Water Resource Recovery Facilities Research Articles

Solids Residence Time Impacts Carbon Dynamics and Bioenergy Feedstock Potential in Phototrophic Wastewater Treatment Systems.

The use of wastewater-grown microalgae has the potential to reduce the cost of algae-derived biofuels while simultaneously advancing nutrient recovery at water resource recovery facilities (WRRFs). However, a significant barrier has been the low yield and high protein content of phototrophic biomass. Here, we examine the use of solids residence time (SRT) as a selective pressure in driving biochemical composition, yield, biofuel production, and WRRF nutrient management cost. We cultivated mixed phototrophic communities in controlled, laboratory-scale photobioreactors on the local WRRF secondary effluent to link SRT with biochemical composition and techno-economic analysis to yield insights into biomass composition and downstream processing effects on minimum fuel selling price. SRT significantly impacted biochemical composition, with total and dynamic carbohydrates the highest at low SRT (total carbohydrates being 0.60 and 0.32 mg-carbohydrate·mg-protein-1 at SRT 5 and 15 days, respectively). However, there were distinct differences between extant, steady-state performance and intrinsic potential, and longer SRT communities were able to accumulate significant fractions (51% on an ash-free dry weight basis, AFDW %) of carbohydrate reserves under nutrient starvation. Overall, hydrothermal liquefaction (HTL) was found to be more suitable than lipid extraction for hydrotreating (LEH) and combined algal processing (CAP) for conversion of biomass to fuels, but LEH and CAP became more competitive when intrinsic carbon storage potential was realized. The results suggest that the use of algae for nutrient recovery could reduce the nutrient management cost at WRRFs through revenue from algal biofuels, with HTL resulting in a net revenue.

Digital solutions for continued operation of WRRFs during pandemics and other interruptions

This paper includes survey results from 17 full‐scale water resource recovery facilities (WRRFs) to explore their technical, operational, maintenance, and management‐related challenges during COVID‐19. Based on the survey results, limited monitoring and maintenance of instrumentation and sensors are among the critical factors during the pandemic which resulted in poor data quality in several WRRFs. Due to lockdown of cities and countries, most of the facilities observed interruptions of chemical supply frequency which impacted the treatment process involving chemical additions. Some plants observed influent flow reduction and illicit discharges from industrial wastewater which eventually affected the biological treatment processes. Delays in equipment maintenance also increased the operational and maintenance cost. Most of the plants reported that new set of personnel management rules during pandemic created difficulties in scheduling operator's shifts which directly hampered the plant operations. All the plant operators mentioned that automation, instrumentation, and sensor applications could help plant operations more efficiently while working remotely during pandemic. To handle emergency circumstances including pandemic, this paper also highlights resources and critical factors for emergency responses, preparedness, resiliency, and mitigation that can be adopted by WRRFs.

Advanced machine learning application for odor and corrosion control at a water resource recovery facility.

The objective of this study was to develop a machine learning (ML) application to determine the optimal dosage of sodium hypochlorite (NaOCl) to curtail corrosion and odor by H2 S in the headworks of a water resource recovery facility (WRRF) without overly consuming volatile fatty acids (VFAs) that are essential for the enhanced biological phosphorus removal. Given the highly diverse datasets available, three subproblems were formulated, and three cascaded ML modules were developed accordingly. The final ML models, chosen based on performance, were able to predict various targeted variables. More specifically, in Module 1, a recurrent neural network (RNN) was designed to predict wastewater characteristics. In Module 2, a random forest (RF) classifier and a support vector machine (SVM) classifier were built with the information from Module 1 along with other datasets to predict the concentrations of VFAs and H2 S, respectively. Finally, in Module 3, with the information obtained from Module 2, another RF classifier was developed to predict NaOCl dosage to reduce H2 S but keeping VFAs within the target range. These efforts are relevant and informative for WRRFs that are considering developing Intelligent Water Systems to predict the wastewater characteristics to make operational improvements. PRACTITIONER POINTS: A recurrent neural network (RNN) using long short-term memory (LSTM) successfully predicted influent wastewater parameters. A support vector machine classifier predicted hydrogen sulfide (H2 S) with 97.6% accuracy. The concentration of VFAs, an important parameter in EBPR, was predicted using a random forest classifier with 93.4% accuracy. The optimal NaOCl dosage for H2 S control can be predicted with a random forest classifier using H2 S, VFAs, and flow.

