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).

Determination of the optimal feed recipe of anaerobic digesters using a mathematical model and a genetic algorithm

Recently, numerous experimental studies have been undertaken to understand the interactions between different feedstocks in anaerobic digestion. They have unveiled the potential of blending substrates in the process. Nevertheless, these experiments are time-intensive, prompting the exploration of various optimization approaches. Notably, genetic algorithms have gained interest due to their population-based structures allowing them to efficiently yield multiple Pareto-optimal solutions in a single run. This study uses a simplified static anaerobic co-digestion model as the fitness function for a multi-objective optimization. The optimization aims to achieve a methane production set-point while reducing the output ammonia nitrogen and increasing the recipe' profitability. Thus, the study employs genetic algorithms to identify Pareto fronts and constraints confined the solution space within feasible boundaries. It also underscores the influence of economic considerations on the viable solution space. Ultimately, the optimal feed recipe not only ensures stable operations within the digester but also enhances associated profits.

Correlations between biochemical composition and biogas production during anaerobic digestion of microalgae and cyanobacteria isolated from different sources of Turkey

Twenty one species of microalgae and Cyanobacteria were isolated from different ecosystems in Turkey to investigate the relation between biochemical methane potential (BMP) and biochemical characterization. Since the highest dry weight (X), specific growth rate (µ) and maximum productivity (P_max) were obtained from the five species, identification of species and BMP tests with the composition analyzes were examined. BMP values were determined 308, 293, 242, 229 and 230 mLCH₄/gVS for Desertifilum tharense, Phormidium animale, Chlorella sp., Anabeana variabilis and Chlorophyta uncultured. The Pearson correlation and principal component analysis (PCA) were applied to extract and clarify the correlation between composition of species and their methane production. Pearson correlation shows that glucose, Kjeldahl nitrogen and chlorophyll are highly and positively correlated with BMP. PCA revealed that Chlorella sp., Chlorophyta uncultured and Desertifilum tharense were placed against Phormidium animale distinguished by its extreme and different profile because of Kjeldahl nitrogen and glucose content.

Optimal conditions for flexible methane production in a demand-based operation of biogas plants

The aim of the presented work was to study the methane production limits and to determine optimal conditions for flexible operation of an anaerobic reactor in order to set up an operational strategy. Punctual overloads were conducted in a laboratory-scale anaerobic reactor with readily biodegradable solid substrates, and the influences of overload intensity, baseload value and substrate used were investigated. A maximal daily value around 1000mL/L of reactor for methane production has been assessed. This value did not evolve significantly during experiment time, and conditioned the persistence of overloads as well as the flexibility margin on the reactor, which ranged from +25% to +140% on daily production. Results highlighted the fact that for a maximum flexibility, low organic loading rates are better to work with on this type of reactors.

Comparison of the mesophilic and thermophilic anaerobic digestion of spent cow bedding in leach-bed reactors

Anaerobic digestion of spent cow bedding in batch leach-bed reactors (LBRs) was compared in mesophilic and thermophilic conditions for the first time. Results show that the use of thermophilic conditions enhanced only the degradation kinetics of easily-degradable matter during the first days of the digestion, whereas similar methane yields (80% of the Biomethane Potential) were reached after 42days at both temperatures. Therefore, the anaerobic digestion in LBRs of spent cow bedding, a substrate rich in slowly-degradable compounds, was not improved in term of methane production considering the overall digestion time. Moreover, the high initial biogas production rate in thermophilic reactors was found to significantly reduce the energetic performance of the cogeneration unit at industrial scale, leading to a 5.9% decrease in the annual electricity production when compared to a mesophilic one.

Leachate flush strategies for managing volatile fatty acids accumulation in leach-bed reactors

In anaerobic leach-bed reactors (LBRs) co-digesting an easily- and a slowly-degradable substrate, the importance of the leachate flush both on extracting volatile fatty acids (VFAs) at the beginning of newly-started batches and on their consumption in mature reactors was tested. Regarding VFA extraction three leachate flush-rate conditions were studied: 0.5, 1 and 2Lkg^-1TSd^-1. Results showed that increasing the leachate flush-rate during the acidification phase is essential to increase degradation kinetics. After this initial phase, leachate injection is less important and the flush-rate could be reduced. The injection in mature reactors of leachate with an acetic acid concentration of 5 or 10gL^-1 showed that for an optimized VFA consumption in LBRs, VFAs should be provided straight after the methane production peak in order to profit from a higher methanogenic activity, and every 6-7h to maintain a high biogas production rate.

A fuzzy-logic-based controller for methane production in anaerobic fixed-film reactors

The main objective of this work was to develop a controller for biogas production in continuous anaerobic fixed-bed reactors, which used effluent total volatile fatty acids (VFA) concentration as control input in order to prevent process acidification at closed loop. To this aim, a fuzzy-logic-based control system was developed, tuned and validated in an anaerobic fixed-bed reactor at pilot scale that treated industrial winery wastewater. The proposed controller varied the flow rate of wastewater entering the system as a function of the gaseous outflow rate of methane and VFA concentration. Simulation results show that the proposed controller is capable to achieve great process stability even when operating at high VFA concentrations. Pilot results showed the potential of this control approach to maintain the process working properly under similar conditions to the ones expected at full-scale plants.

Mesophilic anaerobic digestion of several types of spent livestock bedding in a batch leach-bed reactor: substrate characterization and process performance

Spent animal bedding is a valuable resource for green energy production in rural areas. The properties of six types of spent bedding collected from deep-litter stables, housing either sheeps, goats, horses or cows, were compared and their anaerobic digestion in a batch Leach-Bed Reactor (LBR) was assessed. Spent horse bedding, when compared to all the other types, appeared to differ the most due to a greater amount of straw added to the litter and a more frequent litter change. Total solids content appeared to vary significantly from one bedding type to another, with consequent impact on the methane produced from the raw substrate. However, all the types of spent bedding had similar VS/TS (82.3-88.9)%, a C/N well-suited to anaerobic digestion (20-28, except that of the horse, 42) and their BMPs were in a narrow range (192-239NmLCH₄/gVS). The anaerobic digestion in each LBR was stable and the pH always remained higher than 6.6 regardless of the type of bedding. In contrast to all the other substrates, spent goat bedding showed a stronger acidification resulting in a methane production lag phase. Finally, spent bedding of different origins reached, on average, (89±11)% of their BMP after 60days of operation. This means that this waste is well-suited for treatment in LBRs and that this is a promising process to recover energy from dry agricultural waste.

