Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes

Reutilization of post-adsorption lanthanum-loaded straw alleviates phosphorus pollution in rice-wheat system: Subsequent performance and underlying mechanisms

Adsorption technology for phosphorus (P) removal is considered promising and reutilization of post-adsorbent can contribute to promoting sustainable agricultural production. However, the long-lasting impact of the post-adsorbent on crop growth and P remains unclear. This study assessed the effects of P-adsorbed lanthanum-modified straw (La@straw-P) on the rice yield, P fractionation and associated water quality parameters. The findings indicated that, compared with traditional fertilizer regimes, La@straw-P expedited the P reduction in the flooding water achieving a rate of decline to the tertiary standard for surface water (0.20 mg/L) 3.8 times faster and enhanced increased the P harvest index by 17.00 %. Economic estimation proved the positive benefits of La@straw-P in planting-breeding combination system. Redundancy analysis (RDA) and co-occurrence network analysis (CONA) revealed that electrical conductivity (EC) and dissolved Fe played primary roles in regulating total P. Fourier transform infrared spectra (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectra (XPS), and soil P fractions collectively demonstrated that the abundant adsorption sites on La@straw-P could facilitate the transformation of active P into moderately Ca-bound P. This study proposes a strategy for recycling P-adsorbed materials to mitigate agricultural non-point P pollution.

Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches

In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.

Digitalization of phosphorous removal process in biological wastewater treatment systems: Challenges, and way forward

Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.

Dead in the water - Role of relic DNA and primer choice for targeted sequencing surveys of anaerobic sewage sludge intended for biological monitoring

DNA-based monitoring of microbial communities that are responsible for the performance of anaerobic digestion of sewage wastes has the potential to improve resource recoveries for wastewater treatment facilities. By treating sludge with propidium monoazide (PMA) prior to amplicon sequencing, this study explored how the presence of DNA from dead microbial biomass carried over with feed sludge may mislead process-relevant biomarkers, and whether primer choice impacts such assessments. Four common primers were selected for amplicon preparation, also to determine if universal primers have sufficient taxonomic or functional coverage for monitoring ecological performance; or whether two domain-specific primers for Bacteria and Archaea are necessary. Anaerobic sludges of three municipal continuously stirred-tank reactors in Victoria, Australia, were sampled at one time-point. A total of 240 amplicon libraries were sequenced on a Miseq using two universal and two domain-specific primer pairs. Untargeted metabolomics was chosen to complement biological interpretation of amplicon gene-based functional predictions. Diversity, taxonomy, phylogeny and functional potentials were systematically assessed using PICRUSt2, which can predict community wide pathway abundance. The two chosen universal primers provided similar diversity profiles of abundant Bacteria and Archaea, compared to the domain-specific primers. About 16 % of all detected prokaryotic genera covering 30 % of total abundances and 6 % of PICRUSt2-estimated pathway abundances were affected by PMA. This showed that dead biomass in the anaerobic digesters impacted DNA-based assessments, with implications for predicting active processes, such as methanogenesis, denitrification or the identification of organisms associated with biological foams. Hence, instead of running two sequencing runs with two different domain-specific primers, we propose conducting PMA-seq with universal primer pairs for routine performance monitoring. However, dead sludge biomass may have some predictive value. In principal component analysis the compositional variation of 239 sludge metabolites resembled that of 'dead-plus-alive' biomass, suggesting that dead organisms contributed to the potentially process-relevant sludge metabolome.

Rapid characterization of sulfur and phosphorus in organic waste by near infrared spectroscopy

Near-infrared spectroscopy (NIRS) has recently emerged as a valuable tool for monitoring organic waste utilized in anaerobic digestion processes. Over the past decade, NIRS has significantly improved the characterization of organic waste by enabling the prediction of several crucial parameters such as biochemical methane potential, carbohydrate, lipid and nitrogen contents, Chemical Oxygen Demand, and kinetic parameters. This study investigates the application of NIRS for predicting the levels of Sulfur (S) and Phosphorus (P) within organic waste materials. The results for sulfur prediction exhibited a high level of accuracy, yielding an error of 1.21 g/Kg[TS] in an independently validated dataset, coupled with an R-squared value of 0.84. Conversely, the prediction of phosphorus proved to be slightly less successful, showing an error of 1.49 g/Kg[TS] with an R-squared value of 0.70. Furthermore, the disparities in performance seem to stem from the inherent correlation between the spectral data and the sulfur or phosphorus contents. Significantly, a variable selection technique known as CovSel was employed, shedding light on the differing approaches used for sulfur and phosphorus predictions. In the case of sulfur, the prediction was achieved through a direct correlation with wavelengths associated with sulfur-related functional groups (such as R - S(=O)2 - OH, -SH, and R-S-S-R) present in the NIR spectra. In contrast, phosphorus prediction relied on an indirect correlation with absorption bands related to organic matter (including CH, CH2, CH3, -CHO, R-OH, C = O, -CO2H, and CONH).

Modifications to the anaerobic digestion model no. 1 (ADM1) for enhanced understanding and application of the anaerobic treatment processes - A comprehensive review

Anaerobic digestion (AD) is a promising method for the recovery of resources and energy from organic wastes. Correspondingly, AD modelling has also been developed in recent years. The International Water Association (IWA) Anaerobic Digestion Model No. 1 (ADM1) is currently the most commonly used structured AD model. However, as substrates become more complex and our understanding of the AD mechanism grows, both systematic and specific modifications have been applied to the ADM1. Modified models have provided a diverse range of application besides AD processes, such as fermentation and biogas upgrading processes. This paper reviews research on the modification of the ADM1, with a particular focus on processes, kinetics, stoichiometry and parameters, which are the major elements of the model. The paper begins with a brief introduction to the ADM1, followed by a summary of modifications, including extensions to the model structure, modifications to kinetics (including inhibition functions) and stoichiometry, as well as simplifications to the model. The paper also covers kinetic parameter estimation and validation of the model, as well as practical applications of the model to a variety of scenarios. The review highlights the need for improvements in simulating AD and biogas upgrading processes, as well as the lack of full-scale applications to other substrates besides sludge (such as food waste and agricultural waste). Future research directions are suggested for model development based on detailed understanding of the anaerobic treatment mechanisms, and the need to recover of valuable products.

CFD simulation of anaerobic granular sludge reactors: A review

Anaerobic digestion processes can generate renewable energy in the form of biogas while treating organic wastewater. The generation of biogas within anaerobic digestion systems is directly linked to the mixing conditions inside the reactors. In high-rate reactors such as the upflow anaerobic sludge blanket (UASB) reactor, the expanded granular sludge bed (EGSB) reactor and the internal circulation (IC) reactor, the hydrodynamic behaviour will depend on the interactions between the wastewater, the biogas, and the biomass granules. Over the past few years, various researchers have used computational fluid dynamics (CFD) to study the hydrodynamic behaviour in these types of reactors. This review aims to present and critically discuss the state of the art in the use of CFD applied to anaerobic granular sludge reactors (AGSRs). It briefly introduces and discusses the various aspects of modelling. It also reviews the various papers which used CFD to model these reactors and critically analyses the models used for the simulations in terms of general approaches and single-phase vs multiphase studies. The methods used in the validation of the CFD models are also described and discussed. Based on the findings, the challenges and future perspectives for the CFD modelling of AGSRs are discussed and gaps in the knowledge are identified.

