Strategies for mitigating nitrous oxide production and decreasing the carbon footprint of a full-scale combined nitrogen and phosphorus removal activated sludge system

Novel extended hybrid tool for real time control and practically support decisions to reduce GHG emissions in full scale wastewater treatment plants

In this paper, a novel methodology and extended hybrid model for the real time control, prediction and reduction of direct emissions of greenhouse gases (GHGs) from wastewater treatment plants (WWTPs) is proposed to overcome the lack of long-term data availability in several full-scale case studies. A mechanistic model (MCM) and a machine learning (ML) model are combined to real time control, predict the emissions of nitrous oxide (N2O) and carbon dioxide (CO2) as well as effluent quality (COD - chemical oxygen demand, NH4-N - ammonia, NO3-N - nitrate) in activated sludge method. For methane (CH4), using the MCM model, predictions are performed on the input data (VFA, CODs for aerobic and anaerobic compartments) to the MLM model. Additionally, scenarios were analyzed to assess and reduce the GHGs emissions related to the biological processes. A real WWTP, with a population equivalent (PE) of 125,000, was studied for the validation of the hybrid model. A global sensitivity analysis (GSA) of the MCM and a ML model were implemented to assess GHGs emission mechanisms the biological reactor. Finally, an early warning tool for the prediction of GHGs errors was implemented to assess the accuracy and the reliability of the proposed algorithm. The results could support the wastewater treatment plant operators to evaluate possible mitigation scenarios (MS) that can reduce direct GHG emissions from WWTPs by up to 21%, while maintaining the final quality standard of the treated effluent.

Comprehensive carbon footprint analysis of wastewater treatment: A case study of modified cyclic activated sludge technology for low carbon source urban wastewater treatment

To reduce pollution and carbon emissions, a quantitative evaluation of the carbon footprint of the wastewater treatment processes is crucial. However, micro carbon element flow analysis is rarely focused considering treatment efficiency of different technology. In this research, a comprehensive carbon footprint analysis is established under the micro carbon element flow analysis and macro carbon footprint analysis based on life cycle assessment (LCA). Three wastewater treatment processes (i.e., anaerobic anoxic oxic, A2O; cyclic activated sludge technology, CAST; modified cyclic activated sludge technology, M-CAST) for low carbon source urban wastewater are selected. The micro key element flow analysis illustrated that carbon source mainly flows to the assimilation function to promote microorganism growth. The carbon footprint analysis illustrated that M-CAST as the optimal wastewater treatment process had the lowest global warming potential (GWP). The key to reduce carbon emissions is to limit electricity consumption in wastewater treatment processes. Under the comprehensive carbon footprint analysis, M-CAST has the lowest environmental impact with low carbon emissions. The sensitivity analysis results revealed that biotreatment section variables considerably reduced the environmental impact on the LCA and the GWP, followed by the sludge disposal section. With this research, the optimization scheme can guide wastewater treatment plants to optimize relevant treatment sections and reduce pollution and carbon emissions.

Direct and indirect monitoring methods for nitrous oxide emissions in full-scale wastewater treatment plants: A critical review

Mitigation of nitrous oxide (N2O) emissions in full-scale wastewater treatment plant (WWTP) has become an irreversible trend to adapt the climate change. Monitoring of N2O emissions plays a fundamental role in understanding and mitigating N2O emissions. This paper provides a comprehensive review of direct and indirect N2O monitoring methods. The techniques, strengths, limitations, and applicable scenarios of various methods are discussed. We conclude that the floating chamber technique is suitable for capturing and interpreting the spatiotemporal variability of real-time N2O emissions, due to its long-term in-situ monitoring capability and high data acquisition frequency. The monitoring duration, location, and frequency should be emphasized to guarantee the accuracy and comparability of acquired data. Calculation by default emission factors (EFs) is efficient when there is a need for ambiguous historical N2O emission accounts of national-scale or regional-scale WWTPs. Using process-specific EFs is beneficial in promoting mitigation pathways that are primarily focused on low-emission process upgrades. Machine learning models exhibit exemplary performance in the prediction of N2O emissions. Integrating mechanistic models with machine learning models can improve their explanatory power and sharpen their predictive precision. The implementation of the synergy of nutrient removal and N2O mitigation strategies necessitates the calibration and validation of multi-path mechanistic models, supported by long-term continuous direct monitoring campaigns.

