of sewage sludge may be potentially impaired by the production of inhibitory compounds (e.g. free ammonia). The result of methanogenic inhibition is relatively high effluent concentrations of acetic acid and other soluble organics, as well as reduced methane yields. An extreme example of such an advanced process is the thermal hydrolytic pretreatment of sludge prior to high solids digestion (THD). Compared to a conventional mesophilic anaerobic digestion process (MAD), THD operates in a state of constant inhibition driven by high free ammonia concentrations, and elevated pH values. As such, previous investigations of the kinetics of methanogenesis from acetic acid under uninhibited conditions do not necessarily apply well to the modeling of extreme processes such as THD. By conducting batch ammonia toxicity assays using biomass from THD and MAD reactors, we compared the response of these communities over a broad range of ammonia inhibition. For both processes, increased inhibitor concentrations resulted in a reduction of biomass growth rate (rmax = μmax.X) and a resulting decrease in the substrate half saturation coefficient (KS). These two parameters exhibited a high degree of correlation, suggesting that for a constant transport limited system, the KS was mostly a linear function of the growth rate. After correcting for reactor pH and temperature, we found that the THD and MAD biomass were both able to perform methanogenesis from acetate at high free ammonia concentrations (equivalent to 3-5 g/L total ammonia nitrogen), albeit at less than 30% of their respective maximum rates. The reduction in methane production was slightly less pronounced for the THD biomass than for MAD, suggesting that the long term exposure to ammonia had selected for a methanogenic pathway less dependent on those organisms most sensitive to ammonia inhibition (i.e. aceticlastic methanogens). © 2012 Elsevier Ltd.


Hauduc H.,National Polytechnic Institute of Toulouse | Hauduc H.,French National Institute for Agricultural Research | Hauduc H.,French National Center for Scientific Research | Takacs I.,Dynamita | And 7 more authors.
Water Research | Year: 2015

A dynamic physico-chemical model for chemical phosphorus removal in wastewater is presented as a tool to optimize chemical dosing simultaneously while ensuring compliant effluent phosphorus concentration. This new model predicts the kinetic and stoichiometric variable processes of precipitation of hydrous ferric oxides (HFO), phosphates adsorption and co-precipitation. It is combined with chemical equilibrium and physical precipitation reactions in order to model observed bulk dynamics in terms of pH. The model is calibrated and validated based on previous studies and experimental data from Smith etal. (2008) and Szabo etal. (2008) as a first step for full-plant implementation. The simulation results show that the structure of the model describes adequately the mechanisms of adsorption and co-precipitation of phosphate species onto HFO and that the model is robust under various experimental conditions. © 2015 Elsevier Ltd.


PubMed | Dynamita, CH2M HILL, Inno Water Ltd., Wilfrid Laurier University and 2 more.
Type: | Journal: Water research | Year: 2015

A dynamic physico-chemical model for chemical phosphorus removal in wastewater is presented as a tool to optimize chemical dosing simultaneously while ensuring compliant effluent phosphorus concentration. This new model predicts the kinetic and stoichiometric variable processes of precipitation of hydrous ferric oxides (HFO), phosphates adsorption and co-precipitation. It is combined with chemical equilibrium and physical precipitation reactions in order to model observed bulk dynamics in terms of pH. The model is calibrated and validated based on previous studies and experimental data from Smith et al. (2008) and Szabo et al. (2008) as a first step for full-plant implementation. The simulation results show that the structure of the model describes adequately the mechanisms of adsorption and co-precipitation of phosphate species onto HFO and that the model is robust under various experimental conditions.


Shaw A.,Black and Veatch Corporation | Shaw A.,Illinois Institute of Technology | Takacs I.,Dynamita | Pagilla K.R.,Illinois Institute of Technology | Murthy S.,DC Water
Water Research | Year: 2013

The Monod equation is often used to describe biological treatment processes and is the foundation for many activated sludge models. The Monod equation includes a "half-saturation coefficient" to describe the effect of substrate limitations on the process rate and it is customary to consider this parameter to be a constant for a given system. The purpose of this study was to develop a methodology, and its use to show that the half-saturation coefficient for denitrification is not constant but is in fact a function of the maximum denitrification rate. A 4-step procedure is developed to investigate the dependency of half-saturation coefficients on the maximum rate and two different models are used to describe this dependency: (a) an empirical linear model and (b) a deterministic model based on Fick's law of diffusion. Both models are proved better for describing denitrification kinetics than assuming a fixed KNO3 at low nitrate concentrations. The empirical model is more utilitarian whereas the model based on Fick's law has a fundamental basis that enables the intrinsic KNO3 to be estimated. In this study data was analyzed from 56 denitrification rate tests and it was found that the extant KNO3 varied between 0.07mgN/L and 1.47mgN/L (5th and 95th percentile respectively) with an average of 0.47mgN/L. In contrast to this, the intrinsic KNO3 estimated for the diffusion model was 0.01mgN/L which indicates that the extant KNO3 is greatly influenced by, and mostly describes, diffusion limitations. © 2013 Elsevier Ltd.