Dynamic modelling the effects of ionic strength and ion complexation on trace metal speciation during anaerobic digestion

Dosing trace metals into anaerobic digestors is proven to improve biogas production rate and yield by stimulating microorganisms involved in the metabolic pathways. Trace metal effects are governed by metal speciation and bioavailability. Though chemical equilibrium speciation models are well-established and widely used to understand metal speciation, the development of kinetic models considering biological and physicochemical processes has recently gained attention. This work proposes a dynamic model for metal speciation during anaerobic digestion which is based on a system of ordinary differential equations aimed to describe the kinetics of biological, precipitation/dissolution, gas transfer processes and, a system of algebraic equations to define fast ion complexation processes. The model also considers ion activity corrections to define effects of ionic strength. Results from this study shows the inaccuracy in predicting trace metal effects on anaerobic digestion by typical metal speciation models and the significance of considering non-ideal aqueous phase chemistry (ionic strength and ion pairing/complexation) to define speciation and metal labile fractions. Model results show a decrease in metal precipitation and increase in metal dissolved fraction and methane production yield with increase in ionic strength. Capability of the model to dynamically predict trace metal effects on anaerobic digestion under different conditions, like changing dosing conditions and initial iron to sulphide ratio, was also tested and verified. Dosing iron increases methane production and decreases hydrogen sulphide production. However, when iron to sulphide ratio is greater than 1, methane production decreases due to increase in dissolved iron which reaches inhibitory concentration levels.

Assessment of groundwater-driven dissolved nutrient inputs to coastal wetlands associated with marsh-coastal lagoons systems of the littoral of the outer Río de la Plata estuary

In coastal wetlands the hydrological dynamics and in particular the groundwater flows play a critical role in the establishment of wetlands and in the transport of salts and nutrients. The aim of the work is to analyze the role that groundwater discharge has in the dynamics of the dissolved nutrients of the wetland associated with the coastal lagoon and marshes of the Punta Rasa Natural Reserve, which is located on the coastal sector of the southern end of the Río de la Plata estuary. A monitoring network in the form of transects was generated in order to define groundwater flows and take samples of dissolved species of N and P. The presence of sandy sediments with similar granulometric profiles in all geomorphological environments determines that the underground flow occurs in a homogeneous aquifer. From the dunes and beach ridges the fresh to brackish groundwater flows with a very low hydraulic gradient towards the marsh and coastal lagoon. The contributions of N and P would derive from the degradation of the organic matter of the environment, in the case of the marsh and coastal lagoon also from the tidal flow and discharge of groundwater, and possibly from atmospheric sources in the case of N. Since in all environments oxidizing conditions dominate, nitrification is the main process which is why the most abundant species of N is the NO₃^-. Under oxidizing conditions, P has a greater affinity for the sediments in which it is mostly retained, registering it in low concentrations in water. The discharge of groundwater from the dunes and beach ridges provides dissolved nutrients to the marsh and coastal lagoon. However, the low hydraulic gradient and the dominant oxidizing conditions determine that the flow is scarce and that it only acquires relevance in the contribution of NO₃^-.

Energy-neutral municipal wastewater treatment based on partial denitrification-anammox driven by side-stream sulphide

"Low-carbon" has become an important evaluation index of modernisation construction. In the area of wastewater treatment has also caused considerable concern. Anaerobic ammonium oxidation (anammox) is a novel autotrophic nitrogen removal process that provides an opportunity for low-carbon remodelling of municipal wastewater treatment plants (MWTPs). The stable supply of nitrite is of great significance for the application of anammox. As a process with stable nitrite supply, partial denitrification (PD) is of great significance in the coupling nitrogen removal with anammox in municipal wastewater. Furthermore, innovation of the low-carbon nitrogen removal process can enable the recovery of abundant bioenergy resource from MWTPs. The low-carbon nitrogen removal via PD-anammox process and the bioenergy recovery for municipal wastewater in the previous studies has been summarised. On this basis, a novel energy-neutralisation municipal wastewater treatment process based on partial denitrification-anammox driven by sulphide produced in the side-stream has been proposed. The long-term retention of mainstream anammox and improvement of energy recovery efficiency under the requirement of ensuring nitrogen removal require additional detailed investigation.

Closing the Nutrient Loop-The New Approaches to Recovering Biomass Minerals during the Biorefinery Processes

The recovery of plant mineral nutrients from the bio-based value chains is essential for a sustainable, circular bioeconomy, wherein resources are (re)used sustainably. The widest used approach is to recover plant nutrients on the last stage of biomass utilization processes-e.g., from ash, wastewater, or anaerobic digestate. The best approach is to recover mineral nutrients from the initial stages of biomass biorefinery, especially during biomass pre-treatments. Our paper aims to evaluate the nutrient recovery solutions from a trans-sectorial perspective, including biomass processing and the agricultural use of recovered nutrients. Several solutions integrated with the biomass pre-treatment stage, such as leaching/bioleaching, recovery from pre-treatment neoteric solvents, ionic liquids (ILs), and deep eutectic solvents (DESs) or integrated with hydrothermal treatments are discussed. Reducing mineral contents on silicon, phosphorus, and nitrogen biomass before the core biorefinery processes improves processability and yield and reduces corrosion and fouling effects. The recovered minerals are used as bio-based fertilizers or as silica-based plant biostimulants, with economic and environmental benefits.

Moderate salinity improves the availability of soil P by regulating P-cycling microbial communities in coastal wetlands

Accelerated sea-level rise is expected to cause the salinization of freshwater wetlands, but the responses to salinity of the availability of soil phosphorus (P) and of microbial genes involved in the cycling of P remain unexplored. We conducted a field experiment to investigate the effects of salinity on P cycling by soil microbial communities and their regulatory roles on P availability in coastal freshwater and brackish wetlands. Salinity was positively correlated with P availability, with higher concentrations of labile P but lower concentrations of moderately labile P in the brackish wetland. The diversity and richness of microbial communities involved in P cycling were higher in the brackish wetland than the freshwater wetland. Salinity substantially altered the composition of the P-cycling microbial community, in which those of the brackish wetland were separated from those of the freshwater wetland. Metagenomic sequence analysis indicated that functional genes involved in the solubilization of inorganic P and the subsequent transport and regulation of P were more abundant in coastal soils. The relative abundances of most of the target genes differed between the wetlands, with higher abundances of P-solubilization (gcd and ppa) and -mineralization (phoD, phy, and ugpQ) genes and lower abundances of P-transport genes (pstB, ugpA, ugpB, ugpE, and pit) in the brackish wetland. A significant positive correlation between the concentration of labile P and the abundances of the target genes suggested that salinity may, at least in part, improve P availability by regulating the P-cycling microbial community. Our results suggest that the P-cycling microbial community abundance and P availability respond positively to moderate increases in salinity by promoting the microbial solubilization and mineralization of soil P. Changes in microbial communities and microbially mediated P cycling may represent microbial strategies to adapt to moderate salinity levels, which in turn control soil function and nutrient balance.

Gamma distribution function to understand anaerobic digestion kinetics: Kinetic constants are not constant

The Gamma model is a novel approach to characterise the complex degradation dynamics taking place during anaerobic digestion. This three parameters model results from combining the first-order kinetic model and the Gamma distribution function. In contrast to conventional models, where the kinetic constant is considered invariant, the Gamma model allows analysing the variability of the kinetic constant using a probability density function. The kinetic constant of mono-digestion and co-digestion batch tests of different wastes were modelled using the Gamma model and two common first-order models: one-step one-fraction model and one-step two-fraction model. The Gamma distribution function approximates three distinct probability density functions, i.e. exponential, log-normal, and delta Dirac. Specifically, (i) cattle paunch and pig manure approximated a log-normal distribution; (ii) cattle manure and microalgae approximated an exponential distribution, and (iii) primary sludge and cellulose approximated a delta Dirac distribution. The Gamma model was able to characterise two distinct waste activated sludge, one approximated to a log-normal distribution and the other to an exponential distribution. The same cellulose was tested with two different inocula; in both tests, the Gamma distribution function approximated a delta Dirac function but with a different kinetic value. The potential and consistency of Gamma model were also evident when analysing pig manure and microalgae co-digestion batch tests since (i) the mean k of the co-digestion tests were within the values of the mono-digestion tests, and (ii) the profile of the density function transitioned from log-normal to exponential distribution as the percentage of microalgae in the mixture increased.

