Feeding control of anaerobic co-digestion of waste activated sludge and corn silage performed by rule-based PID control with ADM1

Biogas potential of organosolv pretreated wheat straw as mono and co-substrate: substrate synergy and microbial dynamics

Anaerobic digestion (AD) technology can potentially address the gap between energy demand and supply playing a crucial role in the production of sustainable energy from utilization of biogenic waste materials as feedstock. The biogas production from anaerobic digestion is primarily influenced by the chemical compositions and biodegradability of the feedstock. Organosolv-steam explosion offers a constructive approach as a promising pretreatment method for the fractionation of lignocellulosic biomasses delivering high cellulose content.This study showed how synergetic co-digestion serves to overcome the challenges of mono-digestion's low efficiency. Particularly, the study evaluated the digestibility of organosolv-steam pretreated wheat straw (WSOSOL) in mono as well as co-digesting substrate with cheese whey (CW) and brewery spent grains (BSG). The highest methane yield was attained with co-digestion of WSOSOL + CW (338 mL/gVS) representing an enhanced biogas output of 1-1.15 times greater than its mono digestion. An ammonium production was favored under co-digestion strategy accounting for 921 mg/L from WSOSOL + BSG. Metagenomic study was conducted to determine the predominant bacteria and archaea, as well as its variations in their populations and their functional contributions during the AD process. The Firmicutes have been identified as playing a significant role in the hydrolysis process and the initial stages of AD. An enrichment of the most prevalent archaea genera enriched were Methanobacterium, Methanothrix, and Methanosarsina. Reactors digesting simpler substrate CW followed the acetoclastic, while digesting more complex substrates like BSG and WSOSOL followed the hydrogenotrophic pathway for biomethane production. To regulate the process for an enhanced AD process to maximize CH4, a comprehensive understanding of microbial communities is beneficial.

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.

A novel online analyzer for accurate and rapid measurement of volatile fatty acids in anaerobic wastewater treatment

Volatile fatty acids (VFAs), which are largely generated during the anaerobic acidification process, are considered to be reliable indicators of the stable process operation. However, the common methods for monitoring VFAs are offline, and they are typically manual requiring time-consuming, costly and complex instruments. This study aims to develop a novel online analyzer for automatic measuring VFAs, which was based on the 5-pH point titration, embedded with a proportional-integral-derivative (PID) feedback control system. The results show that it can achieve accurate and rapid monitoring of VFAs ranging between 0-400 mg/L (<9 min/sample) but simultaneously faces the problems of overtitration and interference of complex characteristics of wastewater. In order to improve its accuracy and stability, the effects of three general coefficients (K_I,K_P, and K_D) of PID on the titration were investigated, and the optimal values of K_I, K_P, and K_D were found to be 1.5, 1.0, and -1.0~0.5, respectively. Besides, the initial titration speed was set at 0.06 mL/min, equal to the minimum speed of the peristaltic pump, and the dichotomy approach was integrated into the PID feedback controller. Owing to the above improvements, the relative mean deviation and standard deviation of measuring VFAs in both synthetic and real wastewaters were mostly lower than 5.0% and 5.0 mg/L, proving the online analyzer is rapid, accurate and reliable.

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

Long-term continuous monitoring (LTCM) of water quality can bring far-reaching influences on water ecosystems by providing spatiotemporal data sets of diverse parameters and enabling operation of water and wastewater treatment processes in an energy-saving and cost-effective manner. However, current water monitoring technologies are deficient for long-term accuracy in data collection and processing capability. Inadequate LTCM data impedes water quality assessment and hinders the stakeholders and decision makers from foreseeing emerging problems and executing efficient control methodologies. To tackle this challenge, this review provides a forward-looking roadmap highlighting vital innovations toward LTCM, and elaborates on the impacts of LTCM through a three-hierarchy perspective: data, parameters, and systems. First, we demonstrate the critical needs and challenges of LTCM in natural resource water, drinking water, and wastewater systems, and differentiate LTCM from existing short-term and discrete monitoring techniques. We then elucidate three steps to achieve LTCM in water systems, consisting of data acquisition (water sensors), data processing (machine learning algorithms), and data application (with modeling and process control as two examples). Finally, we explore future opportunities of LTCM in four key domains, water, energy, sensing, and data, and underscore strategies to transfer scientific discoveries to general end-users.

