Full-scale Biological Nutrient Removal Research Articles

Deactivation of internal recirculation in a full-scale Biological Nutrient Removal (BNR) Wastewater Treatment Plant (WWTP) reveals outstanding microeukaryotic bioindicators

The bioindicator potential of the microeukaryotic community in a full-scale A2O wastewater treatment process was assessed after deactivating the internal recirculation in one of the two parallel treatment lines of the plant. The deactivation of the internal recirculation in one of the lines (NIR-line), led to a strong decrease in nitrogen removal efficiency (53 % ammonia-uptake in the NIR-line versus 97 % in the unaltered line or IR-line), as well as to a lower organic matter removal (95 % BOD5 removal versus 97 % in the IR-line). The microeukaryote community structure changed greatly confirming trends observed in experimental studies and showed a decrease in abundance and richness in the NIR-line. However, this line showed a significant higher abundance of certain ciliate species, such as Epistylis camprubii and Vorticellides infusionum, which are common species in conventional activated sludge. Conversely, the IR-line showed useful indicators of internal recirculation, associated with much higher ammonium and BOD5 removal. These results show that identification to ciliate species level provides a more reliable bioindication in nutrient removal systems, supporting the importance of research on biological parameters, mainly protists, as simple and useful tools for plant operators to manage nutrient removal processes. These observations extend the current boundaries of bioindication.

A comprehensive evaluation of process kinetics: A plant-wide approach for nutrient removal and biogas production

The present study investigated the deviations of operational parameters of a large-scale wastewater treatment plant (WWTP) from design basis through combining dedicated batch experiments with full-scale dynamic modeling results. The long-term process performance of a full-scale biological nutrient removal (BNR) plant equipped with anaerobic sludge digestion system was monitored to evaluate the process kinetics of both carbon and nutrient removal and anaerobic sludge digestion. In this respect, plant-specific characterization; chemical oxygen demand (COD) fractionation, batch kinetic studies and sludge settling velocity tests were performed together with plant-wide SUMO model simulation. Results showed that nitrification and anaerobic hydrolysis were found to be 30% and 70% lower than literature values, respectively. The anaerobic digestion test coupled with plant-wide model calibration showed that anaerobic hydrolysis was the bottleneck in biogas production. Correspondingly, performance of the anaerobic digestion in the full-scale plant was poor as low biogas production yields were observed. In addition, the degradation rate via anaerobic hydrolysis of primary sludge was found to be higher (∼2-2.5) compared to anaerobic hydrolysis of biological sludge. The results of this study provide insight into model-based experimental characterization as well as plant-wide modeling approach. Coupling model-based batch experiments with full-scale modeling enabled to reduce the number of kinetic parameters to be fine-tuned. Moreover, the information gathered from kinetic batch tests to the simulation platform yielded a satisfying prediction of long-term performance of the plant operation.

Application of machine learning techniques to model a full-scale wastewater treatment plant with biological nutrient removal

A full-scale biological nutrient removal wastewater treatment process was simulated using artificial intelligence. In wastewater treatment plants, adaptive machine learning models can reduce process disruptions and generate savings through optimized operation. Machine learning is also useful when simulating processes that are particularly complex and where the physio-chemical interactions are not well understood, such as biological nutrients removal. Current models in literature only focus on the prediction of a small number of effluent parameters using a direct input-output approach. This paper presents a machine learning ensemble model that combines artificial neural networks, adaptive neuro-fuzzy inference systems, and support vector regression to predict 15 process parameters that include biomass properties, operation parameters, and effluent characteristics. A historical dataset between 2010 and 2020 was used to develop and validate the model. The model features a six-stage modular model structure where each parameter was predicted using a separate model and based on the preceding predicted parameters. The average correlation coefficient, normalized root mean square error, and symmetric mean absolute error of 69%, 0.06%, and 7.5%, respectively. The ensemble approach improved the average prediction accuracy over individual base models by 5%. The model developed in this study was more versatile than other machine learning models in the literature and relatively reduced the ambiguity of black-box data-driven models.