Economic, technical, and environmental evaluation of retrofitting scenarios in a full-scale industrial wastewater treatment system

The use of mathematical models is a well-established procedure in the field of (waste) water engineering to "virtually" evaluate the feasibility of novel process modifications. In this way, only options with the highest chance of success are further developed to be implemented at full-scale, while less interesting proposals can be disregarded at an early stage. Nevertheless, there is still lack of studies, where different plant-wide model predictions (effluent quality, process economics, and technical aspects) are comprehensibly verified in the field with full-scale data. In this work, a set of analysis/evaluation tools are used to assess alternative retrofitting options in the largest industrial wastewater treatment plant in Northern Europe. A mechanistic mathematical model is simulated to reproduce process behavior (deviation < 11%). Multiple criteria are defined and verified with plant data (deviation < 5%). The feasibility of three types of scenarios is tested: (1) stream refluxing, (2) change of operational conditions and (3) the implementation of new technologies. Experimental measurements and computer simulations show that the current plant´s main revenues are obtained from the electricity produced by the biogas engine (54%) and sales of the inactivated bio-solids for off-site biogas production (33%). The main expenditures are the discharge fee (39%), and transportation and handling of bio-solids (30%). Selective treatment of bio-solid streams strongly modifies the fate of COD and N compounds within the plant. In addition, it increases revenues (+3%), reduces cost (-9%) and liberates capacity in both activated sludge (+25%) and inactivation reactors (+50%). Better management of the buffer tank promotes heterotrophic denitrification instead of dissimilatory nitrate conversion to ammonia. In this way, 11% of the incoming nitrogen is removed within the anaerobic water line and does not overload the activated sludge reactors. Only a marginal increase in process performance is achieved when the anaerobic granular sludge reactor operates at full capacity. The latter reveals that influent biodegradability is the main limiting factor rather than volume. Usage of either NaOH or heat (instead of CaO) as inactivation agents allows anaerobic treatment of the reject water, which substantially benefits revenues derived from higher electricity recovery (+44%). However, there is a high toll paid on chemicals (+73%) or heat recovery (-19%) depending on the inactivation technology. In addition, partial nitration/Anammox and a better poly-aluminum chloride (PAC) dosage strategy is necessary to achieve acceptable (< 2%) N and P levels in the effluent. The scenarios are evaluated from a sustainability angle by using life cycle impact assessment (LCIA) in form of damage stressors grouped into three categories: human health, ecosystems quality, and resource scarcity. The presented decision support tool has been used by the biotech company involved in the study to support decision-making on how to handle future expansions.

Life Cycle Environmental Impacts of Wastewater-Derived Phosphorus Products: An Agricultural End-User Perspective

Recovering phosphorus from wastewater in more concentrated forms has potential to sustainably recirculate phosphorus from cities to agriculture. The environmental sustainability of wastewater-based phosphorus recovery processes or wastewater-derived phosphorus products can be evaluated using life cycle assessment (LCA). Many LCA studies used a process perspective to account for the impacts of integrating phosphorus recovery processes at wastewater treatment plants, while some used a product perspective to assess the impacts of producing wastewater-derived phosphorus products. We demonstrated the application of an end-user perspective by assessing life cycle environmental impacts of substituting half of the conventional phosphorus rock-based fertilizers used in three crop production systems with wastewater-derived phosphorus products from six recovery pathways (RPs). The consequential LCA results show that the substitution reduces global warming potential, eutrophication potential, ecotoxicity potential, and acidification potential of the assessed crop production systems in most RPs and scenarios. The end-user perspective introduced in this study can (i) complement with the process perspective and the product perspective to give a more holistic picture of environmental impacts along the "circular economy value chains" of wastewater-based resource recovery, (ii) enable systemwide assessment of wide uptake of wastewater-derived products, and (iii) draw attention to understanding the long-term environmental impacts of using wastewater-derived products.

Consideration of biological and inorganic additives in upgraded anaerobic digestion BioModel

This paper deals with the numerical simulation of biogas production in the anaerobic digestion process of organic waste. Special attention is focused on the modeling of the activities of biological and inorganic additives, which are used to enhance the process and reduce H₂S content in the biogas. For this purpose, an existing BioModel is upgraded with the modified Michaelis-Menten kinetics in order to model the enzymatic hydrolysis and with adequate modeling of physicochemical processes. The upgraded BioModel was calibrated with experimental data obtained from a full-scale biogas plant, used in combination with an active set optimization procedure; the relative agreement indices were 0.9376, 0.9419, 0.7957, and 0.7663 for biogas, CH₄, H₂, and H₂S flow rates, respectively. Statistical efficiency criteria differ up to 5% in model calibration and validation. The obtained results confirm the importance of additives modeling and the usefulness of the proposed model for industrial biogas plants' performance improvement.

Biogeochemical behavior of P in the soil and porewater of a low-salinity estuarine wetland: Availability, diffusion kinetics, and mobilization mechanism

Estuarine wetlands, which typically store large amounts of phosphorus (P), are experiencing increased salinity as well as changed environmental factors caused by rising sea levels. In this study, the seasonal dynamics of P speciation, availability, and biogeochemical couplings with iron (Fe)-sulfur (S) in soil and porewater were measured in a low-salinity estuarine wetland using in situ high-resolution diffusive gradients in thin films (DGT) and dialysis (HR-Peeper) techniques. The diffusion kinetics and resupply capacity of P from the soil phase to solution were simulated using a DGT-induced fluxes in soils (DIFS) model. The transition from freshwater to brackish wetlands reduced soil P pools and shifted to more recalcitrant speciation. The concentration of DGT-labile P across the soil-water profiles ranged from 0.002 to 0.039 (mean: 0.015) mg L^-1, which increased with increasing salinity in both the field and mesocosm experiments. The distributions of labile and soluble P showed high heterogeneity across the profiles, and there were some sharp peak values below the soil-water interface (SWI), which significantly increased the concentration and lability of P. The strong coupling between labile P and Fe (S) provided direct evidence for the coexistence of iron reduction (IR) and sulfate reduction (SR) in the estuary, while IR might predominate in P mobilization in the brackish environment because of higher labile Fe concentrations and stronger Fe-P couplings. The diffusion fluxes of P were positive at both sites, demonstrating that the kinetics of P were from the soils to the overlying water. Higher R and k_-1 values fitted in the DIFS model implied that a stronger resupply capacity and desorption rate and thus faster remobilization kinetics of P occurred with increasing salinity. Our findings indicated that increased salinity (even at low levels) can alter the desorption rate and resupply capacity of soil P in estuarine wetlands and accelerate P remobilization and release by regulating the IR and SR processes, thereby leading to the deterioration of water quality.