Bioelectrochemical treatment of table olive brine processing wastewater for biogas production and phenolic compounds removal

Industry of table olives is widely distributed over the Mediterranean countries and generates large volumes of processing wastewaters (TOPWs). TOPWs contain high levels of organic matter, salt, and phenolic compounds that are recalcitrant to microbial degradation. This work aims to evaluate the potential of bioelectrochemical systems to simultaneously treat real TOPWs and recover energy. The experiments were performed in potentiostatically-controlled single-chamber systems fed with real TOPW and using a moderate halophilic consortium as biocatalyst. In conventional anaerobic digestion (AD) treatment, ie. where no potential was applied, no CH4 was produced. In comparison, Bio-Electrochemical Systems (BES) showed a maximum CH4 yield of 701 ± 13 NmL CH4·LTOPW(-1) under a current density of 7.1 ± 0.4 A m(-2) and with a coulombic efficiency of 30%. Interestingly, up to 80% of the phenolic compounds found in the raw TOPW (i.e. hydroxytyrosol and tyrosol) were removed. A new theoretical degradation pathway was proposed after identification of the metabolic by-products. Consistently, microbial community analysis at the anode revealed a clear and specific enrichment in anode-respiring bacteria (ARB) from the genera Desulfuromonas and Geoalkalibacter, supporting the key role of these electroactive microorganisms. As a conclusion, bioelectrochemical systems represent a promising bioprocess alternative for the treatment and energy recovery of recalcitrant TOPWs.

Combining pH and electrical conductivity measurements to improve titrimetric methods to determine ammonia nitrogen, volatile fatty acids and inorganic carbon concentrations

Volatile fatty acids (VFA), inorganic carbon (IC) and total ammonia nitrogen (TAN) are key variables in the current context of anaerobic digestion (AD). Accurate measurements like gas chromatography and infrared spectrometry have been developed to follow the concentration of these compounds but none of these methods are affordable for small AD units. Only titration methods answer the need for small plant monitoring. The existing methods accuracy was assessed in this study and reveals a lack of accuracy and robustness to control AD plants. To solve these issues, a new titrimetric device to estimate the VFA, IC and TAN concentrations with an improved accuracy was developed. This device named SNAC (System of titration for total ammonia Nitrogen, volatile fatty Acids and inorganic Carbon) has been developed combining the measurement of electrical conductivity and pH. SNAC were tested on 24 different plant samples in a range of 0-0.16 mol.L(-1) TAN, 0.01-0.21 mol.L(-1) IC and 0-0.04 mol.L(-1) VFA. The standard error was about 0.012 mol.L(-1) TAN, 0.015 mol.L(-1) IC and 0.003 mol.L(-1) VFA. The coefficient of determination R(2) between the estimated and reference data was 0.95, 0.94 and 0.95 for TAN, IC and VFA respectively. Using the same data, current methods based on key pH points lead to standard error more than 14.5 times higher on VFA and more than 1.2 times higher on IC. These results show that SNAC is an accurate tool to improve the management of AD plant.

Electrical conductivity as a state indicator for the start-up period of anaerobic fixed-bed reactors

The aim of this work was to analyse the applicability of electrical conductivity sensors for on-line monitoring the start-up period of an anaerobic fixed-bed reactor. The evolution of bicarbonate concentration and methane production rate was analysed. Strong linear relationships between electrical conductivity and both bicarbonate concentration and methane production rate were observed. On-line estimations of the studied parameters were carried out in a new start-up period by applying simple linear regression models, which resulted in a good concordance between both observed and predicted values. Electrical conductivity sensors were therefore identified as an interesting method for monitoring the start-up period of anaerobic fixed-bed reactors due to its reliability, robustness, easy operation, low cost, and minimum maintenance compared with the currently used sensors.

Biomass hydrolysis inhibition at high hydrogen partial pressure in solid-state anaerobic digestion

In solid-state anaerobic digestion, so-called ss-AD, biogas production is inhibited at high total solids contents. Such inhibition is likely caused by a slow diffusion of dissolved reaction intermediates that locally accumulate. In this study, we investigated the effect of H2 and CO2 partial pressure on ss-AD. Partial pressure of H2 and/or CO2 was artificially fixed, from 0 to 1 557mbars for H2 and from 0 to 427mbars for CO2. High partial pressure of H2 showed a significant effect on methanogenesis, while CO2 had no impact. At high [Formula: see text] , the overall substrate degradation decreased with no accumulation of metabolites from acidogenic bacteria, indicating that the hydrolytic activity was specifically impacted. Interestingly, such inhibition did not occur when CO2 was added with H2. This result suggests that CO2 gas transfer is probably a key factor in ss-AD from biomass.