Modelling greenhouse gas emissions from biological wastewater treatment by GPS-X: The full-scale case study of Corleone (Italy)

Greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) can affect climate change and must be measured and reduced. Mathematical modelling is an attractive solution to get a tool for GHG mitigation. However, although many efforts have been made to create reliable tools that can simulate "sustainable" full-scale WWTP operation, these studies are not considered complete enough to include GHG emissions and energy consumption of biological processes under long-term dynamic conditions. In this study, activated sludge model no. 1 (ASM1) was modified to model nitrous oxide (N2O) emissions with a plant-wide modelling approach. The model is novel compared to the state of the art since it includes three steps denitrification, all N2O production pathways and its stripping in an ASM1. The model has been calibrated and validated through long-term water quality and short-term N2O emissions data collected from Corleone (Italy) WWTP. Different dissolved oxygen (DO) concentrations and return sludge (RAS) ratios were tested with dynamic simulations to optimise the full-scale WWTP. The scenarios have been compared synergistically with effluent quality, direct GHG emissions, and energy footprint by the water-energy‑carbon coupling index (WECCI). This modelling study is novel as it fully covers long-term calibration/validation of the model with N2O measurements and tests the dynamic optimisation. Decision-makers and operators can use this new model to optimise GHG emissions and treatment costs.

Automatic control and optimal operation for greenhouse gas mitigation in sustainable wastewater treatment plants: A review

In order to promote low-carbon sustainable operational management of the wastewater treatment plants (WWTPs), automatic control and optimal operation technologies, which devote to improving effluent quality, operational costs and greenhouse gas (GHG) emissions, have flourished in recent years. There is no consensus on the design procedure for optimal control/operation of sustainable WWTPs. In this review, we summarize recent researches on developing control and optimization strategies for GHG mitigation in WWTPs. Faced with the fact that direct carbon dioxide (CO₂) emissions (considered biological origin) are generally not included in the carbon footprint of WWTPs, direct emissions (nitrous oxide (N₂O), methane (CH₄)) and indirect emissions are paid much attention. Firstly, the plant-wide models with GHG dynamic simulation, which are employed to design and evaluate the automatic control schemes as well as representative studies on identifying key factors affecting GHG emissions or comprehensive performance are outlined. Then, both traditional and advanced control methods commonly used in GHG mitigation are reviewed in detail, followed by the multi-objective optimization practices of control/operational parameters. Based on the mentioned control and (or) optimization strategies, a novel design framework for the optimal control/operation of sustainable WWTPs is proposed. The findings and design framework proposed in the paper will provide guidance for GHG mitigation and sustainable operation in WWTPs. It is foreseeable that more accurate and appropriate plant-wide models together with flexible control methods and intelligent optimization strategies will be developed to satisfy the upgrading requirements of WWTPs in the future.

Modeling nutrient removal and energy consumption in an advanced activated sludge system under uncertainty

Activated sludge models are widely used to simulate, optimize and control performance of wastewater treatment plants (WWTP). For simulation of nutrient removal and energy consumption, kinetic parameters would need to be estimated, which requires an extensive measurement campaign. In this study, a novel methodology is proposed for modeling the performance and energy consumption of a biological nutrient removal activated sludge system under sensitivity and uncertainty. The actual data from the wastewater treatment plant in Slupsk (northern Poland) were used for the analysis. Global sensitivity analysis methods accounting for interactions between kinetic parameters were compared with the local sensitivity approach. An extensive procedure for estimation of kinetic parameters allowed to reduce the computational effort in the uncertainty analysis and improve the reliability of the computational results. Due to high costs of measurement campaigns for model calibration, a modification of the Generalized Likelihood Uncertainty method was applied considering the location of measurement points. The inclusion of nutrient measurements in the aerobic compartment in the uncertainty analysis resulted in percentages of ammonium, nitrate, ortho-phosphate measurements of 81%, 90%, 78%, respectively, in the 95% confidence interval. The additional inclusion of measurements in the anaerobic compartment resulted in an increase in the percentage of ortho-phosphate measurements in the aerobic compartment by 5% in the confidence interval. The developed procedure reduces computational and measurement efforts, while maintaining a high compatibility of the observed data and model predictions. This enables to implement activated sludge models also for the facilities with a limited availability of data.