Phosphorus and carbon solubilization strategies for wastewater sludge valorisation

Phosphorus and carbon solubilisation from wastewater sludges is a difficult task due to specific sludge characteristics and low biodegradability of sludges. This work evaluates operational strategies to solubilise phosphorus and/or carbon from different municipal sludges in a bioacidification reactor operated at low sludge retention time (SRT) compared to conventional digestors, with the objective of valorising sludge and recovering resources onsite of a water resource recovery facility (WRRF). The individual impact of three municipal sludges, three organic loading rates (OLR), two SRTs, two temperatures and thermal hydrolysis pre-treatment was assessed through a well-designed experimental methodology. Bioacidification provided a maximum 79% of PO43--P/Ptot and 29% of CODsol/CODtot solubilisation ratios, which was an increase of approximately 60% and 26%, respectively, compared to a non bioacidified sludge. Similar performance was achieved for the three different sludges and OLRs used in this study under SRT of 4 days and 35 °C. Kinetic tests elucidated that lower SRT (2 days) and temperature (20 °C) negatively impacted P release due to biological fermentation decrease. Iron and polyphosphate release was impacted by present microbial community, while calcium release was more dependent on pH. Organic phosphorus, nitrogen and carbon solubilisation was limited by low sludge hydrolysis and increased only after a thermal-alkaline sludge hydrolysis pre-treatment (pH 9, 80 °C for 1 h) was combined with the bioacidification. This study demonstrates the high potential of the bioacidification process to valorise sludge and provides recommendations for its implementation onsite based on the individual requirements of each WRRF.

From wastewater treatment to water resource recovery: Environmental and economic impacts of full-scale implementation

To reduce greenhouse gas emissions and promote resource recovery, many wastewater treatment operators are retrofitting existing plants to implement new technologies for energy, nutrient and carbon recovery.In literature, there is a lack of studies that can unfold the potential environmental and economic impacts of the transition that wastewater utilities are undertaking to transform their treatment plants to water resource recovery facilities (WRRFs). When existing, literature studies are mostly based on simulations rather than real plant data and pilot-scale results. This study combines life cycle assessment and economic evaluations to quantify the environmental and economic impacts of retrofitting an existing wastewater treatment plant (WWTP), which already implements energy recovery, into a full-scale WRRF with a series of novel technologies, the majority of which are already implemented full-scale or tested through pilot-scales. We evaluate five technology alternatives against the current performance of the WWTP: real-time N2O control, biological biogas upgrading coupled with power-to-hydrogen, phosphorus recovery, pre-filtration carbon harvest and enhanced nitrogen removal. Our results show that real-time N2O control, biological biogas upgrading and pre-filtration lead to a decrease in climate change and fossil resource depletion impacts. The implementation of the real-time measurement and control of N2O achieved the highest reduction in direct CO2-eq emissions (-35%), with no significant impacts in other environmental categories. Biological biogas upgrading contributed to counterbalancing direct and indirect climate change impacts by substituting natural gas consumption and production. Pre-filtration increased climate change reduction by 13%, while it increased impacts in other categories. Enhanced sidestream nitrogen removal increased climate change impacts by 12%, but decreased marine eutrophication impacts by 14%. The reserve base resource depletion impacts, however, were the highest in the plant configurations implementing biological biogas upgrading coupled with power-to-hydrogen. Environmental improvements generated economic costs for all alternatives except for real-time N2O control. The results expose possible environmental and economic trade-offs and hotspots of the journey that large wastewater treatment plants will undertake in transitioning into resource recovery facilities in the coming years.

