Ahmed Al-Omari

Uncoupling the solids retention times of flocs and granules in mainstream deammonification: A screen as effective out-selection tool for nitrite oxidizing bacteria

This study focused on a physical separator in the form of a screen to out-select nitrite oxidizing bacteria (NOB) for mainstream sewage treatment. This separation relied on the principle that the NOB prefer to grow in flocs, while anammox bacteria (AnAOB) reside in granules. Two types of screens (vacuum and vibrating) were tested for separating these fractions. The vibrating screen was preferred due to more moderate normal forces and additional tangential forces, better balancing retention efficiency of AnAOB granules (41% of the AnAOB activity) and washout of NOB (92% activity washout). This operation resulted in increased NOB out-selection (AerAOB/NOB ratio of 2.3) and a total nitrogen removal efficiency of 70% at influent COD/N ratio of 1.4. An effluent total nitrogen concentration <10mgN/L was achieved using this novel approach combining biological selection with physical separation, opening up the path towards energy positive sewage treatment.

Model-based evaluation of mechanisms and benefits of mainstream shortcut nitrogen removal processes

The main challenge in implementing shortcut nitrogen removal processes for mainstream wastewater treatment is the out-selection of nitrite oxidizing bacteria (NOB) to limit nitrate production. A model-based approach was utilized to simulate the impact of individual features of process control strategies to achieve NO(-)(2)-N shunt via NOB out-selection. Simulations were conducted using a two-step nitrogen removal model from the literature. Nitrogen shortcut removal processes from two case studies were modeled to illustrate the contribution of NOB out-selection mechanisms. The paper highlights a comparison between two control schemes; one was based on online measured ammonia and the other was based on a target ratio of 1 for ammonia vs. NOx (nitrate + nitrite) (AVN). Results indicated that the AVN controller possesses unique features to nitrify only that amount of nitrogen that can be denitrified, which promotes better management of incoming organics and bicarbonate for a more efficient NOB out-selection. Finally, the model was used in a scenario analysis, simulating hypothetical optimized performance of the pilot process. An estimated potential saving of 60% in carbon addition for nitrogen removal by implementing full-scale mainstream deammonification was predicted.

Impact of carbon to nitrogen ratio and aeration regime on mainstream deammonification

While deammonification of high-strength wastewater in the sludge line of sewage treatment plants has become well established, the potential cost savings spur the development of this technology for mainstream applications. This study aimed at identifying the effect of aeration and organic carbon on the deammonification process. Two 10 L sequencing bath reactors with different aeration frequencies were operated at 25°C. Real wastewater effluents from chemically enhanced primary treatment and high-rate activated sludge process were fed into the reactors with biodegradable chemical oxygen demand/nitrogen (bCOD/N) of 2.0 and 0.6, respectively. It was found that shorter aerobic solids retention time (SRT) and higher aeration frequency gave more advantages for aerobic ammonium-oxidizing bacteria (AerAOB) than nitrite oxidizing bacteria (NOB) in the system. From the kinetics study, it is shown that the affinity for oxygen is higher for NOB than for AerAOB, and higher dissolved oxygen set-point could decrease the affinity of both AerAOB and NOB communities. After 514 days of operation, it was concluded that lower organic carbon levels enhanced the activity of anoxic ammonium-oxidizing bacteria (AnAOB) over denitrifiers. As a result, the contribution of AnAOB to nitrogen removal increased from 40 to 70%. Overall, a reasonably good total removal efficiency of 66% was reached under a low bCOD/N ratio of 2.0 after adaptation.

Evaluation of the information content of long-term wastewater characteristics data in relation to activated sludge model parameters

A parameter estimation framework was used to evaluate the ability of observed data from a full-scale nitrification-denitrification bioreactor to reduce the uncertainty associated with the bio-kinetic and stoichiometric parameters of an activated sludge model (ASM). Samples collected over a period of 150 days from the effluent as well as from the reactor tanks were used. A hybrid genetic algorithm and Bayesian inference were used to perform deterministic and parameter estimations, respectively. The main goal was to assess the ability of the data to obtain reliable parameter estimates for a modified version of the ASM. The modified ASM model includes methylotrophic processes which play the main role in methanol-fed denitrification. Sensitivity analysis was also used to explain the ability of the data to provide information about each of the parameters. The results showed that the uncertainty in the estimates of the most sensitive parameters (including growth rate, decay rate, and yield coefficients) decreased with respect to the prior information.

Assessment of the endogenous respiration rate and the observed biomass yield for methanol-fed denitrifying bacteria under anoxic and aerobic conditions

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-1 for endogenous respiration rate under aerobic conditions at 20 °C, 0.102 ± 0.013 day-1 under anoxic conditions at 20 °C, and 0.214 ± 0.044 day-1 under aerobic conditions at 25 °C. Results indicated that the endogenous respiration rate of methylotrophs is 20% slower under anoxic conditions than under aerobic conditions, and there is a significant temperature dependency, with an Arrhenius coefficient of 1.10. The observed biomass yield value showed an increasing trend from approximately 0.2 to 0.6 when the starvation time increased from 0 to 10 days.

