Fast ADM1 implementation for the optimization of feeding strategy using near infrared spectroscopy

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.

Sustainability for wastewater treatment: bioelectricity generation and emission reduction

This review covers the technological measures of a self-sustainable anaerobic up-flow sludge blanket (UASB) system compared with an aerobic activated sludge process (ASP) for wastewater treatment plants (WWTPs). The ASP requires a huge amount of electricity and chemicals and also results in the emission of carbon. The UASB system, instead, is based on greenhouse gas (GHG) emission reduction and is associated with biogas production for cleaner electricity. WWTPs including the ASP system are not sustainable due to the massive financial power required for clean wastewater. When the ASP system was used, the amount of production was estimated to be 10658.98 tonnes CO₂eq-d^- of carbon dioxide. Whereas it was 239.19 tonnes CO₂eq-d^-1 with the UASB. The UASB system is advantageous over the ASP system as it has a high production of biogas, needs low maintenance, yields a low amount of sludge, and is also a source of electricity that can be used as a power source for the WWTPs. Also, the UASB system produces less biomass, and this helps in reducing costs and maintaining work. Moreover, the aeration tank of the ASP needs 60% of energy distribution; on the other hand, the UASB consumes less energy, approximately 3-11%.

Fast and robust NIRS-based characterization of raw organic waste: Using non-linear methods to handle water effects

Fast characterization of organic waste using near infrared spectroscopy (NIRS) has been successfully developed in the last decade. However, up to now, an on-site use of this technology has been hindered by necessary sample preparation steps (freeze-drying and grinding) to avoid important water effects on NIRS. Recent research studies have shown that these effects are highly non-linear and relate both to the biochemical and physical properties of samples. To account for these complex effects, the current study compares the use of many different types of non-linear methods such as partial least squares regression (PLSR) based methods (global, clustered and local versions of PLSR), machine learning methods (support vector machines, regression trees and ensemble methods) and deep learning methods (artificial and convolutional neural networks). On an independent test data set, non-linear methods showed errors 28% lower than linear methods. The standard errors of prediction obtained for the prediction of total solids content (TS%), chemical oxygen demand (COD) and biochemical methane potential (BMP) were respectively 8%, 160 mg(O₂).gTS^-1 and 92 mL(CH₄).gTS^-1_. These latter errors are similar to successful NIRS applications developed on freeze-dried samples. These findings hold great promises regarding the development of at-site and online NIRS solutions in anaerobic digestion plants.

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

Anaerobic co-digestion (AcoD) of corn silage (CS) and waste activated sludge (WAS) co-substrates, compared with anaerobic digestion (AD) of mono-substrate WAS, was simulated under mesophilic conditions with the adapted IWA Anaerobic Digestion Model No. 1 (ADM1), and a rule-based PID control system for control of the AcoD of CS and WAS, through control of their ratios in the feed, was developed, implemented with the model as a test platform. Tests on AcoD of co-substrates were conducted at the COD mass-based feeding ratios of CS to WAS 1:2.5, 1:2.0 and 1:1.2. The maximal biogas production was 0.94 m³/kgVS·d at the feeding ratio 1:1.2. The ADM1 was adapted, and the high-sensitivity kinetic parameters were calibrated and optimised using the data from the tests of steady state mono-digestion of WAS and AcoD of CS and WAS. The simulated data of biogas and methane production, methane content, VFA and pH agreed well with the test data. The rule-based PID control was developed with an additional expert system, in which the lower level controller operated the level of VFA/TIC and the upper level controller manipulated the setpoints of methane production. The feeding ratio of CS to WAS was used as a manipulated variable. With the constraint boundaries, the test on the control system showed that it could keep methane production stable to the setpoint and maximise methane production while resisting the disturbances to AcoD by adjusting the feeding ratios of CS to WAS.