Fate of selected organic micropollutants during anaerobic sludge digestion

Organic micropollutants are incompletely removed from wastewater in Water Resource Recovery Facilities using conventional methods and can therefore enter the anaerobic sludge treatment together with primary and secondary sludge. This review compiles literature data on the fate of selected micropollutants (Carbamazepine [CBZ], Diclofenac [DCF], Ibuprofen [IBP], Sulfamethoxazole [SMX], and Triclosan [TCS]) during anaerobic sludge treatment and how the fate is affected by chemical properties, phase distribution and operating conditions. CBZ was found to be persistent to anaerobic degradation in most studies, with some exceptions reporting a degradation efficiency of 60%. Removal efficiencies for DCF, IBP, and TCS varied widely (from no to [very] high removal). For SMX, most studies reported a removal above 80%. A correlation was found between the fate during anaerobic digestion and physicochemical properties (hydrophobicity and molecular structure). Sorption to sludge, affected in some cases by pH changes during digestion, is suggested to reduce bioavailability. IBP and TCS were mainly present in the liquid phase or solid phase, respectively, CBZ and DCF were present in similar proportions in both phases, while statements were contradictory for SMX. Parameters such as temperature and sludge age did not significantly influence the fate of investigated micropollutants during anaerobic digestion. PRACTITIONER POINTS: Most studies report no significant removal of CBZ during anaerobic sludge digestion. Removal efficiencies of DCF, IBP, and TCS vary from study to study between no removal and high or very high removal. Considering such heterogeneous removal efficiencies, it is recommended to conduct digestion trials to find out in which range the values will be for a specific sludge. SMX is very highly removed during anaerobic digestion in most studies. Parameters such as temperature and SRT do not significantly influence the fate of the five investigated micropollutants. Hydrophobicity, which has some effect on the liquid/solid phase distribution of micropollutants, and molecular structure influence the removal efficiencies.

Plant-wide investigation of sulfur flows in a water resource recovery facility (WRRF)

Even though sulfur compounds and their transformations may strongly affect wastewater treatment processes, their importance in water resource recovery facilities (WRRF) operation remains quite unexplored, notably when it comes to full-scale and plant-wide characterization. This contribution presents a first-of-a-kind, plant-wide quantification of total sulfur mass flows for all water and sludge streams in a full-scale WRRF. Because of its important impact on (post-treatment) process operation, the gaseous emission of sulfur as hydrogen sulfide (H2S) was also included, thus enabling a comprehensive evaluation of sulfur flows. Data availability and quality were optimized by experimental design and data reconciliation, which were applied for the first time to total sulfur flows. Total sulfur flows were successfully balanced over individual process treatment units as well as the plant-wide system with only minor variation to their original values, confirming that total sulfur is a conservative quantity. The two-stage anaerobic digestion with intermediate thermal hydrolysis led to a decreased sulfur content of dewatered sludge (by 36%). Higher (gaseous) H2S emissions were observed in the second-stage digester (42% of total emission) than in the first one, suggesting an impact of thermal treatment on the production of H2S. While the majority of sulfur mass flow from the influent left the plant through the treated effluent (> 95%), the sulfur discharge through dewatered sludge and gaseous emissions are critical. The latter are indeed responsible for odour nuisance, lower biogas quality, SO2 emissions upon sludge combustion and corrosion effects.

Transformation Kinetics of Phosphorus and Nitrogen in Iron-Rich Sewage Sludges during Hydrothermal Treatment and Recovery of Nutrients from Process Water

Hydrothermal treatment (HT) is an emerging technique for sustainable sewage sludge management and resource recovery. Many sludges are rich in iron (Fe) due to the common addition of Fe salts in water resource recovery facilities. To develop guidance for reaction conditions targeting nutrient recovery, this study systematically investigated the influence of HT temperature, treatment time, and sludge source on the dynamic speciation evolution of phosphorus (P) and nitrogen (N) during HT of Fe-rich sewage sludge. Complementary chemical extraction and X-ray spectroscopy analyses were conducted to characterize the treatment products. For the sludge mixture (a blend of primary and waste activated sludges), P speciation did not change significantly within 4.5 h at 125 °C HT, while soluble and labile P was converted into insoluble P over time at 175 and 225 °C HT. Strengite (FePO4·2H2O) preferentially formed in the hydrochars with increasing treatment temperature and/or time, whereas 125 °C HT within 1.5 h favored the formation of vivianite (Fe3(PO4)2·8H2O). Organic P was completely decomposed into orthophosphate when the HT temperature reached up to 175 °C. Pyrrole-N was enriched in the hydrochars. Similar reaction pathways were observed during HT of anaerobically digested sludge, though some minor differences in Fe-associated P and organic P were observed. Meanwhile, HT of the two sludges released orthophosphate and ammonia into the process waters at 175 and 225 °C, which can be recovered by a sequential process involving struvite (MgNH4PO4·6H2O) precipitation and air stripping. This study provides new insights into the transformation of P and N during HT of Fe-rich sludges as well as a modular design for maximum P and N recovery from the treatment products.