Plant-wide assessment of alternative activated sludge configurations for biological nutrient removal under uncertain influent characteristics

This study presents an extensive plant-wide model-based assessment of four alternative activated sludge (AS) configurations for biological nitrogen (N) and phosphorus (P) removal under uncertain influent loads and characteristics. Zeekoegat wastewater treatment plant (WWTP) in South Africa was chosen as case study due to its flexible design that enables operation in four different AS configurations: 3-stage Bardenpho (A2O), University of Cape Town (UCT), UCT modified (UCTM), and Johannesburg (JHB). A metamodeling based global sensitivity analysis was performed on a steady-state plant-wide simulation model using Activated Sludge Model No. 2d with the latest extension of physico-chemical processes describing the plant-wide P transformations. The simulation results showed that the predictions of effluent chemical oxygen demand (COD), N and P using the proposed approach fall within the interquartile range of measured data. The study also revealed that process configuration can affect: 1) how influent uncertainty is reflected in model predictions for effluent quality and cost related performances, and 2) the parameter rankings based on variance decomposition, particularly for effluent phosphate, sludge disposal and methane production. The results identified UCT and UCTM as more robust configurations for P removal (less propagated uncertainty and less sensitivity to N load) in the expense of incomplete denitrification. Moreover, based on the results of Monte-Carlo based scenario analysis, the balanced SRT for N and P removal is more sensitive to influent load variation/uncertainty for the A2O and JHB configurations. This gives a more operational flexibility to UCT and UCTM, where a narrow SRT range can ensure both N and P removal.

A plant-wide model describing GHG emissions and nutrient recovery options for water resource recovery facilities

In this study, a plant-wide model describing the fate of C, N and P compounds, upgraded to account for (on-site/off-site) greenhouse gas (GHG) emissions, was implemented within the International Water Association (IWA) Benchmarking Simulation Model No. 2 (BSM2) framework. The proposed approach includes the main biological N₂O production pathways and mechanistically describes CO₂ (biogenic/non-biogenic) emissions in the activated sludge reactors as well as the biogas production (CO₂/CH₄) from the anaerobic digester. Indirect GHG emissions for power generation, chemical usage, effluent disposal and sludge storage and reuse are also included using static factors for CO₂, CH₄ and N₂O. Global and individual mass balances were quantified to investigate the fluxes of the different components. Novel strategies, such as the combination of different cascade controllers in the biological reactors and struvite precipitation in the sludge line, were proposed in order to obtain high plant performance as well as nutrient recovery and mitigation of the GHG emissions in a plant-wide context. The implemented control strategies led to an overall more sustainable and efficient plant performance in terms of better effluent quality, reduced operational cost and lower GHG emissions. The lowest N₂O and overall GHG emissions were achieved when ammonium and soluble nitrous oxide in the aerobic reactors were controlled and struvite was recovered in the reject water stream, achieving a reduction of 27% for N₂O and 9% for total GHG, compared to the open loop configuration.

Reduction of refractory Maillard reaction products by Fe3+ during thermal hydrolysis pretreatment and enhanced sludge biodegradability

Refractory Maillard reaction products (MRPs) produced during thermal hydrolysis pretreatment (THP) of waste activated sludge (WAS) may negatively impact the performance of downstream anaerobic digestion (AD) and nitrogen removal processes. Operating THP at lower temperature can mitigate the production of MRPs and improve biodegradability of WAS, while solubilization of WAS is reduced. This study intends to develop a method to reduce the refractory MRPs of WAS without compromising on the solubilization. Fe³⁺ was introduced into THP process (165 °C, 30 min) to mitigate Maillard reaction. Effects of Fe³⁺ on solubilization of WAS, reduction of refractory residuals, accumulative methane production, and microbial community shift were studied. Results confirm that solubilization of WAS was improved and refractory residuals were reduced with the amendment of 10 mg-Fe/L FeCl₃. MRPs mitigation mechanisms were investigated and mainly attributed to Fe³⁺-triggered Fenton-like reactions. Methane production was enhanced by 10.4 ± 0.8% and attributed to the improved biodegradability of THP liquor, as well as to the enrichment of protein degradation and methane production related microbial community. This work provides a simple, economical, and safe strategy to reduce refractory residuals discharged from THP-AD system and to enhance methane production for more energy recovery.

Comprehensive ADM1 Extensions to Tackle Some Operational and Metabolic Aspects in Anaerobic Digestion

Modelling in anaerobic digestion will play a crucial role as a tool for smart monitoring and supervision of the process performance and stability. By far, the Anaerobic Digestion Model No. 1 (ADM1) has been the most recognized and exploited model to represent this process. This study aims to propose simple extensions for the ADM1 model to tackle some overlooked operational and metabolic aspects. Extensions for the discontinuous feeding process, the reduction of the active working volume, the transport of the soluble compound from the bulk to the cell interior, and biomass acclimation are presented in this study. The model extensions are included by a change in the mass balance of the process in batch and continuous operation, the incorporation of a transfer equation governed by the gradient between the extra- and intra- cellular concentration, and a saturation-type function where the time has an explicit influence on the kinetic parameters, respectively. By adding minimal complexity to the existing ADM1, the incorporation of these phenomena may help to understand some underlying process issues that remain unexplained by the current model structure, broadening the scope of the model for control and monitoring industrial applications.

Role and significance of water and acid washing on biochar for regulating methane production from waste activated sludge

Methane recovered from anaerobic digestion of waste activated sludge (WAS) can be used as the energy supplement of the wastewater treatment plant, benefiting to its carbon-neutral operation. In order to enhance methane production, biochar (BC) has been widely selected as conductive material to build direct interspecies electron transfer (DIET) in anaerobic digestion of WAS. However, the role and significance of washing strategies, including water and acid washing, on BCs for regulating methane production have not been reported. This study selected the frequently used woody- (W) and straw (S)-BCs as mode. Compared to raw W-BC, water and acid washing W-BC increased the methane yields by 19.1% and 15.7%, respectively. Differently, the methane yields among raw, water and acid washing S-BCs were similar. Mechanism study showed that both the two washing strategies optimized the properties of raw W-BC for promoting methane production. Water and acid washing W-BCs increased the electron transfer functional groups, such as ketones and quinones, which were not observed in S-BCs. Moreover, the electron-active microorganisms were enriched with the presence of water and acid washing W-BCs, and the predominant pathway for methane production shifted from hydrogentrophic to acetotrophic and DIET methanogenesis, while the microbial communities, including bacteria and archaea, were similar with the presence of raw, water and acid washing S-BCs. These findings of this work provide some new insights for production improvement regulation of methane from anaerobic digestion of wastes induced by BCs.

Sulfur transformations during two-stage anaerobic digestion and intermediate thermal hydrolysis

The formation of hydrogen sulfide (H₂S) during anaerobic digestion (AD) imposes constraints on the valorisation of biogas. So far, inorganic sulfur compounds -mainly sulfate - have been considered as the main contributors to H₂S formation, while the contribution of organic sulfur compounds is mostly neglected. This study investigates the fate of organic and inorganic sulfur compounds during two-stage anaerobic digestion with intermediate thermal hydrolysis for treatment of primary and secondary sludge in a WWTP treating domestic wastewater. The results of a seven-week monitoring campaign showed an overall decrease of organic sulfur compounds in both stages of anaerobic digestion. Further fractionation of organic sulfur revealed a high conversion of the particulate organic fraction during the first digestion stage and of the soluble organic fraction during the second digestion stage. The decrease of soluble organic sulfur during the second digestion stage was attributed to the solubilisation and hydrolysis of sulfur-containing organic compounds during thermal hydrolysis. In both digestion stages, more organic sulfur was taken up than particulate inorganic sulfur (metal sulfide) was produced, indicating the formation of other reduced sulfur forms (e.g. H₂S). Further batch experiments confirmed the role of organic sulfur uptake in the formation of H₂S during anaerobic digestion as sulfate reduction only partly explained the total sulfide formed (H₂S in biogas and precipitated FeS). Overall, the conversion of organic sulfur was demonstrated to play a major role in H₂S formation (and thus the biogas quality), especially in case of thermal hydrolysis pretreatment.

