Full-scale Sequencing Batch Reactor Research Articles

Utilizing anaerobic substrate distribution for growth of aerobic granular sludge in continuous-flow reactors

The development of continuous flow reactors (CFRs) employing aerobic granular sludge (AGS) for the retrofit of existing wastewater treatment plants (WWTPs) using a continuous-flow activated sludge (CFAS) system has garnered increasing interest. This follows the worldwide adoption of AGS technology in sequencing batch reactors (SBRs). The better settleability of AGS compared to AS allows for process intensification of existing wastewater treatment plants without the difficult conversion of often relatively shallow CFRs to deeper AGS-SBRs.To retrofit existing CFAS systems with AGS, achieving both increased hydraulic capacity and enhanced biological nutrient removal necessitates the formation of granular sludge based on the same selective pressures applied in AGS-SBRs. Previous efforts have focussed mainly on the selective wasting of flocculent sludge and retaining granular sludge to drive aerobic granulation.In this study a pilot-scale CFR was developed to best mimic the implementation of the granulation mechanisms of full-scale AGS-SBRs. The pilot-scale reactor was fed with pre-settled municipal wastewater. We established metrics to assess the degree to which the proposed mechanisms were implemented in the pilot-scale CFR and compared them to data from full-scale AGS-SBRs, specifically with respect to the anaerobic distribution of granule forming substrates (GFS). The selective pressures for granular sludge formation were implemented through inclusion of anaerobic upflow selectors with a water depth of 2.5 meters, which yielded a sludge with properties similar to AGS from full-scale SBRs. In comparison to the CFAS system at Harnaschpolder WWTP treating the same pre-settled wastewater, a more than twofold increase in volumetric removal capacity for both phosphorus and nitrogen was achieved. The use of a completely mixed anaerobic selector, as opposed to an anaerobic upflow selector, caused a shift in EBPR activity from the largest towards the smallest size class, while nitrification was majorly unaffected. Anaerobic selective feeding via bottom-feeding is, therefore, favorable for the long-term stability of AGS, especially for less acidified wastewater. The research underlines the potential of AGS for enhancing the hydraulic and biological treatment capacity of existing CFAS systems.

Microbial community composition from full-scale reactors treating mature landfill leachate through innovative biological processes and its importance in mathematical modeling

This study investigated the microbial community in two full-scale sequencing batch reactors (SBR) treating mature landfill leachate. Partial nitritation/anammox (PN/A) occurred in SBRA while simultaneous partial nitrification and denitrification (SPND) occurred in SBRB. The taxonomic complexity of bacteria and archaea in samples was assessed at the phylum, class and genus levels using 16 S rRNA-based molecular analyses. Despite the different operating conditions in the SBRs, mainly in terms of DO concentration and SBR cycles, the consortia composition in both reactors was quite similar. However, the relative abundance of the major bacterial groups differed, reflecting the different processes involved. Molecular analyses identified dominant bacteria belonging to AOB, Anammox and denitrifies, allowing to select specific kinetic parameters to be used in mathematical modelling, thus reaching a good data reproduction for both reactors.

Evaluating the Operation of a Full-Scale Sequencing Batch Reactor–Reverse Osmosis–Evaporation System Used to Treat Landfill Leachates: Removal of Pollutants, Energy Consumption and Greenhouse Gas Emissions