Treatment of the biodegradable fraction of used disposable diapers by co-digestion with waste activated sludge

The results presented in this paper are part of a project aimed at designing an original solution for the treatment of used disposable diapers permitting the recycling of materials and the recovery of energy. Diapers must be collected separately at source and transported to an industrial facility to undergo special treatment which makes it possible to separate plastics and to recover a biodegradable fraction (BFD) made up mainly of cellulose. The methane yield of BFD was measured and found to be 280 ml CH4/g VSfed on average. 150 kg of dry BFD can be retrieved from the treatment of one ton of used disposable diapers, representing an energy potential of about 400 kW h of total energy or 130 kW h of electricity. As the treatment process for used diapers requires very high volumes of water, the setting up of the diaper treatment facility at a wastewater treatment plant already equipped with an anaerobic digester offers the advantages of optimizing water use as well as its further treatment and, also, the anaerobic digestion of BFD. The lab-scale experiments in a SBR showed that BFD co-digestion with sewage sludge (38% BFD and 62% waste activated sludge on volatile solids basis) was feasible. However, special attention should be paid to problems that might arise from the addition of BFD to a digester treating WAS such as insufficient mixing or floating particles leading to the accumulation of untreated solids in the digester.

French Brittany macroalgae screening: composition and methane potential for potential alternative sources of energy and products

Macroalgae are biomass resources that represent a valuable feedstock to be used entirely for human consumption or for food additives after some extractions (mainly colloids) and/or for energy production. In order to better develop the algal sector, it is important to determine the capacity of macroalgae to produce these added-values molecules for food and/or for energy industries on the basis of their biochemical characteristics. In this study, ten macroalgae obtained from French Brittany coasts (France) were selected. The global biochemical composition (proteins, lipids, carbohydrates, fibers), the presence and characteristics of added-values molecules (alginates, polyphenols) and the biochemical methane potential of these algae were determined. Regarding its biochemical composition, Palmaria palmata is interesting for food (rich in nutrients) and for anaerobic digestion (0.279 LCH4/gVS). Saccharina latissima could be used for alginate extraction (242 g/kgTS, ratio between mannuronic and guluronic acid M/G=1.4) and Sargassum muticum for polyphenol extraction (19.8 g/kgTS).

Benefit of sodium hydroxide pretreatment of ensiled sorghum forage on the anaerobic reactor stability and methane production

The assessment of the pretreatment effect on the anaerobic digestion process is generally based on the results of batch tests, which may fail in truly predicting full-scale anaerobic reactors performance. Therefore, in this study, the effect of alkaline pretreatment on the anaerobic digestion of ensiled sorghum forage was evaluated by comparing the results of two semi-continuous CSTR (Continuously Stirred Tank Reactor) anaerobic reactors. Results showed that an alkaline pretreatment step, prior to the anaerobic digestion of ensiled sorghum forage, can have a beneficial effect both in enhancing methane production (an increase of 25% on methane production was observed, if compared to that of untreated sorghum) and in giving more stability to the anaerobic digestion process.

Simulation of Organic Matter and Pollutant Evolution during Composting: The COP-Compost Model

Organic pollutants (OPs) are potentially present in composts and the assessment of their content and bioaccessibility in these composts is of paramount importance. In this work, we proposed a model to simulate the behavior of OPs and the dynamic of organic C during composting. This model, named COP-Compost, includes two modules. An existing organic C module is based on the biochemical composition of the initial waste mixture and simulates the organic matter transformation during composting. An additional OP module simulates OP mineralization and the evolution of its bioaccessibility. Coupling hypotheses were proposed to describe the interactions between organic C and OP modules. The organic C module, evaluated using experimental data obtained from 4-L composting pilots, was independently tested. The COP-Compost model was evaluated during composting experiments containing four OPs representative of the major pollutants detected in compost and targeted by current and future regulations. These OPs included a polycyclic aromatic hydrocarbon (fluoranthene), two surfactants (4--nonylphenol and a linear alkylbenzene sulfonate), and an herbicide (glyphosate). Residues of C-labeled OP with different bioaccessibility were characterized by sequential extraction and quantified as soluble, sorbed, and nonextractable fractions. The model was calibrated and coupling the organic C and OP modules improved the simulation of the OP behavior and bioaccessibility during composting.

Saponification pretreatment and solids recirculation as a new anaerobic process for the treatment of slaughterhouse waste

Different configurations of anaerobic process, adapted to the treatment of solid slaughterhouse fatty waste, were proposed and evaluated in this study. The tested configurations are based on the combination of anaerobic digestion with/without waste saponification pretreatment (70 °C during 60 min) and with/without recirculation of the digestate solid fraction (ratio=20% w/w). After an acclimation period of substrate pulses-feeding cycles, the reactors were operated in a semi-continuous feeding mode, increasing organic loading rates along experimental time. The degradation of the raw substrate was shown to be the bottleneck of the whole process, obtaining the best performance and process yields in the reactor equipped with waste pretreatment and solids recirculation. Saponification promoted the emulsification and bioavailability of solid fatty residues, while recirculation of solids minimized the substrate/biomass wash-out and induced microbial adaptation to the treatment of fatty substrates.

Effect of organic loading rate on anaerobic digestion of thermally pretreated Scenedesmus sp. biomass

Biogas production is one of the means to produce a biofuel from microalgae. Biomass consisting mainly of Scenedesmus sp. was thermally pretreated and optimum pretreatment length (1 h) and temperature (90 °C) was selected. Different chemical composition among batches stored at 4 °C for different lengths of time resulted in organic matter hydrolysis percentages ranging from 3% to 7%. The lower percentages were attributed to cell wall thickening observed during storage for 45 days. The different hydrolysis percentages did not cause differences in anaerobic digestion. Pretreatment of Scenedesmus sp. at 90 °C for 1h increased methane production 2.9 and 3.4-fold at organic loading rates (OLR) of 1 and 2.5 kg COD m(-3) day(-1), respectively. Regardless the OLR, inhibition caused by organic overloading or ammonia toxicity were not detected. Despite enhanced methane production, anaerobic biodegradability of this biomass remained low (32%). Therefore, this microalga is not a suitable feedstock for biogas production unless a more suitable pretreatment can be found.