Ionic strength of the liquid phase of different sludge streams in a wastewater treatment plant

In a wastewater treatment plant (WWTP), several sludge streams exist and the composition of their liquid phase varies with time and place. For evaluating the potential for formation of precipitates and equilibria for weak acids/bases, the ionic strength and chemical composition need to be known. This information is often not available in literature, and even neglected in chemical model-based research. Based on a literature review, we proposed three ranges of concentration (low, typical and high) for the major constituents of the liquid phase of the different streams in a WWTP. The study also discusses the reasons for the concentration evolution, and the exceptional cases, to allow readers to consider the right range depending on their situation. The ionic strength of the different streams and the contribution of its constituents were calculated based on the ionic composition. The major contributors to the ionic strength for the wastewater-based streams (influent, effluent and mixed sludge) were Na⁺, Cl^-, Mg²⁺ and Ca²⁺, representing 50-70% of the ionic strength. For digestate, NH₄⁺ and HCO₃^- accounted for 65-75% of the ionic strength. Even though the ionic strength is recognized to impact several important wastewater treatment processes, its utilization in literature is not always adequate, which is discussed in this study.

Modelling of autogenerative high-pressure anaerobic digestion in a batch reactor for the production of pressurised biogas

Background

Pressurised anaerobic digestion allows the production of biogas with a high content of methane and, at the same time, avoid the energy costs for the biogas upgrading and injection into the distribution grid. The technology carries potential, but the research faces practical constraints by a.o. the capital investment needed in high-pressure reactors and sensors and associated sampling limitations. In this work, the kinetic model of an autogenerative high-pressure anaerobic digestion of acetate, as the representative compound of the aceticlastic methanogenesis route, in batch configuration, is proposed to predict the dynamic performance of pressurised digesters and support future experimental work. The modelling of autogenerative high-pressure anaerobic digestion in batch configuration, which is not extensively studied and simulated in the present literature, was developed, calibrated, and validated by using experimental results available from the literature.

Results

Under high-pressure conditions, the assessment of the Monod maximum specific uptake rate, the half-saturation constant and the first-order decay rate was carried out, and the values of 5.9 kg COD kg COD⁻¹ d⁻¹, 0.05 kg COD m⁻³ and 0.02 d⁻¹ were determined, respectively. By using the predicted values, excellent fittings of the final pressure, the CH₄ molar fraction and the specific methanogenic yield calculation were obtained. Likewise, the variation in the gas–liquid mass transfer coefficient by several orders of magnitude showed negligible effects on the model predictive values in terms of methane molar fraction of the produced biogas, while the final pressure seemed to be slightly influenced.

Conclusions

The proposed model allowed to estimate the Monod maximum specific uptake rate for acetate, the half-saturation rate for acetate and the first-order decay rate constant, which were comparable with literature values reported for well-studied methanogens under anaerobic digestion at atmospheric pressure. The methane molar fraction and the final pressure predicted by the model showed different responses towards the variation of the gas–liquid mass transfer coefficient since the former seemed not to be affected by the variation of the gas–liquid mass transfer coefficient; in contrast, the final pressure seemed to be slightly influenced. The proposed approach may also allow to potentially identify the methanogens species able to be predominant at high pressure.

Enhancement of anaerobic digestion digital twin through aerobic simulation and kinetic optimization for co-digestion scenarios

An upgraded digital twin of the Anaerobic Digestion Model 1 is proposed to enhance its industrial applicability and range of use. Through the optimization and generalization of kinetic coefficients toward co-digestion reactors simulation and insertion of new equations for the complete biokinetics modeling of H₂S, the proposed model can predict more precisely the exiting biogas fractions comprehensive of H₂S and O₂ without any parametric adjustment. Moreover, it is proposed a new function representing the oxygen-methanogens. The model has been validated through the comparison with other literature models and with experimental data coming both from the literature and from an industrial plant. The comparisons show its flexibility and industrial applicability. Finally, an optimization of the methane content through oxygen rate adjustment is proposed, increasing CH₄ content of 4%vol. The mathematical model has been built using Python™, which makes it easily spreadable and usable.

Considering syntrophic acetate oxidation and ionic strength improves the performance of models for food waste anaerobic digestion

Current mechanistic anaerobic digestion (AD) models cannot accurately represent the underlying processes occurring during food waste (FW) AD. This work presents an update of the Anaerobic Digestion Model no. 1 (ADM1) to provide accurate estimations of free ammonia concentrations and related inhibition thresholds, and model syntrophic acetate oxidation as acetate-consuming pathway. A modified Davies equation predicted NH₃ concentrations and pH more accurately, and better estimated associated inhibitory limits. Sensitivity analysis results showed the importance of accurate disintegration kinetics and volumetric mass transfer coefficients, as well as volatile fatty acids (VFAs) and hydrogen uptake rates. In contrast to the default ADM1, the modified ADM1 could represent methane production and VFA profiles simultaneously (particularly relevant for propionate uptake). The modified ADM1 was also able to predict the predominant acetate-consuming and methane-producing microbial clades. Modelling results using data from reactors dosed with granular activated carbon showed that this additive improves hydrogen uptake.

Phosphorus cycling in freshwater lake sediments: Influence of seasonal water level fluctuations

Freshwater lakes experience drastic water level fluctuations because of climate change and human activities. However, the influence of such fluctuations on phosphorus cycling in sediments has rarely been investigated. We conducted a geochemical investigation on the phosphorus cycle in a shallow freshwater lake, Dongting Lake; under the influence of human activities and climate change, its water regime undergoes drastic changes. Irrespective of the permanent inundation zone (PIZ) or seasonal inundation zone (SIZ), the phosphorus cycle in sediments was found to be dominated by the reductive dissolution of iron (Fe) (oxyhydr)oxides, degradation of organic matters, and conversion between authigenic phosphorus (Ca-P) and detrital phosphorus in individual seasons. From winter to summer, with increasing water level, the content of Fe-bound phosphorus and organic phosphorus increase due to the deposition of suspended matter, thus increasing total phosphorus in PIZ. Moreover, the rising water level also reduces the dissolved oxygen content and promotes the reductive dissolution of Fe (oxyhydr)oxides. The mineralization of increased organic matter can release CO₂ and reduce pH in the vicinity, which can further result in the acidic dissolution of detrital apatite. In turn, most of the released phosphorus can be adsorbed or co-precipitated with calcium minerals, resulting in the significant increase of Ca-P. The mechanisms of phosphorus transformation in SIZ are similar to those in PIZ, but most of the increased organic matter and total P in a core from SIZ are attributable to the decomposition of plant matter. Therefore, the water level rise not only changes the conservative speciation of phosphorus in sediments to active speciation, but also triggers the release of phosphorus adsorbed to oxides and further increases the risk of phosphorus release from sediments to overlying water. Thus, our findings have major implications for freshwater shallow lakes and their P-driven productivity.