Limited information is available in the literature regarding the energy consumption and the greenhouse gases emitted during landfill leachates treatment. A full-scale landfill leachates treatment system that included primary sedimentation, biological treatment in sequencing batch reactors, reverse osmosis and mechanical vapor recompression evaporation was monitored and evaluated for the removal of major pollutants, energy consumption and greenhouse gas emissions. Samples were taken during a period of two years from different points of the system, while the actual power consumption was calculated considering the available mechanical equipment and the hours of operation. The quantities of greenhouse gases emitted were estimated using appropriate equations and based on the operational characteristics of the system. According to chemical analyses, biological treatment resulted in partial removal of COD and total nitrogen, while the removal of BOD5 and NH4-N was significant, reaching 90 and 98%, respectively. Use of reverse osmosis increased the removal of all pollutants, satisfying the requirements of the legislation on wastewater discharge into the environment. Power consumption was calculated to be 35.3 KWhr per m3 of treated leachate, while mechanical vapor recompression evaporation was responsible for 60.5% of the total energy required. The contribution of other processes to energy consumption was as follows, in decreasing order: sequencing batch reactors > reverse osmosis > primary treatment. The roots blower vacuum pump used for mechanical vapor recompression evaporation, and the blowers providing air to the sequencing batch reactors, were the most energy-intensive pieces of apparatus, contributing 44.2% and 11.3% of the required energy, respectively. The quantity of greenhouse gases emitted was estimated to be 27.7 Kg CO2eq per m3 of treated leachates. Among the different processes used, biological treatment and mechanical vapor recompression evaporation contributed to 45.7% and 44.1% of the total emissions, respectively. The findings of this study reveal that an integrated landfill leachate treatment system that combines biological treatment and reverse osmosis can assure the protection of the aquatic environment by producing high-quality effluent; however, further research should be conducted regarding the sustainable management of reverse osmosis concentrate. Mechanical vapor recompression evaporation contributes significantly to the environmental footprint of the landfill leachates treatment system due to both high energy consumption and elevated emissions of greenhouse gases.

Improved Biological Phosphorus Removal under Low Solid Retention Time Regime in Full-Scale Sequencing Batch Reactor

Enhanced biological phosphorus removal (EBPR) is an obscure but economical and helpful technology for removing phosphorus biologically from wastewater. A 3-MLD capacity pre-anoxic selector-attached sequencing batch reactor (SBR) treated municipal wastewater from the residents of IIT Roorkee. The treatment in the plant satisfied the effluent discharge standards in all respects except phosphorus, observed during an intensive two-year study. An elaborated 80-day study was performed to enhance and improve the plant’s performance in terms of phosphorus removal specifically, with run 1: solid retention times (SRT) reduced from 56 to 20 days (t = 35 d), run 2: lowering the diffuser’s running time from 15 min to 10 min in anoxic cum anaerobic selector chambers (dissolved oxygen (DO) concentration reduced to <0.15 mg/L) along with reducing SRT to 15 days (t = 25 d), and run 3:intensive reduction in SRT to ≤10 days (t = 20 d). During run 3, the increment in the enhanced biological phosphorus removal (EBPR) efficiency was three times that of the initial run (ηmax~65%) with a readily biodegradable chemical oxygen demand to total phosphorus ratio (rbCOD/TP) of 7.8. The 16SrRNA sequencing revealed the microbial community structure before and after the changes in SRT and EBPR efficiencies, to correlate the biochemical processes and functional organisms.

End-to-end autonomous and resilient operability strategy of full-scale PN-SBR system: From influent augmentation to AI-aided optimal control and scheduling

This study developed an artificial intelligence (AI)-driven autonomous resilient operation of partial nitrification (PN) process to enhance the performance of a two-stage PN-anammox process by ensuring a specific NO2/NH4 ratio under varying influent conditions before the wastewater enters the subsequent anammox process. First, a mathematical model representing PN process was developed in a full-scale sequencing batch reactor (PN-SBR). That model was then calibrated using AI-driven multi-objective optimization targeting NH4, NO2, and NO3 using a comprehensive rank-based global sensitivity analysis framework to identify the biological kinetic and stoichiometric parameters that has high affection on the PN process. After validating the PN-SBR model with real-time measurements of the PN process, an AI-driven optimal aeration strategy (AI-OpAS) was developed for the targeted PN-SBR. The influent characteristics were augmented using the oversampling method and then clustered using varying influent conditions. The AI-OpAS used iterative approximate dynamic programming (iADP) to determine the optimal aeration length scheduling and optimal dissolved‑oxygen control policy to maintain autonomously the NO2/NH4 ratio while reducing aeration energy under diverse influent conditions. The results show that the proposed AI-OpAS can operate the PN-SBR process by achieving the proposed NO2/NH4 ratio of 1.1 and reducing overall aeration energy consumption by up to 31.38 % under varying influent conditions; furthermore, this AI-aided strategy of resilient operation can be extended to the other variables such as pH for autonomous and sustainable PN-SBR system simultaneously.