Dual substrate limitation modeling and implications for mainstream deammonification

Substrate limitation occurs frequently in wastewater treatment and knowledge about microbial behavior at limiting conditions is essential for the use of biokinetic models in system design and optimization. Monod kinetics are well-accepted for modeling growth rates when a single substrate is limiting, but several models exist for treating two or more limiting substrates simultaneously. In this study three dual limitation models (multiplicative, minimum, and Bertolazzi) were compared based on experiments using nitrite-oxidizing bacteria (limited by dissolved oxygen and nitrite) and ANaerobic AMMonia-OXidizing bacteria or Aanammox (limited by ammonium and nitrite) within mixed liquor from deammonification pilots. A deterministic likelihood-based parameter estimation followed by Bayesian inference was used to estimate model-specific parameters. The minimum model outperformed the other two by a slight margin in three separate analyses. 1) Parameters estimated using the minimum model were closest to parameters estimated from single limitation batch tests. 2) Among simulations based on each models own estimated parameters, the minimum model best described the experimental observations. 3) Among simulations based on parameters estimated from single limitation, the minimum model best described the experimental observations. The dual substrate model selected among the three studied can effect a 75% process performance variation based on simulations of a full-scale mainstream deammonification system.

Supernatant organics from anaerobic digestion after thermal hydrolysis cause direct and/or diffusional activity loss for nitritation and anammox

Treatment of sewage sludge with a thermal hydrolysis process (THP) followed by anaerobic digestion (AD) enables to boost biogas production and minimize residual sludge volumes. However, the reject water can cause inhibition to aerobic and anoxic ammonium-oxidizing bacteria (AerAOB & AnAOB), the two key microbial groups involved in the deammonification process. Firstly, a detailed investigation elucidated the impact of different organic fractions present in THP-AD return liquor on AerAOB and AnAOB activity. For AnAOB, soluble compounds linked to THP conditions and AD performance caused the main inhibition. Direct inhibition by dissolved organics was also observed for AerAOB, but could be overcome by treating the filtrate with extended aerobic or anaerobic incubation or with activated carbon. AerAOB additionally suffered from particulate and colloidal organics limiting the diffusion of substrates. This was resolved by improving the dewatering process through an optimized flocculant polymer dose and/or addition of coagulant polymer to better capture the large colloidal fraction, especially in case of unstable AD performance. Secondly, a new inhibition model for AerAOB included diffusion-limiting compounds based on the porter-equation, and achieved the best fit with the experimental data, highlighting that AerAOB were highly sensitive to large colloids. Overall, this paper for the first time provides separate identification of organic fractions within THP-AD filtrate causing differential types of inhibition. Moreover, it highlights the combined effect of the performance of THP, AD and dewatering on the downstream autotrophic nitrogen removal kinetics.

Modelling oxygen transfer using dynamic alpha factors

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, energy consumption, and process sustainability. Because organic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of considering their dynamic nature on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the correlation between the COD concentration and the α factor in activated sludge. Using the proposed model, the aeration efficiency is calculated as a function of the organic loading (i.e. COD). This results in predictions of oxygen transfer values that are more realistic than the traditional method of assuming constant α values. The model was applied to two water resource recovery facilities, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor (α) as a function of the applied oxygen demand. For the cases presented herein, the model prediction of airflow improved by 20-35% when dynamic α is used. The proposed model offers a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty.

Overcoming floc formation limitations in high-rate activated sludge systems

High-rate activated sludge (HRAS) is an essential cornerstone of the pursuit towards energy positive sewage treatment through maximizing capture of organics. The capture efficiency heavily relies on the degree of solid separation achieved in the clarifiers. Limitations in the floc formation process commonly emerge in HRAS systems, with detrimental consequences for the capture of organics. This study pinpointed and overcame floc formation limitations present in full-scale HRAS reactors. Orthokinetic flocculation tests were performed with varying shear, sludge concentration, and coagulant or flocculant addition. These were analyzed with traditional and novel settling parameters and extracellular polymeric substances (EPS) measurements. HRAS was limited by insufficient collision efficiency and occurred because the solids retention time (SRT) was short and colloid loading was high. The limitation was predominantly caused by impaired flocculation rather than coagulation. In addition, the collision efficiency limitation was driven by EPS composition (low protein over polysaccharide ratio) instead of total EPS amount. Collision efficiency limitation was successfully overcome by bio-augmenting sludge from a biological nutrient removal reactor operating at long SRT which did not show any floc formation limitations. However, this action brought up a floc strength limitation. The latter was not correlated with EPS composition, but rather EPS amount and hindered settling parameters, which determined floc morphology. With this, an analysis toolkit was proposed that will enable design engineers and operators to tackle activated solid separation challenges found in HRAS systems and maximize the recovery potential of the process.

Colloids, flocculation and carbon capture – a comprehensive plant-wide model

The implementation of carbon capture technologies such as high-rate activated sludge (HRAS) systems are gaining interests in water resource and recovery facilities (WRRFs) to minimize carbon oxidation and maximize organic carbon recovery and methane potential through biosorption of biodegradable organics into the biomass. Existing activated sludge models were developed to describe chemical oxygen demand (COD) removal in activated sludge systems operating at long solids retention times (SRT) (i.e. 3 days or longer) and fail to simulate the biological reactions at low SRT systems. A new model is developed to describe colloidal material removal and extracellular polymeric substance (EPS) generation, flocculation, and intracellular storage with the objective of extending the range of whole plant models to very short SRT systems. In this study, the model is tested against A-stage (adsorption) pilot reactor performance data and proved to match the COD and colloids removal at low SRT. The model was also tested on longer SRT systems where effluents do not contain much residual colloids, and digestion where colloids from decay processes are present.