Denitrification Process Enhancement and Diversity of the Denitrifying Community in the Full Scale Activated Sludge System after Adaptation to Fusel Oil

Implementation of anaerobic digestion of primary sludge in modern wastewater treatment plants (WWTPs) limits the availability of organic carbon for denitrification in conventional nitrification-denitrification (N/DN) systems. In order to ensure efficient denitrification, dosage of the external carbon source is commonly undertaken. However, application of commercial products, such us ethanol or acetate, greatly increases operational costs. As such, inexpensive and efficient alternative carbon sources are strongly desirable. In this study, the use of the fusel oil, a by-product from the distillery industry, was validated in terms of the denitrification process enhancement and impact on the activated sludge bacterial community structure. The experiment was conducted at a full scale biological nutrient removal facility (210,000 PE), in the set of the two technological lines: the experimental line (where fusel oil was introduced at 45 cm3/m3 dose) and the reference line (without an external carbon source addition). During the experimental period of 98 days, conventional nitrate utilization rate (NUR) measurements were carried out on a regular basis in order to assess the biomass adaptation to the fusel oil addition and denitrification process enhancement. While the NURs remained at a stable level in the reference line (1.4 ± 0.1 mg NO3-N/g VSS·h) throughout the entire duration of the experiment, the addition of fusel oil gradually enhanced the denitrification process rate up to 2.7 mg NO3-N/g VSS·h. Moreover, fusel oil contributed to the mitigation of the variability of NO3-N concentrations in the effluent from the anoxic zone. The bacterial community structure, characterized by 16S rRNA PCR—DGGE and the clone libraries of the genes involved in the denitrification process (nirS and nirK), was comparable between the reference and the experimental line during the entire experimental period. In both analyzed lines, the most frequent occurrence of denitrifiers belonging to the genera Acidovorax, Alcaligenes, Azoarcus, Paracoccus and Thauera was noticed. Our results proved that fusel oil would a valuable substrate for denitrification. The addition of fusel oil enhances the process rate and does not reflect a severe selection pressure on the bacterial community at applicable doses. Practical application of fusel oil generates opportunities for the WWTPs to meet effluent standards and reduce operational costs, as well as optimizing waste management for the distillery industry.

A novel metabolic-ASM model for full-scale biological nutrient removal systems

This study demonstrates that META-ASM, a new integrated metabolic activated sludge model, provides an overall platform to describe the activity of the key organisms and processes relevant to biological nutrient removal (BNR) systems with a robust single-set of default parameters. This model overcomes various shortcomings of existing enhanced biological phosphorous removal (EBPR) models studied over the last twenty years. The model has been tested against 34 data sets from enriched lab polyphosphate accumulating organism (PAO)-glycogen accumulating organism (GAO) cultures and experiments with full-scale sludge from five water resource recovery facilities (WRRFs) with two different process configurations: three stage Phoredox (A2/O) and adapted Biodenitro™ combined with a return sludge sidestream hydrolysis tank (RSS). Special attention is given to the operational conditions affecting the competition between PAOs and GAOs, capability of PAOs and GAOs to denitrify, metabolic shifts as a function of storage polymer concentrations, as well as the role of these polymers in endogenous processes and fermentation. The overall good correlations obtained between the predicted versus measured EBPR profiles from different data sets support that this new model, which is based on in-depth understanding of EBPR, reduces calibration efforts. On the other hand, the performance comparison between META-ASM and literature models demonstrates that existing literature models require extensive parameter changes and have limited predictive power, especially in the prediction of long-term EBPR performance. The development of such a model able to describe in detail the microbial and chemical transformations of BNR systems with minimal adjustment to parameters suggests that the META-ASM model is a powerful tool to predict and mitigate EBPR upsets, optimise EBPR performance and to evaluate new process designs.