Ammonia-Oxidizing Bacteria Maintain Abundance but Lower amoA-Gene Expression during Cold Temperature Nitrification Failure in a Full-Scale Municipal Wastewater Treatment Plant.

In this study, we explore the relationship between community structure and transcriptional activity of ammonia-oxidizing bacteria during cold temperature nitrification failure in three parallel full-scale sequencing batch reactors (SBRs) treating municipal wastewater. In the three reactors, ammonia concentrations increased with declines in wastewater temperature below 15°C. We quantified and sequenced 16S rRNA and ammonia monooxygenase (amoA) gene fragments in DNA and RNA extracts from activated sludge samples collected from the SBRs during the warmer seasons (summer and fall) and when water temperatures were below 15°C (winter and spring). Taxonomic community composition of amoA genes and transcripts did not vary much between the warmer and colder seasons. However, we observed significant differences in amoA transcript copy numbers between fall (highest) and spring (lowest). Ammonia-oxidizing bacteria of the genus Nitrosomonas sp. could maintain their population abundance despite lowering their amoA gene expression during winter and spring. In spite of relatively low population abundance, an amoA amplicon sequence variant (ASV) cluster identified as most similar to the amoA gene of Nitrosospira briensis showed the highest amoA transcript-to-gene ratio throughout all four seasons, indicating that some nitrifiers remain active at wastewater temperatures below 15°C. Our results show that 16S rRNA and amoA gene copy numbers are limited predictors of cell activity. To optimize function and performance of mixed community bioprocesses, we need to collect high-resolution quantitative transcriptomic and potentially proteomic data to resolve the response of individual species to changes in environmental parameters in engineered systems. IMPORTANCE The diverse microbial community of activated sludge used in biological treatment systems exhibits dynamic seasonal shifts in community composition and activity. Many wastewater treatment plants in temperate/continental climates experience seasonal cold temperature nitrification failure. "Seasonal nitrification failure" is the discharge of elevated concentrations of ammonia (greater than 4 mg/liter) with treated wastewater during the winter (influent wastewater temperatures below 13°C). This study aims at expanding our understanding of how ammonia-oxidizing bacteria in activated sludge change in activity and growth across seasons. We quantified the ammonia monooxygenase (amoA) gene and transcript copy numbers using real-time PCR and sequenced the amoA amplicons to reveal community structure and activity changes of nitrifying microbial populations during seasonal nitrification failure in three full-scale sequencing batch reactors (SRBs) treating municipal wastewater. Relevant findings presented in this study contribute to explain seasonal nitrification performance variability in SRBs.

Intricacies of Enhanced Biological Phosphorus Removal in Full-Scale Sequencing Batch Reactors Based on Wastewater Treatment Plants of India

Intricacies of Enhanced Biological Phosphorus Removal in Full-Scale Sequencing Batch Reactors Based on Wastewater Treatment Plants of India

Impact of nitrite and oxygen on nitrous oxide emissions from a granular sludge sequencing batch reactor