Diversity and Ecophysiology of the Genus OLB8 and Other Abundant Uncultured Saprospiraceae Genera in Global Wastewater Treatment Systems

The Saprospiraceae family within the phylum Bacteroidota is commonly present and highly abundant in wastewater treatment plants (WWTPs) worldwide, but little is known about its role. In this study, we used MiDAS 4 global survey with samples from 30 countries to analyze the abundance and distribution of members of Saprospiraceae. Phylogenomics were used to delineate five new genera from a set of 31 high-quality metagenome-assembled genomes from Danish WWTPs. Newly designed probes for fluorescence in situ hybridization (FISH) revealed rod-shaped morphologies for all genera analyzed, including OLB8, present mostly inside the activated sludge flocs. The genomes revealed potential metabolic capabilities for the degradation of polysaccharides, proteins, and other complex molecules; partial denitrification; and storage of intracellular polymers (glycogen, polyphosphate, and polyhydroxyalkanoates). FISH in combination with Raman microspectroscopy confirmed the presence of intracellular glycogen in Candidatus Brachybacter, Candidatus Parvibacillus calidus (both from the former genus OLB8), and Candidatus Opimibacter, and the presence of polyhydroxyalkanoates in Candidatus Defluviibacterium haderslevense and Candidatus Vicinibacter. These results provide the first overview of the most abundant novel Saprospiraceae genera present in WWTPs across the world and their potential involvement in nutrient removal and the degradation of macromolecules.

Modeling nitrous oxide emissions in membrane bioreactors: Advancements, challenges and perspectives

Membrane bioreactors (MBRs) have become a well-established wastewater treatment technology owing to their extraordinary efficiency and low space advantage over conventional activated sludge processes. Although the extended activated sludge models can predict the general trend of nitrous oxide (N₂O) emissions in MBRs, the simulation results usually deviate from the actual values. This review critically evaluates the recent advances in the modeling of N₂O emissions in MBRs, and proposes future directions for the development and improvement of models that better match the MBR characteristics. The quantitative impact of MBR characteristics on N₂O emissions is identified as a key knowledge gap demanding urgent attention. Accurately clarification of the N₂O emission pathways governed by MBR characteristics is essential to improve the reliability and practicability of existing models. This article lays a momentous foundation for the optimization of N₂O models in MBRs, and proposes new demands for the next-generation model. The contents will assist academics and engineers in developing N₂O production models for accurate prediction.

Enhanced proteins and amino acids production based on ammonia nitrogen assimilation and sludge increment by the integration of bioadsorption with anaerobic-anoxic-oxic (AAO) process

Poor effect of contaminants removal efficiency and low organic matter content of activated sludge are common in wastewater treatment plants (WWTPs) in China due to the low-strength wastewater. An anaerobic-anoxic-oxic (AAO) and an adsorption/AAO (A/AAO) combined system were established simultaneously to conduct a comparative study for realizing the conversion of carbon source in influent and the enrichment and recovery of proteins and amino acids through the assimilation of ammonia nitrogen. The experimental results showed that 63.5% of the organic matter in influent was adsorbed and flocculated in adsorption process, and the removal rates of chemical oxygen demand, total nitrogen and total phosphorus in A/AAO process were 88.7%, 77.1%, and 93.0% respectively, which were remarkably better than those in AAO process owing to the addition of improved carbon source. Ammonia assimilation rate of A/AAO process was 26.7% higher than that of AAO process, which implied that the ammonia used to synthesize sludge protein was prominently increased. Furthermore, intracellular proteins and amino acids in A/AAO process were 20% higher than those of AAO process, and the quality was equivalent with fish meal or soybean meal as feed. In addition, the microbial community analysis based on 16S rDNA was conducted. Dechloromonas, Zoogloea, Nitrospira, and Flavobacterium were the main genera, and played important roles in nutrient removal and ammonia nitrogen assimilation. The integration of adsorption process was significant to low-strength wastewater treatment and the improvement of excess sludge quality, which is a prospective inspiration for the resource recovery-based wastewater treatment process.