Nitrite oxidizing bacteria (NOB) dominating in nitrifying community in full-scale biological nutrient removal wastewater treatment plants

Nitrification activities and microbial populations of ammonium oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) were investigated in 10 full-scale biological nutrient removal wastewater treatment plants in Xi’an, China. Aerobic batch tests were used to determine the nitrifying activities while fluorescence in situ hybridization was used to quantify the fractions of AOB and NOB in the activated sludge. The results showed that nitrifying bacteria accounted for 1–10% of the total population. Nitrosomonas and Nitrospira were the dominant bacteria for AOB and NOB respectively. Moreover, the average percentage of AOB was 1.27% and that of NOB was 4.02%. The numerical ratios of NOB/AOB varied between 1.72 and 5.87. The average ammonium uptake rate and nitrite uptake rate were 3.25 ± 0.52 mg (NH4+–N)/g(VSS) h and 4.49 ± 0.49 mg (NO2−–N)/g(VSS) h, respectively. Correspondingly, the activity of NOB was 1.08–2.00 times higher than that of AOB. Thus, NOB was the dominating bacteria in nitrifying communities. The year-round data of Dianzicun (W6) also expressed a similar trend. Since NOB had higher activities than that of AOB, a large nitrite oxidation pool could be formed, which guaranteed that no nitrite would be accumulated. Therefore, stable nitrification could be achieved. A conceptual model was proposed to describe the population variation of AOB and NOB in a nitrifying community.

Assessment of full-scale biological nutrient removal systems upgraded with physico-chemical processes for the removal of emerging pollutants present in wastewaters from Mexico

Two full-scale biological nutrient removal systems upgraded with three physico-chemical processes (coagulation, chemical precipitation, and neutral Fenton) were evaluated in order to determine the removal of emerging pollutants (EPs) present in municipal wastewater from Mexico. Between 41 and 55 EPs were detected in the influents of two wastewater treatment plants (WWTPs), including personal care products (PPCPs), antibiotics, analgesics, antiepileptics, antilipidemics, antihypertensives, antiseptics, stimulants, and hormones. Emerging pollutants were detected at concentrations ranging from 0.69ng/L to 94,600ng/L. High concentrations of emerging pollutants were found during dry season. WWTP 1, integrated by oxidation ditches and UV light lamps, showed removal efficiencies of EPs between 20% and 22%. On the other hand, WWTP 2 consisted of anaerobic/anoxic/aerobic tanks coupled with two disinfection processes; chlorine dioxide and UV light lamps, for which the removal of EPs was significant (up to 80%). The concentrations of emerging pollutants in WWTP 1 effluent was found within a range<limit of quantification (LOQ) to 3770ng/L. For WWTP 2, the concentrations of the emerging pollutants in the effluent were below 210ng/L. WWTP 2 showed high emerging pollutant removals, compared to those of WWTP 1, due to a greater activity of the simultaneous nitrification-denitrification processes, hydraulic retention time, and solids retention time. The compounds that were more persistent with removals below 50% in both effluents were: carbamazepine, dehydronifedipine, meprobamate, sertraline, propranolol, propoxyphene, norverapamil, diazepam, alprazolam, sulfamethoxazole, metoprolol, ofloxacin, norfloxacin, fluoxetine, erythromycin-H2O, diphenhydramine, dehydronifedipine, clarithromycin, hydrochlorothiazide, and albuterol. The application of neutral Fenton reaction as post-treatment for the two effluents from the WWTPs is promising for the removal of emerging pollutants (up to 100%) and for assuring high quality of treated water.

Potential of hydrolysis of particulate COD in extended anaerobic conditions to enhance biological phosphorous removal.