Friedrich M.,Ingenieurburo Friedrich | Takacs I.,Dynamita | Tranckner J.,University of Rostock
Water Research | Year: 2015

Physiological adaptation as it occurs in bacterial cells at variable environmental conditions influences characteristic properties of growth kinetics significantly. However, physiological adaptation to growth related parameters in activated sludge modelling is not yet recognised. Consequently these parameters are regarded to be constant. To investigate physiological adaptation in activated sludge the endogenous respiration in an aerobic degradation batch experiment and simultaneous to that the maximum possible respiration in an aerobic growth batch experiment was measured. The activated sludge samples were taken from full scale wastewater treatment plants with different sludge retention times (SRTs). It could be shown that the low SRT sludge adapts by growth optimisation (high maximum growth rate and high decay rate) to its particular environment where a high SRT sludge adapts by survival optimization (low maximum growth rate and low decay rate). Thereby, both the maximum specific growth rate and the decay rate vary in the same pattern and are strongly correlated to each other. To describe the physiological state of mixed cultures like activated sludge quantitatively a physiological state factor (PSF) is proposed as the ratio of the maximum specific growth rate and the decay rate. The PSF can be expressed as an exponential function with respect to the SRT. © 2015 Elsevier Ltd.


Friedrich M.,Ingenieurburo Friedrich | Takacs I.,Dynamita | Tranckner J.,University of Rostock
Water Environment Research | Year: 2016

In current process models activated sludge consists of biodegradable and unbiodegradable organic fractions. Recent evidence suggests that this approach may not be accurate because some of this "unbiodegradable" material may indeed be degradable. To improve sludge production predictions, it is important to know to what extent the "unbiodegradable" organic fraction is degradable. Assuming that volatile suspended solids (VSS) is a measure of the sum of biodegradable and unbiodegradable organic solids and the integral of the oxygen uptake rate (OUR) is representative of the biodegradable organics, the combination of these measurements can be used to predict the change of unbiodegradable organic solids within an aerobic digestion batch experiment. This procedure was used to estimate degradation rates of "unbiodegradable" VSS between 0.006 to 0.029 d-1. The advantage of the proposed method is that the degradation rate can be determined directly based onmeasurements and relies on a limited number of assumptions.


In current activated sludge models aerobic degradation, resulting in loss of activity and mass of activated sludge is expressed with only one process called decay. The kinetics of this process is regarded to be first order and constant with respect to the loading conditions. In this work twelve aerobic digestion batch experiments were conducted for the activated sludge of seven different water resource recovery facilities (WRRFs). An analysis of the obtained respirograms shows three clearly distinguishable phases. The first phase is assumed to be due to the degradation of stored material (XSTOR) and active biomass simultaneously. The second phase is exclusively due to the degradation of active biomass that is regarded to consist mainly of ordinary heterotrophic biomass (XOHO). The first order decay rate is slower than the degradation rate in phase 1 and varies between samples. The decay rate correlates with the activity of the activated sludge expressed as the ratio of initial heterotrophic OUR and the initial organic fraction XORG of the activated sludge. This second phase was detectable until day 5 of most of the experiments. After that time within phase 3 the OUR decrease slows down and the OUR even increased for short intervals. This behaviour is thought to be due to the activity of higher organisms and the adaptation of microorganisms to starvation. © 2013 Elsevier Ltd.


PubMed | University of Rostock, Dynamita and Ingenieurburo Friedrich
Type: | Journal: Water research | Year: 2015

Physiological adaptation as it occurs in bacterial cells at variable environmental conditions influences characteristic properties of growth kinetics significantly. However, physiological adaptation to growth related parameters in activated sludge modelling is not yet recognised. Consequently these parameters are regarded to be constant. To investigate physiological adaptation in activated sludge the endogenous respiration in an aerobic degradation batch experiment and simultaneous to that the maximum possible respiration in an aerobic growth batch experiment was measured. The activated sludge samples were taken from full scale wastewater treatment plants with different sludge retention times (SRTs). It could be shown that the low SRT sludge adapts by growth optimisation (high maximum growth rate and high decay rate) to its particular environment where a high SRT sludge adapts by survival optimization (low maximum growth rate and low decay rate). Thereby, both the maximum specific growth rate and the decay rate vary in the same pattern and are strongly correlated to each other. To describe the physiological state of mixed cultures like activated sludge quantitatively a physiological state factor (PSF) is proposed as the ratio of the maximum specific growth rate and the decay rate. The PSF can be expressed as an exponential function with respect to the SRT.


Sharifi S.,Catholic University of America | Sharifi S.,University of Birmingham | Murthy S.,DC Water and Sewer Authority | Takacs I.,Dynamita | Massoudieh A.,Catholic University of America
Water Research | Year: 2014

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. © 2013 Elsevier Ltd.


PubMed | DC Water, Catholic University of America and Dynamita
Type: Journal Article | Journal: Water science and technology : a journal of the International Association on Water Pollution Research | Year: 2017

In this study, the endogenous respiration rate and the observed biomass yield of denitrifying methylotrophic biomass were estimated through measuring changes in denitrification rates (DNR) as a result of maintaining the biomass under methanol deprived conditions. For this purpose, activated sludge biomass from a full-scale wastewater treatment plant was kept in 10-L batch reactors for 8 days under fully aerobic and anoxic conditions at 20 C without methanol addition. To investigate temperature effects, another biomass sample was placed under starvation conditions over a period of 10 days under aerobic conditions at 25 C. A series of secondary batch tests were conducted to measure DNR and observed biomass yields. The decline in DNR over the starvation period was used as a surrogate to biomass decay rate in order to infer the endogenous respiration rates of the methylotrophs. The regression analysis on the declining DNR data shows 95% confidence intervals of 0.130 0.017 day

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