Design of Feedback Control Strategies in a Plant-Wide Wastewater Treatment Plant for Simultaneous Evaluation of Economics, Energy Usage, and Removal of Nutrients

Simultaneous removal of nitrogen and phosphorous is a recommended practice while treating wastewater. In the present study, control strategies based on proportional-integral (PI), model predictive control (MPC), and fuzzy logic are developed and implemented on a plant-wide wastewater treatment plant. Four combinations of control frameworks are developed in order to reduce the operational cost and improve the effluent quality. As a working platform, a Benchmark simulation model (BSM2-P) is used. A default control framework with PI controllers is used to control nitrate and dissolved oxygen (DO) by manipulating the internal recycle and oxygen mass transfer coefficient (KLa). Hierarchical control topology is proposed in which a lower-level control framework with PI controllers is implemented to DO in the sixth reactor by regulating the KLa of the fifth, sixth, and seventh reactors, and fuzzy and MPC are used at the supervisory level. This supervisory level considers the ammonia in the last aerobic reactor as a feedback signal to alter the DO set-points. PI-fuzzy showed improved effluent quality by 21.1%, total phosphorus removal rate by 33.3% with an increase of operational cost, and a slight increase in the production rates of greenhouse gases. In all the control design frameworks, a trade-off is observed between operational cost and effluent quality.

A general framework to model the fate of trace elements in anaerobic digestion environments

Due to the multiplicity of biogeochemical processes taking place in anaerobic digestion (AD) systems and limitations of the available analytical techniques, assessing the bioavailability of trace elements (TEs) is challenging. Determination of TE speciation can be facilitated by developing a mathematical model able to consider the physicochemical processes affecting TEs dynamics. A modeling framework based on anaerobic digestion model no 1 (ADM1) has been proposed to predict the biogeochemical fate TEs in AD environments. In particular, the model considers the TE adsorption–desorption reactions with biomass, inerts and mineral precipitates, as well as TE precipitation/dissolution, complexation reactions and biodegradation processes. The developed model was integrated numerically, and numerical simulations have been run to investigate the model behavior. The simulation scenarios predicted the effect of (i) organic matter concentration, (ii) initial TEs concentrations, (iii) initial Ca–Mg concentrations, (iv) initial EDTA concentration, and (v) change in TE binding site density, on cumulative methane production and TE speciation. Finally, experimental data from a real case continuous AD system have been compared to the model predictions. The results prove that this modelling framework can be applied to various AD operations and may also serve as a basis to develop a model-predictive TE dosing strategy.

Assessment of sludge management strategies in wastewater treatment systems using a plant-wide approach

The objective of this paper is to use plant-wide modeling to assess the net impacts of varying sludge management strategies. Special emphasis is placed on effluent quality, operational cost and potential resource recovery (energy, nutrients). The study is particularly focused on a centralized bio-solids beneficiation facility (BBF), which enables larger, more capital intensive sludge management strategies. Potential barriers include the ability to process reject streams from multiple donor plants in the host plant. Cape Flats (CF) wastewater treatment works (WWTW) (Cape Town, South Africa) was used as a relevant test case since it is currently assessing to process sludge cake from three nearby facilities (Athlone, Mitchells Plain and Wildevoelvlei). A plant-wide model based on the Benchmark Simulation Model no 2 (BSM2) extended with phosphorus transformations was adapted to the CF design / operational conditions. Flow diagram and model parameters were adjusted to reproduce the influent, effluent and process characteristics. Historical data between January 2014 and December 2019 was used to compare full-scale measurements and predictions. Next, different process intensification / mitigation technologies were evaluated using multiple criteria. Simulation values for COD, TSS, VSS/TSS ratio, TN, TP, NH₄⁺/NH₃, H_xPO4^3-x, NO_x alkalinity and pH fall within the interquartile ranges of measured data. The effects of the 2017 severe drought on influent variations and biological phosphorus removal are successfully reproduced for the entire period with dynamic simulations. Indeed, 80% of all dynamically simulated values are included within the plant measurement uncertainty ranges. Sludge management analysis reveals that flow diagrams with thermal hydrolysis pre-treatment (THP) result in a better energy balance in spite of having higher heat demands. The flow diagram with THP is able to i) increase biodegradability/solubility, ii) handle higher sludge loads, iii) change methanogenic microbial population and iv) generate lower solids volumes to dispose by improving sludge dewaterability. The study also reveals the importance of including struvite precipitation and harvesting (SPH) technology, and the effect that pH in the AD and the use of chemicals (NaOH, MgO) may have on phosphorus recovery. Model-based results indicate that the current aerobic volume in the water line (if properly aerated) would be able to handle the returns from the sludge line and the contribution of a granular partial nitritation/Anammox (PN/ANX) reactor on the overall nitrogen removal would be marginal. However autotrophic N denitrification generates a much lower sludge production and therefore increases AD treatment capacity. The study shows for the very first time in Africa how the use of a (calibrated) plant-wide model could assist water utilities to decide between competing plant layouts when upgrading a WWTW.

Dark fermentative hydrogen production from hydrolyzed sugar beet pulp improved by iron addition

This study evaluated the impact of three different iron compounds (Fe₂O₃, FeSO₄, FeCl₃) on hydrogen production via mesophilic dark fermentation (DF) of hydrolyzed sugar beet pulp (SBP). In batch tests, the maximum hydrogen yield of over 200 dm³H₂/kgVS was achieved with the addition of 0.1 gFe₂O₃/dm³, which was twice greater than the control. In semi-continuous experiments, the highest hydrogen production of 52.11 dm³H₂/kgVS combined with 19.4 dm³CH₄/kgVS methane yield was obtained at a dose of 1 gFe₂O₃/dm³. Acetic, lactic and caproic acids were the main metabolic products of DF. Microbiological studies showed some balance between hydrogen producing microorganisms from the order Clostridiales and lactic acid producers (LAB) affiliated with the orders Lactobacillales and Coriobacteriales. Moreover, the presence of methanogens affiliated to the genera Methanobrevibacter and Methanosphaera was also documented. An interesting finding was the appearance of rare bacteria from the genus Caproiciproducens, which was responsible for increased caproic acid production.

Autotrophic sulfide removal by mixed culture purple phototrophic bacteria

Current H₂S treatment methods for sour gases require considerable amounts of chemicals and energy, or in case of biological treatment, unwanted diluents such as oxygen or nitrogen may be introduced. In order to reduce those requirements, the viability of an anaerobic biological H₂S removal process using purple phototrophic bacteria (PPB) was investigated in this study. PPB can use sunlight, and centrate as nutrient source, thus potentially reducing energy and chemical requirements. An added benefit is the production of biomass with potential uses, such as single cell protein. An inoculum of PPB enriched from domestic wastewater was grown photoautotrophically with sulfide as the electron donor and inorganic carbon in a mixed culture. Additionally, synthetic medium and centrate as well as high (56 ± 11 Wm^-2) and low (27 ± 3 Wm^-2) IR irradiation were trialled. Finally, a process model was developed to study biomass specific removal rates and yield. The results showed that a mixed culture of PPB removed sulfide completely in synthetic media (121 ± 9 mg-S.L^-1) at a maximum rate of 1.79 ± 0.16 mg-S(Lh)^-1 (low irradiance) and 2.9 mg-S(Lh)^-1 (high irradiance). The pH increased in both experiments from about 8.5 to 9. Sulfide removal rates using centrate and low irradiance were similar. However Fe and Mn were found to be limiting growth and sulfide removal. In all experiments, Chromatiaceae (purple sulfur bacteria) were most abundant at the end of the experiment, while at the start purple non-sulfur bacteria were most abundant (from the inoculum). Process modelling and experimental work identified the sulfide oxidation to be a multi-step process with accumulation of intermediates. Specific rates were directly dependent on light input, doubling at high irradiance. Sulfide oxidation was estimated at 0.100 ± 0.014 h^-1 (0.085 ± 0.012 g-S(g-VS.h)^-1) at low irradiance, and the biomass yield at 0.86 ± 0.05 mg-COD.mg-COD^-1. This process model enables the virtual evaluation of autotrophic sulfide removal by PPB in a continuous scaled-up process. Overall, the photoautotrophic removal of sulfide seems to be a viable option, especially because of the possibility of using sunlight as an energy source and centrate as a nutrient source.