The effect of anaerobic hydrolysis of particulate COD (pCOD) on biological phosphorous removal in extended anaerobic condition was investigated through (i) sequencing batch reactors (SBR)s with anaerobic hydraulic retention time (HRT) of 0.8, 2, and 4 h; (ii) batch tests using biomass from a full scale biological nutrient removal (BNR) plant; and (iii) activated sludge modeling (BioWin 4.1 simulation). The results from long-term SBRs operation showed that phosphorus removal was correlated to the ratio of filtered COD (FCOD) to total phosphorus (TP) in the influent. Under conditions with low FCOD/TP ratio (average of 20) in the influent, extending anaerobic HRT to 4 h in the presence of pCOD did not significantly improve overall phosphorous removal. During the period with high FCOD/TP ratio (average of 37) in the influent, all SBRs removed phosphorous completely, and the long anaerobic HRT did not have negative effect on overall phosphorous removal. The batch tests also showed that pCOD at different concentration during 4 h test did not affect the rate of anaerobic phosphorus release. The rate of anaerobic hydrolysis of pCOD was significantly low and extending the anaerobic HRT was ineffective. The simulation (BioWin 4.1) of SBRs with low influent FCOD/TP ratio showed that the default kinetics of anaerobic hydrolysis in ASM2d overestimated phosphorous removal in the SBRs (high anaerobic hydrolysis of pCOD). The default anaerobic hydrolysis rate in BioWin 4.1 (ten times lower) could produce similar phosphorous removal to that in the experiment. Results showed that the current kinetics of anaerobic hydrolysis in ASM2d could lead to considerable error in predicting phosphorus removal in processes with extended anaerobic HRT. Biotechnol. Bioeng. 2016;113: 2377-2385. © 2016 Wiley Periodicals, Inc.

A logistic model for the remediation of filamentous bulking in a biological nutrient removal wastewater treatment plant.

Biological nutrient removal (BNR) systems across the globe frequently experience bulking and foaming episodes, which present operational challenges such as poor sludge settling due to excessive filamentous bacteria. A full-scale BNR plant treating primarily domestic wastewater was monitored over a period of 1 year to investigate filamentous bacterial growth response under various plant operating parameters. Identification of filamentous bacteria by conventional microscopy and fluorescent in situ hybridisation indicated the dominance of Eikelboom Type021N, Thiothrix spp., Eikelboom Type 1851 and Eikelboom Type 0092. A cumulative logit model (CLM) was applied to elucidate significant relationships between the filamentous bacteria and plant operational parameters. The model could predict the potential abundance of dominant filamentous bacteria in relation to wastewater treatment plant operational parameters. Data obtained from the model corroborated with previous findings on the dominance of most filaments identified, except for Type 0092, which exhibited some unique traits. With further validation, the model could be successfully applied for identifying specific parameters which could contribute towards filamentous bulking, thus, providing a useful tool for regulating specific filamentous growth in full-scale wastewater treatment plants.

Achieving low effluent NO3-N and TN concentrations in low influent chemical oxygen demand (COD) to total Kjeldahl nitrogen (TKN) ratio without using external carbon source

Two mathematical models were used to optimize the performance of a full-scale biological nutrient removal (BNR) activated treatment plant, a plug-flow bioreactors operated in a 3-stage phoredox process configuration, anaerobic anoxic oxic (A2/O). The ASM2d implemented on the platform of WEST2011 software and the BioWin activated sludge/anaerobic digestion (AS/AD) models were used in this study with the aim of consistently achieving the designed effluent criteria at a low operational cost. Four ASM2d parameters (the reduction factor for denitrification \((\eta _{NO_3 H} )\), the maximum growth rate of heterotrophs (µH), the rate constant for stored polyphosphates in PAOs (qpp), and the hydrolysis rate constant (kh)) were adjusted. Whereas three BioWin parameters (aerobic decay rate (bH), heterotrophic dissolved oxygen (DO) half saturation (KOA), and YP/acetic) were adjusted. Calibration of the two models was successful; both models have average relative deviations (ARD) less than 10% for all the output variables. Low effluent concentrations of nitrate nitrogen (N-NO3), total nitrogen (TN), and total phosphorus (TP) were achieved in a full-scale BNR treatment plant having low influent chemical oxygen demand (COD) to total Kjeldahl nitrogen (TKN) ratio (COD/TKN). The effluent total nitrogen and nitrate nitrogen concentrations were improved by 50% and energy consumption was reduced by approximately 25%, which was accomplished by converting the two-pass aerobic compartment of the plug-flow bioreactor to anoxic reactors and being operated in an alternating mode. Findings in this work are helpful in improving the operation of wastewater treatment plant while eliminating the cost of external carbon source and reducing energy consumption.

Dissolved and colloidal organic nitrogen removal from wastewater treatment plants effluents and reject waters using physical-chemical processes.