First evaluation of wastewater discharge influence on marine water contamination in the vicinity of Arctowski Station (Maritime Antarctica)

In Antarctica, waste is generated mainly during scientific research programmes and related logistics. In this study, the impact of wastewater on the western shore of Admiralty Bay was investigated during austral summer in 2017 and 2019. A range of physicochemical parameters and the presence of selected trace metals, formaldehyde and different groups of surfactants were determined in wastewater coming from Arctowski Station and in nearby coastal waters. The presence of selected trace metals (e.g., Cr: 2.7-4.4 μg/L; Zn: 15.2-37.3 μg/L; and Ni: 0.9-23.3 μg/L) and the sums of cationic (0.3-1.5 mg/L), anionic (3.1-1.7 mg/L), and non-ionic (0.6-2.4 mg/L) surfactants in wastewater indicated the potential influence of anthropogenic factors on sea water. The determined surfactants are found in many hygiene products that end up in the waste water tank after human use and, if untreated, can be released into surface waters with discharge. In addition, the levels of some trace metals indicate that they cannot come only from natural sources, but are the result of human activity. The reported data show disturbances in the marine environment caused by non-treated wastewater discharge, e.g. by comparing the obtained results from the values of the no observed effect concentrations (NOECs) on selected Antarctic bioindicators, and provide information for the implementation of proper wastewater treatment at any Antarctic station in the future.

Treatment efficiency and greenhouse gas emissions of non-floating and floating bed activated sludge system with acclimatized sludge treating landfill leachate

This research investigates the treatment efficiency and greenhouse gas (GHG) emissions of non-floating and floating bed AS systems with acclimatized sludge treating landfill leachate. The GHGs under study included carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). The non-floating and floating bed AS systems were operated in parallel with identical landfill leachate influent under different hydraulic retention time (HRT) conditions (24, 18, and 12 h). The experimental results showed that the treatment efficiency of organic compounds under 24 h HRT of both systems (90 - 98%) were insignificantly different, while the nutrient removal efficiency of both systems were between 54 and 98 %. The treatment efficiency of the floating bed AS system, despite shorter HRT, remained relatively unchanged due to an abundance of effective bacteria residing in the floating media. The CO₂ emissions were insignificantly different between both AS systems under all HRT conditions (22 - 26.3 μmol/cm².min). The CO₂ emissions were positively correlated with organic loading but inversely correlated with HRT. The CH₄ emissions were positively correlated with HRT (26.3 μmol/cm².min under 24 h HRT of the floating bed AS system). The N₂O emissions were positively correlated with nitrogen loading, and the N₂O emissions from the floating bed AS system were lower due to an abundance of N₂O-reducing bacteria. The floating media enhanced the biological treatment efficiency while maintaining the bacterial community in the system. However, the floating media promoted CH₄ production under anoxic conditions. The originality of this research lies in the use of floating media in the biological treatment system to mitigate GHG emissions, unlike existing research which focused primarily on enhancement of the treatment efficiency.