Maximizing nutrient removal and minimizing greenhouse gas (GHG) emissions is imperative for the future of wastewater treatment. As municipalities focus on minimizing their carbon footprints, future permits could regulate GHG emissions from wastewater treatment plants. This study investigates how nitrous oxide (N2O) emissions are affected by dissolved oxygen and nitrite concentrations, providing potential strategies to meet possible gaseous emission permits. A lab-scale sequencing batch reactor (SBR) was enriched with aerobic granular sludge (AGS) capable of phosphate removal and simultaneous nitrification-denitrification (SND). N2O emissions were tracked at varying dissolved oxygen (DO) and nitrite (NO2−) concentrations, with >99% SND efficiency and 93%–100% phosphate removal efficiency. Higher DO and NO2− concentrations were associated with higher N2O emissions. Emissions were minimized at a DO concentration of 1 mg L−1, with an average emission factor of 0.18% of oxidized NH3–N emitted as N2O–N, which is lower than factors from many full-scale treatment plants (Vasilaki et al., 2019) and similar to a Nereda® full-scale AGS SBR (van Dijk et al., 2021). This challenges assertions that AGS emits more N2O than conventional activated sludge, although more research at full-scale with influent quality variations is required to confirm this trend. Molecular analyses revealed that the efficient SND was likely achieved with shortcut nitrogen removal facilitated by a low presence of nitrite oxidizing bacteria and a large population of denitrifying phosphate accumulating organisms, which far outnumbered denitrifying glycogen accumulating organisms.

Activated sludge microbial communities and hydrolytic potential in a full-scale SBR system treating landfill leachate

Landfill leachate, due to its recalcitrant nature and toxicity, poses a serious environmental threat, which requires the implementation of effective treatment processes. In this work, a full-scale treatment system consisting of two Sequencing Batch Reactors (SBRs) was used for the processing of landfill leachate of intermediate to mature age (BOD/COD ratio of 0.16). Biosystem operation resulted in BOD5, COD and TKN removal efficiencies of 81%, 39% and 76%, respectively, whereas the low residual NO3 --N concentration in the effluent (4.01 ± 0.10 mg/L) was indicative of the efficient denitrification process. Assessment of hydrolytic potential of activated sludge revealed high endocellular and extracellular lipase activities, which reached values up to 206 and 141 U/g protein respectively, possibly as the consequence of plastics degradation during maturation process. Implementation of Illumina sequencing indicated the predominance of Alphaproteobacteria, accompanied by members of Bacteroidetes, Betaproteobacteria and Chloroflexi. Paracoccus was the predominant genus identified, followed by representatives of the genera Bellilinea, Flavobacterium, Thauera and Truepera. Nitrosomonas was the major ammonia-oxidizing bacterium (AOB), while nitrite oxidation was mainly achieved by the uncultured nitrite-oxidizing bacterium (NOB) Candidatus Nitrotoga.

Influence of variations in wastewater on simultaneous nutrient removal in pre-anoxic selector attached full-scale sequencing batch reactor

Influence of variations in wastewater on simultaneous nutrient removal in pre-anoxic selector attached full-scale sequencing batch reactor

Perspectives of intracellular polymers in functional evaluation of the microbes for EBPR

Abstract To substantiate and interpret the performance of the Enhanced Biological Phosphorus Removal (EBPR) processes with simultaneous nitrogen removal in five full-scale sequencing batch reactors (SBR) systems (with or without pre-anoxic/anaerobic selector) across India, conventional microscopic examinations were performed. Regular examining and cyclic behavior evaluation studies specified that these systems worked for EBPR with effectiveness depending on the wastewater quality and operational steadiness. Treatment with Neisser stain for identifying polyphosphates (poly-P) and Sudan black B stain for observing poly-β-hydroxybutyrates (PHB) granules showed that the enriched biomass of the SBR plants was very diverse concerning morphology, residing populations of traditional rod-shaped PAOs, tetrad (or Sarcina-like cells) forming organisms (submitted as TFOs instead of GAOs), diplococci-shaped cells, and staphylococci-like clustered populations (CC), including few filaments which correlate well with biochemical processes undergoing in SBR plants. SBR plants with readily biodegradable chemical oxygen demand (rbCOD) fraction in COD > 16% and rbCOD/TP ∼10–20 in Varanasi, Mumbai, and Gurgaon, respectively, have performed for >20% EBPR (∼77.8%, ∼76.6%, and ∼84.8% TP removal, respectively) as well as >85% Simultaneous Nitrification and Denitrification (SND). This study can open novel dimensions for optimization by relating microscopic observations (qualitative examination) with the processes undergoing in the plants under varied physicochemical parameters.