Add Control: plant virtualization for control solutions in WWTP

This paper summarizes part of the research work carried out in the Add Control project, which proposes an extension of the wastewater treatment plant (WWTP) models and modelling architectures used in traditional WWTP simulation tools, addressing, in addition to the classical mass transformations (transport, physico-chemical phenomena, biological reactions), all the instrumentation, actuation and automation & control components (sensors, actuators, controllers), considering their real behaviour (signal delays, noise, failures and power consumption of actuators). Its ultimate objective is to allow a rapid transition from the simulation of the control strategy to its implementation at full-scale plants. Thus, this paper presents the application of the Add Control simulation platform for the design and implementation of new control strategies at the WWTP of Mekolalde.

Comparison of seven types of thermo-chemical pretreatments on the structural features and anaerobic digestion of sunflower stalks

Sunflower stalks can be used for the production of methane, but their recalcitrant structure requires the use of thermo-chemical pretreatments. Two thermal (55 and 170°C) and five thermo-chemical pretreatments (NaOH, H(2)O(2), Ca(OH)(2), HCl and FeCl(3)) were carried out, followed by anaerobic digestion. The highest methane production (259 ± 6 mL CH(4)g(-1) VS) was achieved after pretreatment at 55°C with 4% NaOH for 24h. Acidic pretreatments at 170°C removed more than 90% of hemicelluloses and uronic acids whereas alkaline and oxidative pretreatments were more effective in dissolving lignin. However, no pretreatment was effective in reducing the crystallinity of cellulose. Methane production rate was positively correlated with the amount of solubilized matter whereas methane potential was negatively correlated with the amount of lignin. Considering that the major challenge is obtaining increased methane potential, alkaline pretreatments can be recommended in order to optimize the anaerobic digestion of lignocellulosic substrates.

Comparison of ultrasound and thermal pretreatment of Scenedesmus biomass on methane production

Ultrasound at 20Hz was applied at different energy levels (Es) to treat Scenedesmus biomass, and organic matter solubilization, particle size distribution, cell disruption and biochemical methane potential were evaluated. An Es of 35.5 and 47.2MJ/kg resulted in floc deagglomeration but no improvement in methane production compared to untreated biomass. At an Es of 128.9, cell wall disruption was observed together with a 3.1-fold organic matter solubilization and an approximately 2-fold methane production in comparison with untreated biomass. Thermal pretreatment at 80°C caused cell wall disruption and improved anaerobic biodegradability 1.6-fold compared to untreated biomass. Since sonication caused a temperature increase in samples to as high as 85°C, it is likely that thermal effects accounted for much of the observed changes in the biomass. Given that ultrasound treatment at the highest Es studied only increased methane production by 1.2-fold over thermal treatment at 80°C, the higher energy requirement of sonication might not justify the use of this approach over thermal treatment.

Modelling of organic matter dynamics during the composting process

Composting urban organic wastes enables the recycling of their organic fraction in agriculture. The objective of this new composting model was to gain a clearer understanding of the dynamics of organic fractions during composting and to predict the final quality of composts. Organic matter was split into different compartments according to its degradability. The nature and size of these compartments were studied using a biochemical fractionation method. The evolution of each compartment and the microbial biomass were simulated, as was the total organic carbon loss corresponding to organic carbon mineralisation into CO(2). Twelve composting experiments from different feedstocks were used to calibrate and validate our model. We obtained a unique set of estimated parameters. Good agreement was achieved between the simulated and experimental results that described the evolution of different organic fractions, with the exception of some compost because of a poor simulation of the cellulosic and soluble pools. The degradation rate of the cellulosic fraction appeared to be highly variable and dependent on the origin of the feedstocks. The initial soluble fraction could contain some degradable and recalcitrant elements that are not easily accessible experimentally.

Effect of the addition of fatty by-products from the refining of vegetable oil on methane production in co-digestion

The purpose of this work was to investigate the effects of the addition of by-products from the refining of vegetable oil on the behavior of co-digestion reactors treating a mixture of grass, cow dung and fruit and vegetable waste. Three by-products were used: one soapstock, one used winterization earth and one skimming of aeroflotation of the effluents. Three 15 l reactors were run in parallel and fed five times a week. In a first phase of 4 weeks, the three reactors were fed with the co-digestion substrates alone (grass, cow dung and fruit and vegetable waste) at an organic loading rate (OLR) of 1.5 g VS/kg d (VS: volatile solids). Then, a different by-product from the refining of oil was added to the feed of each reactor at an OLR of 0.5 g VS/kg d, generating a 33% increase in the OLR. The results show that the addition of by-products from the refining of oil is an efficient way of increasing the methane production of co-digestion reactors thanks to high methane yield of such by-products (0.69-0.77 l CH(4)/g VS loaded). In fact, in this work, it was possible to raise the methane production of the reactors by about 60% through a 33% increase in the OLR thanks to the addition of the by-products from the refining of vegetable oil.

Thermal pre-treatment of aerobic granular sludge: impact on anaerobic biodegradability

The aerobic granular systems are a good alternative to the conventional activated sludge (AS) ones to reduce the production of sludge generated in wastewater treatment plants (WWTP). Although the quantity of produced sludge is low its post-treatment is still necessary. In the present work the application of the anaerobic digestion combined with a thermal pre-treatment was studied to treat two different aerobic granular biomasses: one from a reactor fed with pig manure (G1) and another from a reactor fed with a synthetic medium to simulate an urban wastewater (G2). The results obtained with the untreated aerobic granular biomasses showed that their anaerobic biodegradability (BD) (33% for G1 and 49% for G2) was similar to that obtained for an activated sludge (30-50%) and demonstrate the feasibility of their anaerobic digestion. The thermal pre-treatment before the anaerobic digestion was proposed as a good option to enhance the BD when this was initially low (33% G1) with an enhancement between 20% at 60 °C and 88% at 170 °C with respect to the untreated sludge. However when the initial BD was higher (49% G2) the thermal pre-treatment produced a slight improvement in the methane production (14% and 18%) and at high temperatures (190 and 210 °C) which did not justify the application of such a treatment.