Insights into Nitrous Oxide Mitigation Strategies in Wastewater Treatment and Challenges for Wider Implementation

Nitrous oxide (N₂O) emissions account for the majority of the carbon footprint of wastewater treatment plants (WWTPs). Many N₂O mitigation strategies have since been developed while a holistic view is still missing. This article reviews the state-of-the-art of N₂O mitigation studies in wastewater treatment. Through analyzing existing studies, this article presents the essential knowledge to guide N₂O mitigations, and the logics behind mitigation strategies. In practice, mitigations are mainly carried out by aeration control, feed scheme optimization, and process optimization. Despite increasingly more studies, real implementation remains rare, which is a combined result of unclear climate change policies/incentives, as well as technical challenges. Five critical technical challenges, as well as opportunities, of N₂O mitigations were identified. It is proposed that (i) quantification methods for overall N₂O emissions and pathway contributions need improvement; (ii) a reliable while straightforward mathematical model is required to quantify benefits and compare mitigation strategies; (iii) tailored risk assessment needs to be conducted for WWTPs, in which more long-term full-scale trials of N₂O mitigation are urgently needed to enable robust assessments of the resulting operational costs and impact on nutrient removal performance; (iv) current mitigation strategies focus on centralized WWTPs, more investigations are warranted for decentralised systems, especially decentralized activated sludge WWTPs; and (v) N₂O may be mitigated by adopting novel strategies promoting N₂O reduction denitrification or microorganisms that emit less N₂O. Overall, we conclude N₂O mitigation research is reaching a maturity while challenges still exist for a wider implementation, especially in relation to the reliability of N₂O mitigation strategies and potential risks to nutrient removal performances of WWTPs.

Integrated Model for Understanding N2O Emissions from Wastewater Treatment Plants: A Deep Learning Approach

This study aims to demonstrate the application of deep learning to quantitatively describe long-term full-scale data observed from wastewater treatment plants (WWTPs) from the perspectives of process modeling, process analysis, and forecasting modeling. Approximately, 750,000 measurements including the influent flow rate, air flow rate, temperature, ammonium, nitrate, dissolved oxygen, and nitrous oxide (N₂O) collected for more than a year from the Avedøre WWTP located in Denmark are utilized to develop a deep neural network (DNN) through supervised learning for process modeling, and the optimal DNN (R² > 0.90) is selected for further evaluation. For process analysis, global sensitivity analysis based on variance decomposition is considered to identify the key parameters contributing to high N₂O emission characteristics. For N₂O forecasting, the proposed DNN-based model is compared with long short-term memory (LSTM), showing that the LSTM-based forecasting model performs significantly better than the DNN-based model (R² > 0.94 and the root-mean-squared error is reduced by 64%). The results account for the feasibility of data-driven methods based on deep learning for quantitatively describing and understanding the rather complex N₂O dynamics in WWTPs. Research into hybrid modeling concepts integrating mechanistic models of WWTPs (e.g., ASMs) with deep learning would be suggested as a future direction for monitoring N₂O emissions from WWTPs.

Optimization of the Aeration Strategies in a Deammonification Sequencing Batch Reactor for Efficient Nitrogen Removal and Mitigation of N2O Production

In deammonification systems, nitrite-oxidizing bacteria (NOB) suppression and nitrous oxide (N₂O) mitigation are two important operational objectives. To carry out this multivariable analysis of response, a comprehensive model for the N cycle was developed and evaluated against experimental data from a laboratory-scale deammonification granular sludge sequencing batch reactor. Different aeration strategies were tested, and the manipulated variables comprised the dissolved oxygen (DO) set point in the aerated phase, aeration on/off frequency (F), and the ratio (R) between the non-aerated and aerated phase durations. Experimental results showed that a high ammonium utilization rate (AUR) in relation to the low nitrate production rate (NPR) (NPR/AUR = 0.07-0.08) and limited N₂O emissions (E_N2O < 2%) could be achieved at the DO set point = 0.7 mg O₂/L, R ratio = 2, and F frequency = 6-7 h^-1. Under specific operational conditions (biomass concentration, NH₄⁺-N loading rate, and temperature), simulation results confirmed the feasible aeration strategies for the trade-offs between the NOB suppression and N₂O emission. The intermittent aeration regimes led to frequent shifts in the predominating N₂O production pathways, that is, hydroxylamine (NH₂OH) oxidation (aerated phase) versus autotrophic denitrification (non-aerated phase). The inclusion of the extracellular polymeric substance mechanism in the model explained the observed activity of heterotrophs, especially Anaerolineae, and granule formation.