Semi-continuous feeding combined with traditional domestication improved anaerobic performance during treatment of cassava stillage

The effects of feeding pattern were studied during anaerobic digestion of cassava stillage. Continuous feeding and semi-continuous feeding, were adopted in two internal circulation (IC) reactors (A and B, respectively). The reactors showed different performance in the anaerobic digestion process. The maximum difference, was observed for the soluble chemical oxygen demand (SCOD) removal rate and the biogas production, which were 23.2% and 95.7 L/2 d higher in reactor B than reactor A, respectively. The overall VFAs level of reactor A was higher than that of reactor B. Microbial community analyses indicated that the abundances of dominant bacteria and methanogens became higher in the reactor B than in reactor A as the digestion process progressed. Hence, semi-continuous feeding showed superior performance than continuous feeding for SCOD removal rate, biogas production, and the relative abundances of methanogens in the case of high OLR.

Influence of Pre-Hydrolysis on Sewage Treatment in an Up-Flow Anaerobic Sludge BLANKET (UASB) Reactor: A Review

The up-flow anaerobic sludge blanket (UASB) process has emerged as a promising high-rate anaerobic digestion technology for the treatment of low- to high-strength soluble and complex wastewaters. Sewage, a complex wastewater, contains 30–70% particulate chemical oxygen demand (CODP). These particulate organics degrade at a slower rate than the soluble organics found in sewage. Accumulation of non-degraded suspended solids can lead to a reduction of active biomass in the reactor and hence a deterioration in its performance in terms of acid accumulation and poor biogas production. Hydrolysis of the CODP in sewage prior to UASB reactor will ensure an increased organic loading rate and better UASB performance. While single-stage UASB reactors have been studied extensively, the two-phase full-scale treatment approach (i.e., a hydrolysis unit followed by an UASB reactor) has still not yet been commercialized worldwide. The concept of treating sewage containing particulate organics via a two-phase approach involves first hydrolyzing and acidifying the volatile suspended solids without losing carbon (as methane) in the first reactor and then treating the soluble sewage in the UASB reactor. This work reviews the available literature to outline critical findings related to the treatment of sewage with and without hydrolysis before the UASB reactor.

Modified Anaerobic Digestion Model No. 1 for modeling methane production from food waste in batch and semi-continuous anaerobic digestions

A modified Anaerobic Digestion Model No. 1 (ADM1) with optimized kinetic parameters was presented to model methane production in the anaerobic digestion of food waste. Experimental data from batch and semi-continuous fermentations were used to calibrate and verify the model. Modified ADM1 simulation was carried out using AQUASIM 2.0 software. Sensitivity analysis was used to identify and evaluate the most sensitive kinetic parameters during biogas production. The decay constant of microorganisms, the disintegration constant, the hydrolysis constant of carbohydrates, the Monod maximum specific substrate uptake rate, and the half-saturation constants affected biogas production significantly. The optimized values of these parameters were 0.001, 0.16, 3, 1 and 0.23, respectively. Optimization results were validated using batch and semi-continuous experiments. The modified ADM1 well-predicted methane production, with R² values for the validation experiments all above 90%. These results can be used as basic data to simulate methane production in full-scale reactors.

Co-digestion of solid waste: Towards a simple model to predict methane production

Modeling methane production is a key issue for solid waste co-digestion. Here, the effect of a step-wise increase in the organic loading rate (OLR) on reactor performance was investigated, and four new models were evaluated to predict methane yields using data acquired in batch mode. Four co-digestion experiments of mixtures of 2 solid substrates were conducted in semi-continuous mode. Experimental methane yields were always higher than the BMP values of mixtures calculated from the BMP of each substrate, highlighting the importance of endogenous production (methane produced from auto-degradation of microbial community and generated solids). The experimental methane productions under increasing OLRs corresponded well to the modeled data using the model with constant endogenous production and kinetics identified at 80% from total batch time. This model provides a simple and useful tool for technical design consultancies and plant operators to optimize the co-digestion and the choice of the OLRs.