Tracking de novo protein synthesis in the activated sludge microbiome using BONCAT-FACS

In order to ensure stable performance of engineered biotechnologies that rely on mixed microbial community systems, it is important to identify process-specific microbial traits and study their in-situ activity and responses to changing environmental conditions and system operational parameters. We used BioOrthogonal Non-Canonical Amino acid Tagging (BONCAT) in combination with Fluorescence-Activated Cell Sorting (FACS) and 16S rRNA gene amplicon sequencing to identify translationally active cells in activated sludge. We found that only a subset of the activated sludge microbiome is translationally active during the aerobic treatment phase of a full-scale sequencing batch reactor designed to enhance biological phosphorus removal from municipal wastewater. Relative abundance of amplicon sequence variants was not a reliable predictor of species activity. BONCAT-positive and -negative cells revealed a broad range of population-wide and taxa-specific translational heterogeneity. BONCAT-FACS in combination with amplicon sequencing can provide new insights into the ecophysiology of highly dynamic microbiomes in activated sludge systems.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater

To investigate the major triggers of nitrous oxide (N2O) production in a full-scale wastewater treatment plant, N2O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N2O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N2O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N2O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N2O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N2O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N2O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N2O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N2O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N2O emission factor) (p-value = 0.00001, Mann-Whitney test).

Emission characteristics of odorous volatile sulfur compound from a full-scale sequencing batch reactor wastewater treatment plant.

Volatile sulfur compounds (VSCs) generated and discharged as air pollutants from wastewater treatment plants (WWTPs) pose a threat to human health and the environment. This study characterized VSC emissions from a full-scale sequencing batch reactor (SBR) WWTP at the water-air interface for one year. Results demonstrated that higher ambient temperatures and aeration contributed significantly to VSC emissions as the highest emissions occurred over summer during the feeding synchronous aeration period. VSC emissions were related to chemical oxygen demand and sulfate concentrations in wastewater, and empirical formulas based on these values were proposed that can be used to model VSC emission fluxes from SBR WWTP. VSC emission factors (μg·ton-1 wastewater) throughout the SBR treatment process were: 361±101 hydrogen sulfide (H2S), 82±76 methyl mercaptan (MT), 61±31 dimethyl sulfide, 17±5 carbon disulfide, and 46±24 dimethyl disulfide. H2S and MT were the dominant odors released. Findings from this study may be applicable for calculating VSC emissions during SBR wastewater treatment stages, and may be beneficial for determining methods and strategies to reduce VSCs.