Rapid measurement of the yield stress of anaerobically-digested solid waste using slump tests

The anaerobic digestion of solid waste is usually performed using dry or semi-dry technology. Incoming waste and fermenting digestate are pasty media and thus, at the industrial scale, their suitability for pumping and mixing is a prerequisite at the industrial scale. However, their rheology has been poorly characterised in the literature because there is no suitable experimental system for analysing heterogeneous media composed of coarse particles. We have developed a practical rheometrical test, a "slump test", for the analysis of actual digested solid waste. It makes it possible to estimate yield stress from the final slump height. From the slump behavior, we conclude that digestates behave as visco-elastic materials. The yield stress of different digested waste was measured between 200 and 800Pa. We show that the media containing smaller particles or with higher moisture content are characterised by smaller yield stresses. This study thus demonstrates the impact of the origin of the digestate on the yield stress.

First step towards a fast analytical method for the determination of Biochemical Methane Potential of solid wastes by near infrared spectroscopy

Methane can be produced by anaerobic digestion. The Biochemical Methane Potential (BMP) test is widely applied to determine the anaerobic biodegradability of wastes. It is based on a fermentation process, which is time consuming, about 30 days. This study investigates the use of near infrared spectroscopy to predict the Biochemical Methane Potential value of municipal solid waste. Near infrared spectroscopy has the advantage to be very fast and applicable to solid waste with a light sample preparation. Satisfying results were obtained: R(2)=0.76; Standard Error of Prediction=28 ml CH(4) g(-1) VS, that compare very favourably with reported results for other more expensive and more time-consuming methods. To our knowledge, it is the first time near infrared spectroscopy is used to predict the Biochemical Methane Potential value. Using near infrared spectroscopy for waste management would thus lead to a real benefit from an industrial point of view.

Combination of batch experiments with continuous reactor data for ADM1 calibration: application to anaerobic digestion of pig slurry

Modelling anaerobic digestion processes is a key aspect of studying and optimizing digesters and related waste streams. However, for the satisfactory prediction of biogas production and effluent characteristics, some parameters have to be calibrated according to the characteristics of the substrates. This article describes a calibration procedure for the IWA 'Anaerobic Digestion Model no. 1' applied to the modelling of a digester for treatment of pig slurry. The most sensitive parameters were selected and calibrated combining results from a continuous digester and from batch trials run with the sludge sampled from the digester and the addition of specific substrates. According to the sensitivity analysis, acetoclastic methanogenesis, acetogenesis of propionate and acidogenesis of sugars were identified as the main sensitive steps in our case. The calibration procedure led us to modify slightly acetogenesis of propionate kinetic. However, acetoclastic methanogenesis and acidogenesis of sugars kinetics were significantly reduced by decreasing km and increasing Ks. Indeed, for instance, a decrease of km_ac from 8 to 7 day(-1) combined with an increase of Ks_ac from 0.15 to 1.5 kgCOD/m3 was necessary. After calibration, ADM1 provides an accurate simulation of the continuous reactor results.

Pretreatment methods to improve sludge anaerobic degradability: a review

This paper presents a review of the main sludge treatment techniques used as a pretreatment to anaerobic digestion. These processes include biological (largely thermal phased anaerobic), thermal hydrolysis, mechanical (such as ultrasound, high pressure and lysis), chemical with oxidation (mainly ozonation), and alkali treatments. The first three are the most widespread. Emphasis is put on their impact on the resulting sludge properties, on the potential biogas (renewable energy) production and on their application at industrial scale. Thermal biological provides a moderate performance increase over mesophilic digestion, with moderate energetic input. Mechanical treatment methods are comparable, and provide moderate performance improvements with moderate electrical input. Thermal hydrolysis provides substantial performance increases, with a substantial consumption of thermal energy. It is likely that low impact pretreatment methods such as mechanical and thermal phased improve speed of degradation, while high impact methods such as thermal hydrolysis or oxidation improve both speed and extent of degradation. While increased nutrient release can be a substantial cost in enhanced sludge destruction, it also offers opportunities to recover nutrients from a concentrated water stream as mineral fertiliser.

A procedure to estimate proximate analysis of mixed organic wastes

In waste materials, proximate analysis measuring the total concentration of carbohydrate, protein, and lipid contents from solid wastes is challenging, as a result of the heterogeneous and solid nature of wastes. This paper presents a new procedure that was developed to estimate such complex chemical composition of the waste using conventional practical measurements, such as chemical oxygen demand (COD) and total organic carbon. The procedure is based on mass balance of macronutrient elements (carbon, hydrogen, nitrogen, oxygen, and phosphorus [CHNOP]) (i.e., elemental continuity), in addition to the balance of COD and charge intensity that are applied in mathematical modeling of biological processes. Knowing the composition of such a complex substrate is crucial to study solid waste anaerobic degradation. The procedure was formulated to generate the detailed input required for the International Water Association (London, United Kingdom) Anaerobic Digestion Model number 1 (IWA-ADM1). The complex particulate composition estimated by the procedure was validated with several types of food wastes and animal manures. To make proximate analysis feasible for validation, the wastes were classified into 19 types to allow accurate extraction and proximate analysis. The estimated carbohydrates, proteins, lipids, and inerts concentrations were highly correlated to the proximate analysis; correlation coefficients were 0.94, 0.88, 0.99, and 0.96, respectively. For most of the wastes, carbohydrate was the highest fraction and was estimated accurately by the procedure over an extended range with high linearity. For wastes that are rich in protein and fiber, the procedure was even more consistent compared with the proximate analysis. The new procedure can be used for waste characterization in solid waste treatment design and optimization.