A framework for model-based assessment of resilience in water resource recovery facilities against power outage

Current practice to enhance resilience in Water Resource Recovery Facilities (WRRFs) is to ensure redundancy or back-up for most critical equipment (e.g. pumps or blowers). Model-based assessment allows evaluation of different strategies for quantitatively and efficiently enhancing resilience and justifying the allocation of resources. The goal of this study is to provide guidance for the development of tailored deterministic models of full-scale WRRFs. A framework for model-based resilience assessment is proposed that provides guidance on data collection, model selection, model calibration and scenario analysis. The framework is embedded into the Good Modeling Practice (GMP) Unified Protocol, providing a new application for resilience assessment and an initial set of stressors for WRRFs. The usefulness of the framework is illustrated through a resilience assessment of the WRRF of Girona against power outage. Results show that, for the Girona facility, limited energy back-up can cause non-compliance of WRRF discharge limits in the case of a blower power shut-down of 6 h, and around 12 h when the blower shut-down is also combined with a shut-down of the recirculation pumps. The best option to enhance resilience would be increasing the power back-up by 218%, which allows the plant to run with recirculation pumps and blowers at minimum capacity. In such a case, resilience can be further enhanced by manipulating the air supply valves to optimise the air distribution, to balance oxygen needs in each reactor with the overall system pressure. We conclude that, with industry consensus on what is considered an acceptable level of resilience, a framework for resilience assessment would be a useful tool to enhance the resilience of our current water infrastructure. Further research is needed to establish if the permit structure should accommodate levels sof functionality to account for stress events.

Soft Sensing for On-Line Fault Detection of Ammonium Sensors in Water Resource Recovery Facilities.

The increasing demand for online sensors applied to advanced control strategies in water resource recovery facilities has resulted in the increasing investigation of fault-detection methods to improve the reliability of sensors installed in harsh environments. The study herein focuses on the fault detection of ammonium sensors, especially for effluent monitoring, given their potential in ammonium-based aeration control applications. An artificial neural network model was built to predict the ammonium content in the effluent by employing the information from five other sensors installed in the activated sludge tank: NH4+, pH, ORP, DO, and TSS. The residual between the model prediction and the effluent ammonium sensor signal was utilized in a fault-detection mechanism based on principal component analysis and Shewhart monitoring charts. In contrast to previous studies, the present work utilizes typical faults collected from a 1 year historic dataset of an actual sensor setup. Treatment process anomalies, calibration bias faults, and fouling drifts were the most common issues identified from the historic dataset, and they were promptly identified by the proposed fault-detection methodology. Once a fault is detected, the model prediction can be actively used in place of the sensor for process control without affecting the treatment process by utilizing faulty datasets.

Carbonaceous vs. total biochemical oxygen demand as a basis for WRRF design and performance monitoring.

The standard 5-day biochemical oxygen demand (BOD5 ) measurement of water quality is used widely as a design parameter for water resource recovery facilities (WRRFs). This measure usually includes a component of nitrogenous oxygen demand (NOD) that can cause oversizing of biological processes and under-evaluation of process capacity. Carbonaceous BOD (CBOD5 ) more closely represents oxygen demand associated with biodegradation of organic constituents of a wastewater than does BOD5 and therefore should be used as a basis for sizing aerobic treatment processes. Nitrogenous oxygen demand or reduced nitrogen content should be used as a loading and process performance parameter for nitrogen removal processes. PRACTITIONER POINTS: Oxygen demand for aerobic biodegradation reactions typically is divided into two major categories-carbonaceous biochemical oxygen demand (CBOD) and nitrogenous oxygen demand (NOD). Use of BOD5 as a design parameter and CBOD5 as an effluent water quality parameter distorts the true performance and loading rate capacity of a treatment plant. Carbonaceous BOD (CBOD5 ) more closely represents oxygen demand associated with biodegradation of organic constituents of a wastewater than does BOD5 and therefore should be used as a basis for sizing and evaluating the performance of aerobic treatment processes. Nitrogenous oxygen demand or reduced nitrogen content should be used as a loading and process performance parameter for nitrogen removal processes.