Mitigating nitrous oxide emissions at a full-scale wastewater treatment plant

Mitigation of nitrous oxide (N2O) emissions is of primary importance to meet the targets of reducing carbon footprints of wastewater treatment plants (WWTPs). Despite of a large amount of N2O mitigation studies conducted in laboratories, full-scale implementation of N2O mitigation is scarce, mainly due to uncertainties of mitigation effectiveness, validation of N2O mathematical model, risks to nutrient removal performance and additional costs. This study aims to address the uncertainties by investigating the quantification, development and implementation of N2O mitigation strategies at a full-scale sequencing batch reactor (SBR). To achieve this, N2O emission dynamics, nutrient removal performance and operation of the SBR were monitored to quantify N2O emissions, and identify the N2O generation mechanisms. N2O mitigation strategies centered on reducing dissolved oxygen (DO) levels were consequently proposed and evaluated using a multi-pathway N2O production mathematical model before implementation. The implemented mitigation strategy resulted in a 35% reduction in N2O emissions (from the emission factor of 0.89 ± 0.05 to 0.58 ± 0.06%), which was equivalent to annual reduction of 2.35 tonne of N2O from the studied WWTP. This could be mainly attributed to reductions in N2O generated via the NH2OH oxidation pathway due to the lowering of DO level. As the first reported mitigation strategy permanently implemented at a full scale WWTP, it showcased that the mitigation of N2O emissions at full-scale is feasible and that widely accepted N2O mitigation strategies developed in laboratory studies are also likely effective in full-scale plants. Furthermore, the close agreement between the validated and predicted N2O emission factors (0.58% vs 0.55%, respectively), showed that the N2O mathematical model is a useful tool to evaluate N2O mitigation strategies at full-scale. Importantly this work demonstrated that N2O mitigation does not necessarily require additional operational cost to meet reduction targets. In contrast, the N2O mitigation applied here reduced energy requirements for aeration by 20%. Equally important, long-term monitoring identified that N2O mitigation did not affect the nutrient removal performance of the plant. Finally, with the knowledge acquired in this study, a standard approach for mitigating N2O emissions from full-scale treatment plants was proposed.

Composition and Dynamics of the Activated Sludge Microbiome during Seasonal Nitrification Failure

Wastewater treatment plants in temperate climate zones frequently undergo seasonal nitrification failure in the winter month yet maintain removal efficiency for other contaminants. We tested the hypothesis that nitrification failure can be correlated to shifts in the nitrifying microbial community. We monitored three parallel, full-scale sequencing batch reactors over the course of a year with respect to reactor performance, microbial community composition via 16S rRNA gene amplicon sequencing, and functional gene abundance using qPCR. All reactors demonstrated similar changes to their core microbiome, and only subtle variations among seasonal and transient taxa. We observed a decrease in species richness during the winter, with a slow recovery of the activated sludge community during spring. Despite the change in nitrification performance, ammonia monooxygenase gene abundances remained constant throughout the year, as did the relative sequence abundance of Nitrosomonadacae. This suggests that nitrification failure at colder temperatures might result from different reaction kinetics of nitrifying taxa, or that other organisms with strong seasonal shifts in population abundance, e.g. an uncultured lineage of Saprospiraceae, affect plant performance in the winter. This research is a comprehensive analysis of the seasonal microbial community dynamics in triplicate full-scale sequencing batch reactors and ultimately strengthens our basic understanding of the microbial ecology of activated sludge communities by revealing seasonal succession patterns of individual taxa that correlate with nutrient removal efficiency.

Genomic insights into the metabolism of 'Candidatus Defluviicoccus seviourii', a member of Defluviicoccus cluster III abundant in industrial activated sludge.

Filamentous cluster III Defluviicoccus (DF3) are known to proliferate and cause bulking issues in industrial wastewater treatment plants. Members of the genus Defluviicoccus are also known to exhibit the glycogen accumulating organism (GAO) phenotype, which is suggested to be detrimental to enhanced biological phosphorus removal (EBPR). Despite the reported negative impact members of the DF3 have on activated sludge wastewater treatment systems, limited research has focused on understanding the physiological traits that allow them to compete in these environments. In this study, a near complete genome of an abundant filamentous DF3 named 'Candidatus Defluviicoccus seviourii' was obtained from a full-scale sequencing batch reactor (SBR) treating winery wastewater. Annotation of the 'Ca. D. seviourii' genome revealed interesting metabolic features that help to understand the abundance of this microorganism in industrial wastewater treatment plants. Their potential for the storage of polyhydroxyalkanoates (PHA) is suggested to favour these organisms with the intermittent availability of carbon in these systems. An ability to fix nitrogen and take up urea may provide them with an additional advantage with the characteristically high carbon to nitrogen content of industrial waste. The genome and preliminary findings of this study provide a foundation for further research into these biotechnologically relevant organisms.