Not Just Numbers: Mathematical Modelling and Its Contribution to Anaerobic Digestion Processes

Mathematical modelling of bioprocesses has a long and notable history, with eminent contributions from fields including microbiology, ecology, biophysics, chemistry, statistics, control theory and mathematical theory. This richness of ideas and breadth of concepts provide great motivation for inquisitive engineers and intrepid scientists to try their hand at modelling, and this collaboration of disciplines has also delivered significant milestones in the quality and application of models for both theoretical and practical interrogation of engineered biological systems. The focus of this review is the anaerobic digestion process, which, as a technology that has come in and out of fashion, remains a fundamental process for addressing the global climate emergency. Whether with conventional anaerobic digestion systems, biorefineries, or other anaerobic technologies, mathematical models are important tools that are used to design, monitor, control and optimise the process. Both highly structured, mechanistic models and data-driven approaches have been used extensively over half a decade, but recent advances in computational capacity, scientific understanding and diversity and quality of process data, presents an opportunity for the development of new modelling paradigms, augmentation of existing methods, or even incorporation of tools from other disciplines, to ensure that anaerobic digestion research can remain resilient and relevant in the face of emerging and future challenges.

Theoretical framework for the estimation of H2S concentration in biogas produced from complex sulfur-rich substrates

A theoretical framework was developed and validated for the estimation of H₂S concentration in biogas produced from complex sulfur-rich effluents. The modeling approach was based on easy-to-obtain data such as biological biogas potential (BBP), chemical oxygen demand, and total sulfur content. Considering the few data required, the model fitted well the experimental H₂S concentrations obtained from BBP tests and continuous bioreactors reported in the literature. The model supported a correlation coefficient (R²) of 0.989 over the experimental data, obtaining average and maximum errors of ~ 25 and ~ 35%, respectively. The theoretical framework yielded good estimations for a wide range of experimental H₂S concentrations (0.2 to 4.5% in biogas). This modeling approach is, therefore, a useful tool towards anticipating the H₂S concentration in biogas produced from sulfur-rich substrates and deciding whether the installation of a desulfurization technology is required or not.

Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.

Essential regulators of iron chemical speciation distributions in anaerobic digestion of pretreated food waste: Organic volatile fatty acids or inorganic acid radicals?

In this work, a 30-days batched mesophilic assay on pretreated food waste (PFW) under different inoculum/substrate (I/S) ratios (1:5, 1:2, 1:1, 2:1, 4:1 and 1:0) was carried out, to target the most important parameters in AD matrix on regulating iron (Fe) chemical speciation. Correlation coefficients were calculated within four Fe chemical forms and AD parameters of pH, volatile fatty acids (VFAs), inorganic acid radicals (IARs), and alkalinity. Results showed that IARs were not key factors on regulating Fe speciation. Without acidification, IARs showed weak correlations (coefficients < 0.40) with Fe chemical dynamics while other parameters showed stronger correlations (coefficients ≥ 0.60). Under acidification, VFAs initiated the conversion of exchangeable Fe into water soluble fraction. Residual fraction might play important role in regulating Fe shifting to more bioavailable states.

Application of IWA Anaerobic Digestion Model No. 1 to simulate butyric acid, propionic acid, mixed acid, and ethanol type fermentative systems using a variable acidogenic stoichiometric approach

IWA Anaerobic Digestion Model No. 1 (ADM1) is the most widely recognised and popular mathematical model for anaerobic digestion processes. However, the application of ADM1 to acidogenic fermentation is limited by its use of constant stoichiometry to describe the formation of products via carbohydrate fermentation. This study presents a modification of ADM1 using a variable acidogenic stoichiometric approach in which the hydrogen partial pressure (p_H2) and pH are used to predict and regulate the acidogenic process. The fermentation of ethanol and its kinetics were introduced into the model structure. Experimental data from mixed acid-type fermentation in a 28.4 L anaerobic baffled reactor (ABR) fed with a sucrose solution with a chemical oxygen demand of 4000 mg L^-1 were used to calibrate the model parameters. Two case studies involving continuous ethanol-type fermentation in an ABR and a continuous stirring tank reactor (CSTR) were used to validate the approach. The modified model achieved good predictions of the experimental data collected from butyric acid, propionic acid, mixed acid, and ethanol-type fermentation in the ABR and CSTR using the standard ADM1 parameter values without any parameter fitting beyond implementation of the variable acidogenic stoichiometry. The p_H2 and pH thresholds in butyric acid, propionic acid, mixed acid, and ethanol-type fermentation could be predicted using this model, which was shown to be a valid mathematical tool for the regulation of fermentation type.

ADM1-based mechanistic model for the role of trace elements in anaerobic digestion processes

An original mechanistic model able to describe the fate of trace elements (TE) in anaerobic digestion systems has been synthetized from mass balance equations. The model takes into account the main biochemical and physico-chemical processes affecting TE bioavailability and it is aimed at evaluating the effect that the combination of such processes exerts on the system performance. Five main modules have been introduced: biochemistry, physico-chemistry, sorption, complexation and precipitation. The model is based on mass conservation principles and is formulated as a set of ordinary differential equations for the soluble and particulate components constituting the system. Model applications of two illustrative cases are provided. The first case is based on experimental results and examines the effect of TE depletion in an AD process of food waste (FW). The second case shows the effects of different metal supplements on methane production and biogas composition. The simulation results confirm that the model can fairly be used to predict the effect of TE dynamics and bioavailability, by considering biological, chemical and physicochemical processes in AD environments.

Evaluation of anaerobic digestion post-treatment options using an integrated model-based approach

The objective of this paper is to present the main results of an engineering-research project dealing with model-based evaluation of waste streams treatment from a biotech company. This has been extensively done in domestic treatment systems, but is equally important, and with different challenges in industrial wastewater treatment. A new set of biological (activated sludge, anaerobic digestion), physicochemical (aqueous phase, precipitation, mass transfer) process models and model interfaces are required to describe removal of organics in an upflow anaerobic sludge blanket (UASB) reactor plus either traditional nitrification/denitrification (A₁) or partial nitritation (PN)/anammox (ANX) (A₂) processes. Model-based analysis shows that option A₁ requires a decrease in digestion energy recovery (E_recovery) in order to have enough organic substrate for subsequent post NO₃ reduction treatment (95 kWh.kg N^-1). In contrast, A₂ in an aerobic granular sludge reactor allows for higher UASB conversion since N removal is carried out autotrophically. The study also reveals that the addition of an aerated pre-treatment unit prior to the PN/ANX (A₂) reactor promotes COD and H₂S oxidation, CO₂ and CH₄ stripping, a pH increase (up to 8.5) and a reduction of the risk of intra-granular precipitation as well as sulfide inhibition. Simulations indicate clear differences regarding the microbial distribution/abundance within the biofilm in A₂ when comparing the two operational modes. Final results show the effects of different loading and operational conditions; dissolved oxygen (DO), Total Suspended Solids (TSS_op), energy recovery (E_recovery); on the overall process performance; N removal, aeration energy (E_aeration), net energy production (E_recovery); using response surfaces, highlighting the need of integrated approaches to avoid sub-optimal outcomes. The study shows the benefits of virtual plant simulation and demonstrates the potential of model-based evaluation when process engineers in industry have to decide between competing options.