Experimental and modeling investigations of a hybrid upflow anaerobic sludge-filter bed (UASFB) reactor

A 9.8-L hybrid UASFB reactor, in which the lower half was occupied by a sludge blanket and the upper half by small floating polyethylene media, was evaluated using wine distillery vinasse as substrate. The reactor was operated for a total period of 232 days at 33 + 1 degrees C. Continuous feeding of the reactor was started with an initial OLR of 2.9 g COD/L.d and then it was increased step wise to 19.5 g COD/L.d by increasing the feed COD, while maintaining a constant HRT (1.05 d). The reactor was equipped with a continuous internal recirculation system from top to the bottom at the rate of 9 L/h (upflow velocity = 0.83 m/h) upto day 159 and then it was reduced to about half on day 160 onwards. It was observed that the reduced recirculation rate did not affect the performance of the reactor with an average COD(t) and COD(s) removal efficiencies of 82 and 88%, respectively. A maximum gas production rate of 6.7 L CH(4)/L(reactor).d was achieved for the highest OLR applied. The specific activity analysis depicts that the activity of the attached biomass was more than 2 times higher than that of the granular sludge. The efficiency of liquid mixing was good through out this study. The packing medium had a dual role in the retention of the biomass inside the reactor: i.e. entrapment of biomass within the support and filtration of the granular biomass, preventing it from going out of the reactor. ADM1_10 model simulated well the dynamic evolutions of the main variables in the liquid as well as in the gas phases.

Modeling microbial diversity in anaerobic digestion

The aim of this study is to develop a modeling approach able to handle microbial diversity both in normal and abnormal situations. Normal situations are defined as changing input characteristics that do not imply process imbalance while abnormal situations are illustrated by the presence of toxicant into the reactor. In both cases, modeling is performed by adding a stochastic term on top of a well defined and well structured model such as the IWA Anaerobic Digestion Model No1. Experimental data from a 1 m3 pilot scale anaerobic digester treating wine distillery wastewater are provided to demonstrate the applicability of this approach. Discussion also highlights that monitoring of digesters might receive a renewed consideration in the near future in order to handle explicitly microbial diversity within the control objectives.

Use of modelling to evaluate best control practice for winery-type wastewaters

Winery wastewaters are high strength, and readily biodegradable, making them perfect for application of anaerobic digestion. However, inherent buffering against pH changes also requires some process knowledge and monitoring. They are therefore an important target for anaerobic process control. This has had limited application, but is emerging as an important research and development area. In this paper, we evaluate the use of model-based control analysis of a heavily loaded vinasse-fed reactor. Two controllers--both proportional-integral (PI)--on total volatile fatty acids (VFA) (< 500 mg/L), alkalinity (VFA/Total Alkalinity < 0.2) were evaluated in a fitted model, against the actual control mechanism used, which was model-based adaptive control. The two controllers were both less aggressive than the adaptive controller, producing less gas overall, but also using more caustic for pH control. The controllers were also evaluated against their ability to deal with noise, as PI controllers are relatively poor for controlling non-linear processes. The VFA controller was very poor with noise added, proving difficult to tune, and oscillatory. The alkalinity controller was effective with moderate detuning. This emphasizes the need to use effective controller inputs, when applying simple, linear controllers. Overall, use of a model was an effective method to evaluate the different controllers in a competitive way, in a standardized environment.

Towards a global multi objective optimization of wastewater treatment plant based on modeling and genetic algorithms

The optimization of the Benchmark Simulation Model 1 (BSM1) through a multi objective genetic algorithm (MOGA) is studied in this paper. First, the optimization of the set points of the two Proportional Integral (PI) controllers proposed in BSM1 is performed. Then, a new controller layout composed of three PI controllers is proposed and the set points are also optimized. Among all performance indexes proposed in BSM1, only the effluent quality and the energy consumption for pumping and aeration were taken into account in both optimization problems. Since these two objectives are conflicting, the use of the MOGA allows in both cases a direct visualization of the possible trade-offs through a Pareto curve. These two case studies showed the feasibility of such optimizations even when dealing with computing intensive model like the full scale waste water treatment plant (WWTP) model.

Influence of closed loop control on microbial diversity in a nitrification process

This paper compares two control strategies for a nitrification process. The objective is to achieve partial nitrification and thus to accumulate nitrite instead of nitrate. To this end, change in temperature setpoint and active control of oxygen and ammonia concentrations are evaluated in the long term. Evaluation is made on the control performances that are obtained, but also--and more importantly--on the microbial diversity. In particular, it is shown that the combined oxygen and ammonia control strategy is more appropriate since shift in the temperature setpoint strongly affects the composition of the microbial ecosystem present in the reactor whereas active control of oxygen and ammonia does not.

A review of ADM1 extensions, applications, and analysis: 2002-2005

Since publication of the Scientific and Technical Report (STR) describing the ADM1, the model has been extensively used, and analysed in both academic and practical applications. Adoption of the ADM1 in popular systems analysis tools such as the new wastewater benchmark (BSM2), and its use as a virtual industrial system can stimulate modelling of anaerobic processes by researchers and practitioners outside the core expertise of anaerobic processes. It has been used as a default structural element that allows researchers to concentrate on new extensions such as sulfate reduction, and new applications such as distributed parameter modelling of biofilms. The key limitations for anaerobic modelling originally identified in the STR were: (i) regulation of products from glucose fermentation, (ii) parameter values, and variability, and (iii) specific extensions. Parameter analysis has been widespread, and some detailed extensions have been developed (e.g., sulfate reduction). A verified extension that describes regulation of products from glucose fermentation is still limited, though there are promising fundamental approaches. This is a critical issue, given the current interest in renewable hydrogen production from carbohydrate-type waste. Critical analysis of the model has mainly focused on model structure reduction, hydrogen inhibition functions, and the default parameter set recommended in the STR. This default parameter set has largely been verified as a reasonable compromise, especially for wastewater sludge digestion. One criticism of note is that the ADM1 stoichiometry focuses on catabolism rather than anabolism. This means that inorganic carbon can be used unrealistically as a carbon source during some anabolic reactions. Advances and novel applications have also been made in the present issue, which focuses on the ADM1. These papers also explore a number of novel areas not originally envisaged in this review.