Activated sludge and other aerobic suspended culture processes

This paper provides an overview of activated sludge related to suspended growth processes for the year 2019. The review encompasses process modeling of activated sludge, microbiology of activated sludge, process kinetics and mechanism, nitrogen and phosphorus control, design, and operation in the activated sludge field. The fate and effect of xenobiotics in activated sludge, including trace organic contaminant and heavy metal xenobiotics, which had influence on the growth of suspended sludge, are covered in this review. Compared to past reviews, many topics show increase in activity in 2019. These include, biokinetics process of aerobic granular sludge formation, pyrolysis kinetic mechanism of granular sludge. These topics are referred to formation and disintegration of granular sludge. Other sections include activated sludge settling model, toxicity resistant microbial community, nitritation-anammox processes for nitrogen removal, and respirometry used in the operation of real wastewater treatment plant are especially highlighted in this review. PRACTITIONER POINTS: Biokinetics process of aerobic granular sludge formation Toxicity resistant microbial community in activated sludge Nitritation-anammox processes for nitrogen removal in activated sludge.

Recent advances in nitrous oxide production and mitigation in wastewater treatment

Nitrous oxide (N₂O) emitted from wastewater treatment plants has caused widespread concern. Over the past decade, people have made tremendous efforts to discover the microorganisms responsible for N₂O production, elucidate metabolic pathways, establish production models and formulate mitigation strategies. The ultimate goal of all these efforts is to shed new light on how N₂O is produced and how to reduce it, and one of the best ways is to find key opportunities by integrating the information obtained. This review article critically evaluates the knowledge gained in the field within a decade, especially in N₂O production microbiology, biochemistry, models and mitigation strategies, with a focus on denitrification. Previous research has greatly deepened the understanding of the N₂O generation mechanism, but further efforts are still needed due to the lack of standardized methodology for establishing N₂O mitigation strategies in full-scale systems. One of the challenges seems to be to convert the denitrification process from a net N₂O source into an effective sink, which is recommended as a key opportunity to reduce N₂O production in this review.

Influence of chlortetracycline as an antibiotic residue on nitrous oxide emissions from wastewater treatment

Strengthening the removal of antibiotics in wastewater treatment plants is a research focus, but whether antibiotics affect nitrous oxide (N₂O) emissions from wastewater treatment remains to be determined. In this study, the effect of chlortetracycline (CTC) on N₂O emissions in anaerobic/oxic/anoxic sequential batch reactors was investigated. Experimental results show that CTC promotes N₂O emissions during biological nutrient removal. The addition of 0.1 mg/L CTC increased the N₂O emission factor by 41.4% compared to the control. Mechanism exploration shows that CTC stimulates the release of extracellular polymeric substance (EPS) and binds to it, the generated EPS-CTC conjugates hinder or expand the mass transfer channel, which intensifies the electronic competition between oxidoreductases and the substrate competition between microorganisms, resulting in incomplete denitrification and nitrite accumulation, thereby increasing N₂O emissions.

Paradigm shifts and current challenges in wastewater management

Wastewater is a significant environmental and public health concern which management is a constant challenge since antiquity. Wastewater research has increased exponentially over the last decades. This paper provides a global overview of the exponentially increasing wastewater research in order to identify current challenges and paradigm shifts. Besides households, hospitals and typical industries, other sources of wastewater appear due to emerging activities like hydraulic fracturing. While the composition of wastewater needs constant reassessment to identify contaminants of interest, the comprehensive chemical and toxicological analysis remains one of the main challenges in wastewater research. Moreover, recent changes in the public perception of wastewater has led to several paradigm shifts: i) water reuse considering wastewater as a water resource rather than a hazardous waste, ii) wastewater-based epidemiology considering wastewater as a source of information regarding the overall health of a population through the analysis of specific biomarkers, iii) circular economy through the implementation of treatment processes aiming at harvesting valuable components such as precious metals or producing valuable goods such as biofuel. However, wastewater research should also address social challenges such as the public acceptance of water reuse or the access to basic sanitation that is not available for nearly a third of the world population.