A method-of-lines formulation for a model of reactive settling in tanks with varying cross-sectional area

Abstract Reactive settling denotes the process of sedimentation of small solid particles dispersed in a viscous fluid with simultaneous reactions between the components that constitute the solid and liquid phases. This process is of particular importance for the simulation and control of secondary settling tanks (SSTs) in water resource recovery facilities (WRRFs), formerly known as wastewater treatment plants. A spatially 1D model of reactive settling in an SST is formulated by combining a mechanistic model of sedimentation with compression with a model of biokinetic reactions. In addition, the cross-sectional area of the tank is allowed to vary as a function of height. The final model is a system of strongly degenerate parabolic, nonlinear partial differential equations that include discontinuous coefficients to describe the feed, underflow and overflow mechanisms, as well as singular source terms that model the feed mechanism. A finite difference scheme for the final model is developed by first deriving a method-of-lines formulation (discrete in space, continuous in time) and then passing to a fully discrete scheme by a time discretization. The advantage of this formulation is its compatibility with common practice in development of software for WRRFs. The main mathematical result is an invariant-region property, which implies that physically relevant numerical solutions are produced. Simulations of denitrification in SSTs in WRRFs illustrate the model and its discretization.

Design of the Reactor and the Clarifier of an Activated Sludge Water Resource Recovery Facility, AS WRRF

Metcalf & Eddy´s formula that gives the mixed liquor volatile suspended solids, MLVSS= Xv, produced in the aeration tank, from hereon called Reactor, will be used giving it the parameters for AS WRRFs shown in Table 10-5 of its 3rd Edition placing values of hydraulic retention time, HRT, in the first column and values of solids retention time, SRT, in the first row. Many solutions are found that solve the formula. Some will be studied, using the flux graph, to check if they comply with other requirements as moderate volume, V, of Reactor, small surface, S, of Clarifier, ample range of return flow percentages, R, and admissible relation F/M. A solution will then be chosen.

Dynamic load shifting for the abatement of GHG emissions, power demand, energy use, and costs in metropolitan hybrid wastewater treatment systems

The installation of satellite water resource recovery facilities (WRRFs) has strengthened the ability to provide cheap and reliable recycled water to meet the increasing water demand of expanding cities. As a result, recent studies have attempted to address the problem of how to optimally integrate satellite systems with other sectors of the urban sphere, such as the local economy, the power supply, and the regional carbon footprint. However, such studies are merely based on the spatial domain, thus neglecting potential time-dependent strategies that could further improve the sustainability of metropolitan water systems. Therefore, in this study a new conceptual framework is proposed for the dynamic management of hybrid systems comprised of both centralized and satellite WRRFs. Furthermore, a novel set of integrated real-time control (RTC) strategies are considered to analyze three different scenarios: 1) demand response, 2) flow equalization of the centralized WRRF and 3) reduction of greenhouse gas emissions. Data from a case study in California is used to develop an integrated dynamic model of a system of 8 facilities. Our results show that by dynamically shifting the dry-weather influent wastewater flows between hydraulically connected WRRFs, a reduction in power demand (up to 25%), energy use (4%), operating costs (8.5%) and indirect carbon emissions (4.5%) can be achieved. Therefore, this study suggests that a certain degree of hydraulic interconnection coupled with dynamic load-shifting strategies, can broaden the operational flexibility and overall sustainability of hybrid WRRF systems.

Integrating dairy manure for enhanced resource recovery at a WRRF: Environmental life cycle and pilot-scale analyses.