Sewage-water treatment with bio-energy production and carbon capture and storage

Typical large-scale sewage-water treatments consume energy, occupy space and are unprofitable. This work evaluates a conceivable two-staged sewage-water treatment at 40,000 m³/d of sewage-water with sewage-sludge (totaling 10kg^COD/m³) that becomes a profitable bioenergy producer exporting reusable water and electricity, while promoting carbon capture. The first stage comprises microbial anaerobic digesters reducing the chemical oxygen demand (COD) by 95% and producing 60%mol methane biogas. The effluent waters enter the subsequent aerobic stage comprising microbial air-fed digesters that extend COD reduction to 99.7%. To simulate the process, up-to-date anaerobic/aerobic digester models were implemented. A biogas-combined-cycle power plant with/without post-combustion carbon capture is designed to match the biogas production, supplying electricity to the process and to the grid. Results comprehend electricity exportation of 13.21 MW (7.92 kWh/t^{Reusable-Water}) with -9.957t^CO2/h of negative carbon emission (-0.6 kg^CO2-Emitted/kg^COD-Removed). The biogas-combined-cycle without carbon capture achieves 21.08 MW of power exportation, while a 37.3% energy penalty arises if carbon capture is implemented. Configurations with/without carbon capture reach feasibility at 125 USD/MWh of electricity price, with respective net present values of 6.86 and 85.07 MMUSD and respective payback-times of 39 and 12 years. These results demonstrate that large-scale sewage-water treatment coupled to biogas-fired combined-cycles and carbon capture can achieve economically feasible bioenergy production with negative carbon emissions.

Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling

Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.

Methane production from food waste using a feedback control strategy in a sequencing batch reactor

The performance of a feedback control strategy in the operation of a sequencing batch reactor was evaluated. This strategy uses the online biogas flow measurements to define the duration of the reaction phase of each operating cycle, thereby increasing the energy production of the system and maximizing the methane production rate. The reaction phase is ended when the biogas flow rate reaches a sustained value significantly lower value than the maximum flow rate achieved, as a consequence of the depletion of the soluble chemical oxygen demand. The implementation of the depletion-time control was successful and reached a maximum methane production rate of 1.22 L CH₄/d, showing an average productivity of 0.73 ± 0.3 L CH₄/d. The reaction phase varied from 1.2 to 6 days with hydraulic retention times from 6 to 30 days. The use of this feedback control strategy increased the methane production and the energy production in 80% of the evaluated cycles (from 10.4 to 43.8%) compared to the operation of conventional AD without a control strategy. Furthermore, the strategy is easy to implement since it does not require complex calculations and uses a readily available biogas flow rate sensor.

Moving average convergence and divergence indexes based online intelligent expert diagnosis system for anaerobic wastewater treatment process

Anaerobic wastewater treatment process is efficient but unstable due to various disturbances, such as refractory organics and influent organic overloading. Therefore, sensitive and accurate status diagnosis is important for reasonable control to improve the stability of anaerobic process. In this study, an online intelligent expert diagnosis system for anaerobic process was established based on moving average convergence and divergence (MACD) indexes of gas- and liquid-phase parameters, combined with online monitoring system and expert diagnosis database. The effect of this diagnosis system was verified through refractory organics and organic overloading shock experiments. Results showed that this diagnosis system could make rapid, accurate and comprehensive diagnosis, predictions and early-warning. MACD algorithm could enhance pattern recognition capacity of status parameters, overcome the lagging of anaerobic process and filter irregular noisy fluctuations of status parameters. MACD index of H₂ partial pressure is suitable as sensitive early-warning indicator in the initial shock stage.

Influence of particle scattering on photo biochemical transformation process of direct absorption methane digester

An outdoor anaerobic fermentation reactor loses a significant amount of energy due to heat dissipation to the surrounding environment. The digester of direct absorption biogas can effectively utilize solar energy and scattering of the medium to enhance reaction temperature, which can promote anaerobic fermentation of microorganisms. A numerical model for the direct absorption methane digester was established to investigate the mechanism of photo biochemical transformation. The average relative values of simulated results were 4.1% and 9.6%, indicating that the model can effectively simulate the heat transfer process of biogas slurry under solar irradiation. Decreasing the albedo and increasing the effect of forward scattering of small particles can improve the regenerative performance and biogas production of digester. Increasing the backward scattering effect of small particles limited biogas fermentation. Scattering distribution had bigger effects on the rates of biogas and propionic acid production than those of albedo.