Plant-wide model-based analysis of iron dosage strategies for chemical phosphorus removal in wastewater treatment systems

Stringent phosphorus discharge standards (i.e. 0.15-0.3 g P.m^-3) in the Baltic area will compel wastewater treatment practice to augment enhanced biological phosphorus removal (EBPR) with chemical precipitation using metal salts. This study examines control of iron chemical dosing for phosphorus removal under dynamic loading conditions to optimize operational aspects of a membrane biological reactor (MBR) pilot plant. An upgraded version of the Benchmark Simulation Model No. 2 (BSM2) with an improved physico-chemical framework (PCF) is used to develop a plant-wide model for the pilot plant. The PCF consists of an equilibrium approach describing ion speciation and pairing, kinetic minerals precipitation (such as hydrous ferric oxides (HFO) and FePO₄) as well as adsorption and co-precipitation. Model performance is assessed against data sets from the pilot plant, evaluating the capability to describe water and sludge lines across the treatment process under steady-state operation. Simulated phosphorus differed as little as 5-10% (relative) from measured phosphorus, indicating that the model was representative of reality. The study also shows that environmental factors such as pH, as well operating conditions such as Fe/P molar ratios (1, 1.5 and 2), influence the concentration of dissolved phosphate in the effluent. The time constant of simultaneous precipitation in the calibrated model, due to a step change decrease/increase in FeSO₄ dosage, was found to be roughly 5 days, indicating a slow dynamic response due to a multi-step process involving dissolution, oxidation, precipitation, aging, adsorption and co-precipitation. The persistence effect of accumulated iron-precipitates (HFO particulates) in the activated sludge seemed important for phosphorus removal, and therefore solids retention time plays a crucial role according to the model. The aerobic tank was deemed to be the most suitable dosing location for FeSO₄ addition, due to high dissolved oxygen levels and good mixing conditions. Finally, dynamic model-based analyses show the benefits of using automatic control when dosing chemicals.

Competitive dynamics of anaerobes during long-term biological sulfate reduction process in a UASB reactor

To reveal the long-term competitive dynamics of anaerobes in anaerobic bioreactors with sulfate reduction, a comprehensive structured mathematical model was designed for an extension of the Anaerobic Digestion Model No. 1 (ADM1). Sulfate reduction bacteria (SRB) were categorized into acetogenic-likewise SRB (ASRB) and methanogenic-likewise SRB (MSRB). Experimental data from 329 days of continuous operation of a laboratory-scale upflow anaerobic sludge bed (UASB) reactor was used for model calibration and validation. Results show that the model has a good agreement with experimental data and that three stages including the MPA dominant, stalemate and SRB dominant stages were clearly appeared throughout the whole competition period. The model was capable of predicting the long-term dynamic competition of sulfidogens and methanogens for electrons. This could explain a long-term of over 200 days needed for the SRB out-competing the MPA, and support speculation that the SRB could finally out-compete both the AcB and the MPA.

Assessing the effects of intra-granule precipitation in a full-scale industrial anaerobic digester

In this paper, a multi-scale model is used to assess the multiple mineral precipitation potential in a full-scale anaerobic granular sludge system. Reactor behaviour is analysed under different operational conditions (addition/no addition of reject water from dewatering of lime-stabilized biomass) and periods of time (short/long term). Model predictions suggest that a higher contribution of reject water promotes the risk of intra-granule CaCO₃ formation as a result of the increased quantity of calcium arriving with that stream combined with strong pH gradients within the biofilm. The distribution of these precipitates depends on: (i) reactor height; and (ii) granule size. The study also exposes the potential undesirable effects of the long-term addition of reject water (a decrease in energy recovery of 20% over a 100-day period), caused by loss in biomass activity (due to microbial displacement), and the reduced buffer capacity. This demonstrates how both short-term and long-term operational conditions may affect the formation of precipitates within anaerobic granules, and how it may influence methane production and consequently energy recovery.

Sulfur cycling in freshwater sediments: A cryptic driving force of iron deposition and phosphorus mobilization

Sulfur cycling in freshwater ecosystems has been previously considered minor, and the direct evidence of its impacts on iron and phosphorus cycles in freshwater sediments remains unclear. In this study, mesocosms with amended acetate and various sulfate concentrations (1.5-3.0 mmol L^-1) were set up to investigate sulfur cycling and its influences on iron-rich freshwater sediments. Acetate addition induced hypoxia and provided substrates, which stimulated the sulfur cycling with evidence of SO₄^2- decline, ΣS^2-, S⁰ increase and corresponding variations of sulfate-reducing bacteria (SRB) and sulfur-oxidizing bacteria. Meanwhile, the growth of iron-reducing bacteria (IRB) was suppressed, and lower Fe(II) release was correspondingly related to larger SRB abundance at higher sulfate level, indicating that microbial iron reduction might be blocked by SRB activities. However, continuous dissolution of Fe(III) oxides and generation of iron sulfides were observed, suggesting that sulfide-mediated chemical iron reduction (SCIR) became the dominant iron-reducing pathway, and Fe(II) was buried as iron sulfides instead of released to water column, which resulted in a transition of iron cycling into unidirectional SCIR. Consequently, continuous dissolution of Fe(III) oxides led to significant increase of PO₄^3- concentration in the water column and sediment pore-water, revealing the phosphorus mobility in sediments derived from the SCIR process. To note, sustained accumulation of iron sulfides was observed even without ΣS^2- presence, suggesting that ΣS^2- precipitation occurred prior to diffusion. Thus, ΣS^2--missing sulfur cycling seemed "cryptic" in this study. To highlight, the transition of the iron-reducing pathway and resulting PO₄^3- release can be induced even under current sulfate level of Lake Taihu, and elevated sulfate levels could significantly intensify SCIR and phosphorus mineralization. Thus, the stimulated iron deposition and the resulting phosphorus release derived from the sulfur cycling should be paid more attention to in the treatment of eutrophic freshwater ecosystems.

ADM1 based mathematical model of trace element complexation in anaerobic digestion processes

In this study, a new model based on anaerobic digestion model no.1 (ADM1) approach has been proposed to simulate trace elements (TEs) complexation, precipitation and their effect on the anaerobic batch methane production. TEs complexation reactions with VFAs and EDTA have been incorporated in an extended ADM1 model which considers TE precipitation/dissolution reactions as well as biodegradation processes. The kinetic model tracks the dynamics of 90 state variables which constitute the components of the proposed anaerobic digestion (AD) model. The incorporation of the complexation reactions required the definition of new inorganic components (EDTA species) and new complexation process rates in the ADM1 framework. The charge balance was modified accordingly to consider the effects of the additional components. The new model is able to predict: a) the effect of TE-EDTA/VFA complexation on methane production, and b) the effect of the initial calcium and magnesium concentrations on process performance.

A comprehensive review of anaerobic digestion of organic solid wastes in relation to microbial community and enhancement process

Organic solid wastes (OSWs) should be regarded as valuable resources rather than dead-end landfill waste that causes public health and odor concerns. Anaerobic digestion (AD) is an ideal approach for managing organic solid waste issues and involves using a group of anaerobic microorganisms to transform OSWs into useful products. In this review, over 100 publications related to AD of OSWs have been compiled, discussed, and analyzed. A comprehensive analysis of the environmental and safety impacts of AD, its key environmental factors, co-digestion, and pretreatment, as well as the AD of OSWs by various anaerobic microbes uncovered by high throughput sequencing-based approaches, is presented. The purpose of this review is to provide an outline of the current knowledge of AD processes from a multi-angle perspective. A comprehensive understanding of AD of OSWs and genome-enabled biology development could be helpful for providing up-to-date knowledge of AD, developing it, overcoming its drawbacks and, ultimately, improving global waste control for more efficient environmental management. © 2018 Society of Chemical Industry.