Four physical-chemical processes were compared in terms of the efficiencies of dissolved and colloidal organic nitrogen (DON and CON) removal from the secondary effluents (SE) and reject water from full-scale biological nutrient removal activated sludge systems. Adsorption on activated carbon was most efficient and allowed removal from the SE of up to 80% and 100% of DON and CON, respectively. High efficiencies of DON removal from SE (up to 55%) were also obtained when using coagulation with iron(III) chloride and calcium hydroxide at final pH = 11.0-11.5. The efficiency of DON removal from thickening waste activated sludge (TWAS) reject water, obtained using coagulation with iron(III) chloride, was comparable with the efficiency for the SE. The efficiency of this process with regard to the sludge digester liquors (SDL) was significantly higher, i.e., 65-70% for both DON and CON. The ion exchange process with strongly acidic cation exchange resin (without pH correction) resulted in a relatively small efficiency of DON removal (<15%), and negligible efficiency of CON removal (<10%). Furthermore, ultrafiltration (0.015 μm) of SE and TWAS reject water resulted in a relatively low efficiency of DON removal (10-13% and 10-20% respectively). Ultrafiltration was found to be more effective for DON removal from SDL (41-68%).

Quantification method of N2O emission from full-scale biological nutrient removal wastewater treatment plant by laboratory batch reactor analysis

This study proposes a simplified method for the quantification of N2O emission from a biological nutrient removal wastewater treatment plant (WWTP). The method incorporates a laboratory-scale batch reactor which had almost the same operational (wastewater and sludge flow rates) condition of a unit operation/process of the WWTP. Cumulative N2O emissions from the batch reactor at the corresponding hydraulic retention times of the full-scale units (primary and secondary clarifiers, pre-anoxic, anaerobic, anoxic and aerobic basins) were used for the quantification of N2O emission. The analysis showed that the aerobic basin emitted 95% of the total emission and the emission factor (yield) reached 0.8% based on the influent nitrogen load. The method successfully estimated N2O emission from the WWTP and it has shown advantages in measurement time and cost over the direct field measurement (floating chamber) method.

Dissolved and colloidal organic nitrogen removal from WWTP effluents and reject waters using physical-chemical processes

Dissolved and colloidal organic nitrogen removal from WWTP effluents and reject waters using physical-chemical processesThe efficiencies of various physical-chemical processes were compared with respect to dissolved and colloidal organic nitrogen (DON and CON) removal from the plant effluents and sludge digester liquors of full-scale biological nutrient removal (BNR) activated sludge systems. Adsorption on granulated activated carbon was most efficient and allowed to remove up to 80% and 100%...Author(s)K. CzerwionkaJ. MakiniaSourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jul, 2013ISSN1938-6478DOI10.2175/193864713813525635Volume / Issue2013 / 4Content sourceNutrient Removal and Recovery SymposiumCopyright2013Word count249

Modeling External Carbon Addition in Biological Nutrient Removal Processes with an Extension of the International Water Association Activated Sludge Model

The aim of this study was to expand the International Water Association Activated Sludge Model No. 2d (ASM2d) to account for a newly defined readily biodegradable substrate that can be consumed by polyphosphate-accumulating organisms (PAOs) under anoxic and aerobic conditions, but not under anaerobic conditions. The model change was to add a new substrate component and process terms for its use by PAOs and other heterotrophic bacteria under anoxic and aerobic conditions. The Gdansk (Poland) wastewater treatment plant (WWTP), which has a modified University of Cape Town (MUCT) process for nutrient removal, provided field data and mixed liquor for batch tests for model evaluation. The original ASM2d was first calibrated under dynamic conditions with the results of batch tests with settled wastewater and mixed liquor, in which nitrate-uptake rates, phosphorus-release rates, and anoxic phosphorus uptake rates were followed. Model validation was conducted with data from a 96-hour measurement campaign in the full-scale WWTP. The results of similar batch tests with ethanol and fusel oil as the external carbon sources were used to adjust kinetic and stoichiometric coefficients in the expanded ASM2d. Both models were compared based on their predictions of the effect of adding supplemental carbon to the anoxic zone of an MUCT process. In comparison with the ASM2d, the new model better predicted the anoxic behaviors of carbonaceous oxygen demand, nitrate-nitrogen (NO3-N), and phosphorous (PO4-P) in batch experiments with ethanol and fusel oil. However, when simulating ethanol addition to the anoxic zone of a full-scale biological nutrient removal facility, both models predicted similar effluent NO3-N concentrations (6.6 to 6.9 g N/m3). For the particular application, effective enhanced biological phosphorus removal was predicted by both models with external carbon addition but, for the new model, the effluent PO4-P concentration was approximately one-half of that found from ASM2d. On a PO4-P removal percentage basis, the difference was small, that is, 94.1 vs. 97.1%, respectively, for the ASM2d and expanded ASM2d.