The Twin Falls, Idaho wastewater treatment plant (WWTP), currently operates solely to achieve regulatory permit compliance. Research was conducted to evaluate conversion of the WWTP to a water resource recovery facility (WRRF) and to assess the WRRF environmental sustainability; process configurations were evaluated to produce five resources-reclaimed water, biosolids, struvite, biogas, and bioplastics (polyhydroxyalkanoates, PHA). PHA production occurred using fermented dairy manure. State-of-the-art biokinetic modeling, performed using Dynamita's SUMO process model, was coupled with environmental life cycle assessment to quantify environmental sustainability. Results indicate that electricity production via combined heat and power (CHP) was most important in achieving environmental sustainability; energy offset ranged from 43% to 60%, thereby reducing demand for external fossil fuel-based energy. While struvite production helps maintain a resilient enhanced biological phosphorus removal (EBPR) process, MgO2 production exhibits negative environmental impacts; integration with CHP negates the adverse consequences. Integrating dairy manure to produce bioplastics diversifies the resource recovery portfolio while maintaining WRRF environmental sustainability; pilot-scale evaluations demonstrated that WRRF effluent quality was not affected by the addition of effluent from PHA production. Collectively, results show that a WRRF integrating dairy manure can yield a diverse portfolio of products while operating in an environmentally sustainable manner. PRACTITIONER POINTS: Wastewater carbon recovery via anaerobic digestion with combined heat/power production significantly reduces water resource recovery facility (WRRF) environmental emissions. Wastewater phosphorus recovery is of value; however, struvite production exhibits negative environmental impacts due to MgO2 production emissions. Bioplastics production on imported organic-rich agri-food waste can diversify the WRRF portfolio. Dairy manure can be successfully integrated into a WRRF for bioplastics production without compromising WRRF performance. Diversifying the WRRF products portfolio is a strategy to maximize resource recovery from wastewater while concurrently achieving environmental sustainability.

High Diversity and Functional Potential of Undescribed "Acidobacteriota" in Danish Wastewater Treatment Plants.

Microbial communities in water resource recovery facilities encompass a large diversity of poorly characterized lineages that could have undescribed process-critical functions. Recently, it was shown that taxa belonging to “Acidobacteriota” are abundant in Danish full-scale activated sludge wastewater treatment plants (WWTP), and here we investigated their diversity, distribution, and functional potential. “Acidobacteriota” taxa were identified using a comprehensive full-length 16S rRNA gene reference dataset and amplicon sequencing surveys across 37 WWTPs. Members of this phylum were diverse, belonging to 14 families, eight of which are completely uncharacterized and lack type strains. Several lineages were abundant, with relative abundances of up to 5% of the microbial community. Genome annotation and metabolic reconstruction of 50 high-quality “Acidobacteriota” metagenome-assembled genomes (MAGs) from 19 WWTPs showed high metabolic diversity and potential involvement in nitrogen and phosphorus removal and iron reduction. Fluorescence in situ hybridization (FISH) using newly-designed probes revealed cells with diverse morphologies, predominantly located inside activated sludge flocs. FISH in combination with Raman microspectroscopy revealed ecophysiological traits in probe-defined cells from the families Holophagaceae, Thermoanaerobaculaceae, and Vicinamibacteraceae, and families with the placeholder name of midas_f_502, midas_f_973, and midas_f_1548. Members of these lineages had the potential to be polyphosphate-accumulating organisms (PAOs) as intracellular storage was observed for the key compounds polyphosphate and glycogen.

Prioritize effluent quality, operational costs or global warming? – Using predictive control of wastewater aeration for flexible management of objectives in WRRFs

This study presents a general model predictive control (MPC) algorithm for optimizing wastewater aeration in Water Resource Recovery Facilities (WRRF) under different management objectives. The flexibility of the MPC is demonstrated by controlling a WRRF under four management objectives, aiming at minimizing: (A) effluent concentrations, (B) electricity consumption, (C) total operations costs (sum electricity costs and discharge effluent tax) or (D) global warming potential (direct and indirect nitrous oxide emissions, and indirect from electricity production) . The MPC is tested with data from the alternating WRRF in Nørre Snede (Denmark) and from the Danish electricity grid. Results showed how the four control objectives resulted in important differences in aeration patterns and in the concentration dynamics over a day. Controls B and C showed similarities when looking at total costs, while similarities in global warming potential for controls A and D suggest that improving effluent quality also reduced greenhouse gasses emissions. The MPC flexibility in handling different objectives is shown by using a combined objective function, optimizing both cost and greenhouse emissions. This shows the trade-off between the two objectives, enabling the calculation of marginal costs and thus allowing WRRF operators to carefully evaluate prioritization of management objectives. The long-term MPC performance is evaluated over 51 days covering seasonal and inter-weekly variations. On a daily basis, control A was 9–30% cheaper on average compared to controls A, D and to the current rule-based control. Similarly, control D resulted on average in 35–43% lower greenhouse gasses daily emission compared to the other controls. Difference between control performance increased for days with greater inter-diurnal variations in electricity price or greenhouse emissions from electricity production, i.e. when MPC has greater possibilities for exploiting input variations. The flexibility of the proposed MPC can easily accommodate for additional control objectives, allowing WRRF operators to quickly adapt the plant operation to new management objectives and to face new performance requirements.