Lessons learnt from 15 years of ICA in anaerobic digesters

Anaerobic digestion plants are highly efficient wastewater treatment processes with inherent energy production. Despite these advantages, many industries are still reluctant to use them because of their instability confronted with changes in operating conditions. There is therefore great potential for application of instrumentation, control and automation (ICA) in the field of anaerobic digestion. This paper will discuss the requirements (in terms of on-line sensors needed, modelling efforts and mathematical complexity) but also the advantages and drawbacks of different control strategies that have been applied to AD high rate processes over the last 15 years.

Modular expert system for the diagnosis of operating conditions of industrial anaerobic digestion plants

Anaerobic digestion (AD) plants are highly efficient wastewater treatment processes with possible energetic valorisation. Despite these advantages, many industries are still reluctant to use them because of their instability in the face of changes in operating conditions. To the face this drawback and to enhance the industrial use of anaerobic digestion, one solution is to develop and to implement knowledge base (KB) systems that are able to detect and to assess in real-time the quality of operating conditions of the processes. Case-based techniques and heuristic approaches have been already tested and validated on AD processes but two major properties were lacking: modularity of the system (the knowledge base system should be easily tuned on a new process and should still work if one or more sensors are added or removed) and uncertainty management (the assessment of the KB system should remain relevant even in the case of too poor or conflicting information sources). This paper addresses these two points and presents a modular KB system where an uncertain reasoning formalism is used to combine partial and complementary fuzzy diagnosis modules. Demonstration of the interest of the approach is provided from real-life experiments performed on an industrial 2,000 m3 CSTR anaerobic digester.

Kinetic parameters estimation in an anaerobic digestion process using successive quadratic programming

In this work, an optimization method is implemented in an anaerobic digestion model to estimate its kinetic parameters and yield coefficients. This method combines the use of advanced state estimation schemes and powerful nonlinear programming techniques to yield fast and accurate estimates of the aforementioned parameters. In this method, we first implement an asymptotic observer to provide estimates of the non-measured variables (such as biomass concentration) and good guesses for the initial conditions of the parameter estimation algorithm. These results are then used by the successive quadratic programming (SQP) technique to calculate the kinetic parameters and yield coefficients of the anaerobic digestion process. The model, provided with the estimated parameters, is tested with experimental data from a pilot-scale fixed bed reactor treating raw industrial wine distillery wastewater. It is shown that SQP reaches a fast and accurate estimation of the kinetic parameters despite highly noise corrupted experimental data and time varying inputs variables. A statistical analysis is also performed to validate the combined estimation method. Finally, a comparison between the proposed method and the traditional Marquardt technique shows that both yield similar results; however, the calculation time of the traditional technique is considerable higher than that of the proposed method.

Robust interval-based regulation for anaerobic digestion processes

A robust regulation law is applied to the stabilization of a class of biochemical reactors exhibiting partially known highly nonlinear dynamic behavior. An uncertain environment with the presence of unknown inputs is considered. Based on some structural and operational conditions, this regulation law is shown to exponentially stabilize the aforementioned bioreactors around a desired set-point. This approach is experimentally applied and validated on a pilot-scale (1 m3) anaerobic digestion process for the treatment of raw industrial wine distillery wastewater where the objective is the regulation of the chemical oxygen demand (COD) by using the dilution rate as the manipulated variable. Despite large disturbances on the input COD and state and parametric uncertainties, this regulation law gave excellent performances leading the output COD towards its set-point and keeping it inside a pre-specified interval.

Sensors network diagnosis in anaerobic digestion processes using evidence theory

Instrumentation defines a sensors network on a process. Hardware sensors indeed allow one to get different information sources that can be often cross-checked to provide reliable data. However, each of these sources of information contains some uncertainties, either due to the hardware sensors' measurement principles, to their possible fouling, to the estimated parameters of the models used in software sensors and/or to the specific structures of the software sensors. This paper demonstrates that, in this context, the evidence theory is a very well suited formalism for fault detection and diagnosis. This theory indeed allows one to take into account the exact knowledge supported by each source of information and to combine them in order to detect the occurring faults. Moreover, this combination guarantees the best fault isolability from a practical point of view and is suitable for multiple faults occurring at the same time. Finally, the evidence theory is a highly modular formalism since new information sources can be very easily added and old ones can be removed. Validation is performed using real-life experiments from a 1 m3 anaerobic digestion fixed bed process used applied to the treatment of winery wastewaters.

Dynamic evaluation of a fixed bed anaerobic digestion process in response to organic overloads and toxicant shock loads

This paper details a dynamic evaluation of a 1 m3 fixed bed anaerobic digestion reactor in response to organic overloads and toxicant shock loads. Raw industrial wine distillery wastewater was used as a reference substrate and several disturbances were applied to the process: (i) organic overloads with and without pH regulation in the feeding line, (ii) adding of ammonia in the input wastewater. The purpose of this study was to assess, using on-line instrumentation, the robustness of a fixed bed anaerobic digester. Anaerobic digestion processes have the reputation of being difficult to operate and prone to process instability due to external disturbances and the objective of this study was to demonstrate the possibility of such a reactor configuration for industrial use.

Automatic control of volatile fatty acids in anaerobic digestion using a fuzzy logic based approach

A control law based on fuzzy logic was developed and validated for an anaerobic wastewater treatment process. The controlled variable was the concentration of volatile fatty acids (VFA) in the reactor and the manipulated variable was the input flow rate. In order to use it as the input of the fuzzy sets, the controlled variable was treated using an algorithm of interpolation, extrapolation and filtering. The treatment of VFA values attempted to anticipate the behaviour of the variable and to avoid the inherent delay of the response, associated to the time constant of the system. Furthermore, the controlled variable derivative was used as a second input of the fuzzy sets to increase or decrease the speed of the control action. The control law was applied to a 0.948 m3 fixed-bed anaerobic reactor treating raw and diluted (1:2) industrial distillery vinasses. The validation was performed establishing different transient states between different set points in the range of 0.8 and 1.8 g VFA/l and different concentrations of the influent. The control law proved to be reliable supplying an adequate control action in terms of amplitude and velocity to achieve the desired set point for different types of perturbation and control purposes.