Spatial distribution and viability of nitrifying, denitrifying and ANAMMOX bacteria in biofilms of sponge media retrieved from a full-scale biological nutrient removal plant

The spatial distribution and activities of nitrifying and denitrifying bacteria in sponge media were investigated using diverse tools, because understanding of in situ microbial condition of sponge phase is critical for the successful design and operation of sponge media process. The bacterial consortia within the media was composed of diverse groups including a 14.5% Nitrosomonas spp.-like ammonia oxidizing bacteria (AOB), 12.5% Nitrobacter spp.-like nitrite oxidizing bacteria (NOB), 2.0% anaerobic ammonium-oxidizing (ANAMMOX) bacteria and 71.0% other bacteria. The biofilm appeared to be most dense in the relatively outer region of the media and gradually decreased with depth, but bacterial viabilities showed space-independent feature. The fluorescent in situ hybridization results revealed that AOB and NOB co-existed in similar quantities on the side fragments of the media, which was reasonably supported by the microelectrode measurements showing the concomitant oxidation of NH(4) (+) and production of NO(3) (-) in this zone. However, a significantly higher fraction of AOB was observed in the center than side fragment. As with the overall biofilm density profile, the denitrifying bacteria were also more abundant on the side than in the center fragments. ANAMMOX bacteria detected throughout the entire depth offer another advantage for the removal of nitrogen by simultaneously converting NH(4) (+) and NO(2) (-) to nitrogen gas.

Characteristics and fate of organic nitrogen in municipal biological nutrient removal wastewater treatment plants

The aim of this study was to investigate the occurrence and fate of colloidal and dissolved organic nitrogen (CON and DON) across biological nutrient removal (BNR) activated sludge bioreactors. Primary and secondary effluent total nitrogen (TN) measurements and component fractionation, CON and DON concentration profiles across BNR bioreactors, and laboratory batch experiments with the process mixed liquor were carried out at several full-scale BNR plants in northern Poland. The organic nitrogen (ON) components were divided into high CON, low CON, and DON based on sequential filtration through 1.2, 0.45 and 0.1 μm pore-size filters. The average influent DON0.1μm (<0.1 μm) concentrations ranged from 1.1 g N/m3 to 3.9 g N/m3 and accounted for only 4–13% of total organic nitrogen. In the effluents, however, this contribution increased to 12–45% (the DON0.1μm concentrations varied in a narrow range of 0.5–1.3 g N/m3). Conversions of ON inside the bioreactors were investigated in more detail in two largest plants, i.e. Gdansk (565,000 PE) and Gdynia (516,000 PE). Inside the two studied bioreactors, the largest reductions of the colloidal fraction were found to occur in the anaerobic and anoxic compartments, whereas an increase of DON0.1μm concentrations was observed under aerobic conditions in the last compartment. Batch experiments with the process mixed liquor confirmed that DON0.1μm was explicitly produced in the aerobic phase and significant amounts of ON were converted in the anoxic phase of the experiments.