Modelling the dynamic long-term performance of a full-scale digester treating sludge from an urban WRRF using an extended version of ADM1

The optimization of full-scale digesters requires the development of models able to describe the main process performances, due to the strategic role of anaerobic digestion in the sustainability of Water Resource Recovery Facilities (WRRFs). In this study, an extended version of the Anaerobic Digestion Model No. 1 (ADM1) was developed to simulate the long-term performance of a full-scale anaerobic digester treating primary and activated sludge of a large WWRF (300,000 p.e.). Monitored data were collected over 973 days and analyzed in order to provide reconciled datasets for modeling purposes. A comprehensive influent characterization in terms of biodegradability extent, COD and N content was carried out by combining measurements of several parameters and Biochemical Methane Potential (BMP) tests to provide a compatible ADM1 substrate fractionation. The model was calibrated by comparing simulation results against both routine plant measurements and data from a dedicated measuring campaign. Disintegration constants and particulate inert fractions were the sole estimated model parameters. Disintegration constants determined in the calibration step resulted in values 5-times greater than those initially estimated from BMP tests. The model was able to accurately predict digestate composition in terms of TSS, VSS, COD, N and P as well as biogas production and methane content. It was demonstrated that a precise description of the anaerobic co-digestion of sewage sludges relies on the estimation of solubilization kinetic parameters together with the use of two different composite variables representing each substrate. The developed model proved to be a useful tool that can be integrated in a plant-wide model to assess plant process interactions under different operating conditions

Investigating organic nitrogen production in activated sludge process: Size fraction and biodegradability

The effect of sludge retention time (SRT) on the production of organic nitrogen (ON) fractions (particulate, colloidal and soluble) and the biodegradability of produced soluble ON in an activated sludge process was investigated. Synthetic wastewater with no ON was fed to the four laboratory-scale reactors operated at SRTs of 2, 5, 10 and 20 d, respectively. Effluent ON from each reactor was fractionated into particulate, colloidal, and soluble ON (pON, cON, and sON). The effluent total ON contained 5.7 to 11.9 mg/L pON, 3.6 to 3.8 mg/L cON, and 2.3 to 4.6 mg/L sON. cON fraction can be larger than sON fraction in the secondary effluent. Therefore, besides focusing on sON, water resource recovery facilities aiming to meet stricter effluent TN limits should also identify appropriate technologies to target cON. More than 50% of effluent sON was biodegradable under SRTs of 2, 5, and 10 d but the biodegradability decreased to 31% at 20-d SRT. Large fractions of non-biodegradable sON (69%) at SRT of 20-d could be contributed by extracellular polymeric substances and soluble microbial products, specifically biomass associated products due to endogenous respiration. Thus, sON generated at long SRTs may take longer to decompose in receiving waters.

Sensor bias impact on efficient aeration control during diurnal load variations.

This study highlights the need to increase our understanding of the interplay between sensor drift and the performance of the automatic control system. The impact from biased sensors on the automatic control systems is rarely considered when different control strategies are assessed in water resource recovery facilities. Still, the harsh measurement environment with negative effects on sensor data quality is widely acknowledged. Simulations were used to show how sensor bias in an ammonium cascade feedback controller impacts aeration energy efficiency and total nitrogen removal in an activated sludge process. Response surface methodology was used to reduce the required number of simulations, and to consider the combined effect of two simultaneously biased sensors. The effects from flow variations, and negatively biased ammonium (-1 mg/L) and suspended solids sensors (-500 mg/L) reduced the nitrification aeration energy efficiency by between 7 and 25%. Less impact was seen on total nitrogen removal. There were no added non-linear effects from the two simultaneously biased sensors, apart from an interaction between a biased ammonium sensor and dissolved oxygen sensor located in the last aerated zone. Negative effects from sensor bias can partly be limited if the expected bias direction is considered when the controller setpoint-limits are defined.