Robust regulation of anaerobic digestion processes

This paper deals with the problem of controlling anaerobic digestion processes. A two-step (i.e. acidogenesis-methanization) mass balance model is considered for a 1 m3 fixed bed digester treating industrial wine distillery wastewater. The control law aims at regulating the organic pollution level while avoiding washout of biomass. To this end, a simple output feedback controller is considered which regulates a variable strongly related to the Chemical Oxygen Demand (COD). Numerical simulations assuming noisy measurements first illustrate the robustness of this control procedure. Then, the regulating procedure is implemented on the considered anaerobic digestion process in order to validate and demonstrate its efficiency in real life experiments.

Application of a variable structure model in observation and control of an anaerobic digestor

In this work, a variable structure model (VSM) of an anaerobic digestion process was developed. The anaerobic biodegradation process was described by four nonlinear submodels representing methanogenic, chemical oxygen demand overload, acidogenic, and hydrogen-inhibited states of the anaerobic process. At any instant, process dynamics was modeled only by one of the submodels, while the others were considered trailing. The choice of a leading submodel was handled by a knowledge-based system, which analyzed available process variables, such as off-gas composition and reactor pH. The feasibility of the proposed method was demonstrated both by using the VSM to predict the outputs of a comprehensive process model, and the experimental results obtained in a pilot scale anaerobic fixed-bed bioreactor.

Software sensors for highly uncertain WWTPs: a new approach based on interval observers

This paper presents the practical implementation of a new robust interval observer on a 1 m3 continuous fixed bed anaerobic reactor used for the treatment of industrial wine distillery wastewater. This interval observer is able to generate guaranteed intervals for the unmeasured variables (i.e. acidogenic and methanogenic bacteria, alkalinity and chemical oxygen demand) from few on-line measurements (i.e. input liquid flow rate, CO2 gaseous flow rate, volatile fatty acids and total inorganic carbon). The main advantage of this approach is its independance with respect to disturbances and uncertainty in the initial conditions, in the kinetics and, last but not least, in the process inputs.

Evaluation of a four year experience with a fully instrumented anaerobic digestion process

For several years, a 1 m3 fixed bed anaerobic digestion process has been operated for the treatment of distillery vinasses. This reactor has been fully instrumented with the following variables available on-line: pH, temperature, liquid and gas flow rates, gas composition (i.e., CH4, CO2 and H2), concentration of bicarbonate, chemical oxygen demand, total organic carbon, volatile fatty acids and partial and total alkalinity, these last four variables being measured twice by different techniques (i.e., using a TOC analyzer, a titrimetric sensor and an infrared spectrometer). The purpose of this paper is to compare the respective benefits of advanced instrumentation for the monitoring of wastewater treatment processes in general, and for anaerobic digestion in particular. It will also provide some statistical analysis of the time required to operate a fully instrumented wastewater treatment process. It is indeed well admitted in the literature that instrumentation is usually the main limitation step for using closed-loop control. However, it is our opinion that, in the near future, this situation will change. This point is discussed based on our four years practical experience.

Model based prediction of the clogging of an anaerobic fixed bed reactor

This paper presents the use of nonlinear constrained optimization techniques in order to detect and evaluate the degree of clogging in an anaerobic fixed bed reactor. First, experimental results show that the validity of a mass balance model can degrade over the time. Using the available model of the process and nonlinear constrained optimization tools, it is established that these changes can be due to the decrease of the liquid volume into the reactor while the mean values of biomass concentrations increase, leading to the clogging of the reactor. These theoretical results are confirmed experimentally in evaluating the hydraulic retention time of the reactor using a tracer.

Dynamical model development and parameter identification for an anaerobic wastewater treatment process

This paper deals with the development and the parameter identification of an anaerobic digestion process model. A two-step (acidogenesis-methanization) mass-balance model has been considered. The model incorporates electrochemical equilibria in order to include the alkalinity, which has to play a central role in the related monitoring and control strategy of a treatment plant. The identification is based on a set of dynamical experiments designed to cover a wide spectrum of operating conditions that are likely to take place in the practical operation of the plant. A step by step identification procedure to estimate the model parameters is presented. The results of 70 days of experiments in a 1-m(3) fermenter are then used to validate the model.

Software sensor design for COD estimation in an anaerobic fluidized bed reactor

In this paper, a method for unknown input estimation in stochastic system is presented. A key problem in bioprocess systems is the absence, in some cases, of reliable on-line measurements for real time monitoring applications. In this paper, a software sensor for an anaerobic digester is presented. Unmeasured components of the influent are estimated from available on-line measurements. Unknown input Kalman filter is discussed to estimate the state and unknown input of the process. First, the theory of unknown inputs optimal filtering in the stochastic case is exposed and a design procedure is proposed. The observer is applied to an anaerobic fluidized bed reactor to estimate the variations in Chemical Oxygen Demand (COD) concentration and experimental results are presented.

Advanced monitoring and control of anaerobic wastewater treatment plants: fault detection and isolation

In this paper, a fault detection and isolation approach using fuzzy logic is described for on-line analysis of problems occurring in anaerobic digestion processes. The measurements available on the process are preprocessed to build a vector of fault residuals indicating the magnitude of the problems. This vector is classified into a prespecified category (i.e., a class) which is a state of the system, according to discrimination fuzzy rules. Three different types of classes were defined in a hierarchical structure: sensors faults, sub-process faults and process faults. This approach was developed to handle in real time both technical and biological problems. Demonstration of the practical interest of this study was made using real life experiments and large improvement of the reliability and safety of the process was obtained, thus optimizing the overall wastewater treatment.