Nitrous oxide generation in full-scale biological nutrient removal wastewater treatment plants

International guidance for estimating emissions of the greenhouse gas, nitrous oxide (N 2O), from biological nutrient removal (BNR) wastewater systems is presently inadequate. This study has adopted a rigorous mass balance approach to provide comprehensive N 2O emission and formation results from seven full-scale BNR wastewater treatment plants (WWTP). N 2O formation was shown to be always positive, yet highly variable across the seven plants. The calculated range of N 2O generation was 0.006–0.253 kgN 2O–N per kgN denitrified (average: 0.035 ± 0.027). This paper investigated the possible mechanisms of N 2O formation, rather than the locality of emissions. Higher N 2O generation was shown to generally correspond with higher nitrite concentrations, but with many competing and parallel nitrogen transformation reactions occurring, it was very difficult to clearly identify the predominant mechanism of N 2O production. The WWTPs designed and operated for low effluent TN (i.e. <10 mgN L −1) had lower and less variable N 2O generation factors than plants that only achieved partial denitrification.

Activity and identity of fermenting microorganisms in full‐scale biological nutrient removing wastewater treatment plants

Hydrolysis and fermentation are of key importance in biological nutrient removal (BNR) wastewater treatment plants as they provide polyphosphate-accumulating organisms and denitrifying bacteria with carbon and energy sources (e.g. short chain fatty acids). Little information, however, exists about the microbiology of the microorganisms involved in hydrolysis and fermentation. In this study, fermentation of monosaccharides was found to be a universal process taking place in all full-scale BNR plants investigated, where glucose and other monosaccharides were consumed and fermented during anaerobic conditions. The removal rates of glucose were in the range of 0.05-0.32 mmol gVSS(-1) h(-1) and only slightly lower than glucose removal under aerobic conditions. The main fermentation products detected were (in descending order) propionic acid, lactic acid, acetic acid and formic acid. The fermentation was diverse, consisting of at least three fermentation metabolisms, including lactic acid (homolactic), mixed acid and propionic acid fermentations. Possible existence of alcohol and/or butyric acid fermentations could not be excluded. Fermentation organisms in Aalborg East treatment plant were identified by using microautoradiography combined with fluorescence in situ hybridization. All microorganisms involved in monosaccharide fermentation belonged to either Gram-positive Firmicutes or Actinobacteria. Most of them were related either to Streptococcus, hybridizing to the oligonucleotide probe Str, or to uncultured Actinobacteria with a phenotype of polyphosphate-accumulating organisms. The fermenting bacteria were widespread in the nine full-scale BNR plants investigated and constituted 3-21% of the total bacterial biovolume.

Evolutionary Multivariate Dynamic Process Model Induction for a Biological Nutrient Removal Process

This paper proposes an automatic process model induction system using an evolutionary computational intelligence, called grammar-based genetic programming, that is specially designed to automatically discover multivariate dynamic process models that best fit observed process data. This automatic process model induction system combines an evolutionary self-organizing system of genetic programming paradigm with various mathematical functions for a multivariate nonlinear model evolution using a grammar system via the mechanism of genetics and natural selection. The results demonstrate how the automatic process model induction system based on grammar-based genetic programming can be used to develop accurate and relatively cost-effective multivariate dynamic process models for the full-scale biological nutrient removal process. Multivariate dynamic process models are derived automatically in the form of understandable mathematical formulas that enable engineers to extract important knowledge hidden in the data and develop better operation and control strategies.

Comparison of Two Model Concepts for Simulation of Nitrogen Removal at a Full-Scale Biological Nutrient Removal Pilot Plant

The experimental studies conducted at the Hanover-Gummerwald pilot wastewater treatment plant (WWTP) focused on minimizing nitrogen loads discharged during stormwater events. The data collected during the plant operation were used for a long-term process simulation. The aim of this study was to compare predictive capabilities of two different mechanistic models (ASM2d and ASM3P) in terms of nitrogen removal. The influent wastewater composition was generated using on-line measurements of only three parameters (COD, N–N H4+ , P–P O4 3− ) and the model predictions were primarily compared with on-line data (concentrations of N–N H4+ , N–N O3− ) originating from the aerobic zone of the bioreactor. The simulation results confirmed the experimental data concerning the capabilities of the system for handling increased flows during stormwater events. The predicted peaks of N–N H4+ at the line with the quadruple dry weather flow rate were normally exceeding 8 g N∙ m−3 (similar to the observations), whereas no (or m...