Optimization aspects of the biological nitrogen removal process in a full-scale twin sequencing batch reactor (SBR) system in series treating landfill leachate

ABSTRACTDespite the fact that biological nitrogen removal (BNR) process has been studied in detail in laboratory- and pilot-scale sequencing batch reactor (SBR) systems treating landfill leachate, a limited number of research works have been performed in full-scale SBR plants regarding nitrification and denitrification. In the current study, a full-scale twin SBR system in series of 700 m3 (350 m3 each) treating medium-age landfill leachate was evaluated in terms of its carbon and nitrogen removal efficiency in the absence and presence of external carbon source, i.e., glycerol from biodiesel production. Both biodegradable organic carbon and ammonia were highly oxidized [biochemical oxygen demand (BOD5) and total Kjehldahl nitrogen (TKN) removal efficiencies above 90%], whereas chemical oxygen demand (COD) removal efficiency was slightly above 40%, which is within the range reported in the literature for pilot-scale SBRs. As the consequence of the high recalcitrant organic fraction of the landfill leachate, dissimilatory nitrate reduction was restricted in the absence of crude glycerol, although denitrification was improved by electron donor addition, resulting in TN removal efficiencies above 70%. Experimental data revealed that the second SBR negligibly contributed to BNR process, since carbon and ammonia oxidation completion was achieved in the first SBR. On the other hand, the low VSS/SS ratio, due to the lack of primary sedimentation, highly improved sludge settleability, resulting in sludge volume indices (SVI) below 30 mL g–1.

Modeling and simulation of the industrial sequencing batch reactor wastewater treatment process for cleaner production in pulp and paper mills

Being an internationally accepted standard for the activated sludge modeling, the Activated Sludge Model No.1 (ASM1) was used to simulate the treatment of paper mills effluent in an industrial full-scale sequencing batch reactor (SBR). Key characteristic parameters were estimated and corrected with the wastewater temperature: maximum heterotrophic growth rate μH (9.69/day), heterotrophic yield YH (0.625 g cell COD/g COD oxidized) and heterotrophic decay rate bH (1.98/day). The wastewater chemical oxygen demand (COD) was fractionated as slowly biodegradable substrate XS (20%), particulate inert organic matter XI (58%), readily biodegradable substrate SS (18%) and soluble inert organic matter SI (4%). Finally, the SBR operation was simulated with field data from the paper mill. The average relative error of the simulated effluent COD was 12.7%. The results showed that the ASM1 could be reasonably used in the papermaking wastewater treatment simulation.

A chemometric analysis on the fluorescent dissolved organic matter in a full-scale sequencing batch reactor for municipal wastewater treatment

Rapid monitoring of water quality is crucial to the operation of municipal wastewater treatment plants (WWTPs). Fluorescence excitation-emission matrix (EEM) in combination with parallel factor analysis (PARAFAC) has been used as a powerful tool for the characterization of dissolved organic matter (DOM) in WWTPs. However, a recent work has revealed the drawback of PARAFAC analysis, i.e., overestimating the component number. A novel method, parallel factor framework-clustering analysis (PFFCA), has been developed in our earlier work to resolve this drawback of PARAFAC. In the present work, both PARAFAC and PFFCAwere used to analyze the EEMs of water samples from a full-scale WWTP from a practical application point of view. The component number and goodness-offit from these two methods were compared and the relationship between the relative score change of component and the actual concentration was investigated to evaluate the estimation error introduced by both methods. PFFCA score and actual concentration exhibited a higher correlation coefficient (R 2 = 0.870) compared with PARAFAC (R 2<0.771), indicating that PFFCA provided a more accurate relative change estimation than PARAFAC. The results suggest that use of PARAFAC may cause confusion in selecting the component number, while EEM-PFFCA is a more reliable alternative approach for monitoring water quality in WWTPs.