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.

Adaptation of acidogenic sludge to increasing glycerol concentrations for biohydrogen production.

Hydrogen is a promising alternative as an energetic carrier and its production by dark fermentation from wastewater has been recently proposed, with special attention to crude glycerol as potential substrate. In this study, two different feeding strategies were evaluated for replacing the glucose substrate by glycerol substrate: a one-step strategy (glucose was replaced abruptly by glycerol) and a step-by-step strategy (progressive decrease of glucose concentration and increase of glycerol concentration from 0 to 5 g L(-1)), in a continuous stirred tank reactor (12 h of hydraulic retention time (HRT), pH 5.5, 35 °C). While the one-step strategy led to biomass washout and unsuccessful H2 production, the step-by-step strategy was efficient for biomass adaptation, reaching acceptable hydrogen yields (0.4 ± 0.1 molH2 mol(-1) glycerol consumed) around 33 % of the theoretical yield independently of the glycerol concentration. Microbial community structure was investigated by single-strand conformation polymorphism (SSCP) and denaturing gradient gel electrophoresis (DGGE) fingerprinting techniques, targeting either the total community (16S ribosomal RNA (rRNA) gene) or the functional Clostridium population involved in H2 production (hydA gene), as well as by 454 pyrosequencing of the total community. Multivariate analysis of fingerprinting and pyrosequencing results revealed the influence of the feeding strategy on the bacterial community structure and suggested the progressive structural adaptation of the community to increasing glycerol concentrations, through the emergence and selection of specific species, highly correlated to environmental parameters. Particularly, this work highlighted an interesting shift of dominant community members (putatively responsible of hydrogen production in the continuous stirred tank reactor (CSTR)) according to the gradient of glycerol proportion in the feed, from the family Veillonellaceae to the genera Prevotella and Clostridium sp., putatively responsible of hydrogen production in the CSTR.

Modelling ammonium-oxidizing population shifts in a biofilm reactor.

The dynamic reactor behaviour of a nitrifying inverse turbulent bed reactor, operated at varying loading rate, was described with a one-dimensional two-step nitrification biofilm model. In contrast with conventional biofilm models, this model includes the competition between two genetically different populations of ammonia-oxidizing bacteria (AOB), besides nitrite-oxidizing bacteria (NOB). Previously gathered experimental evidence showed that different loading rates in the reactor resulted in a change in the composition of the AOB community, besides a different nitrifying performance. The dissolved oxygen concentration in the bulk liquid was put forward as the key variable governing the experimentally observed shift from Nitrosomonas europaea (AOB1) to Nitrosomonas sp. (AOB2), which was confirmed by the developed one-dimensional biofilm model. Both steady state and dynamic analysis showed that the influence of microbial growth and endogenous respiration parameters as well as external mass transfer limitation have a clear effect on the competition dynamics. Overall, it was shown that the biomass distribution profiles of the coexisting AOB reflected the ecological niches created by substrate gradients.

Instrumentation, control and automation in wastewater--from London 1973 to Narbonne 2013.

Key developments of instrumentation, control and automation (ICA) applications in wastewater systems during the past 40 years are highlighted in this paper. From the first ICA conference in 1973 through to today there has been a tremendous increase in the understanding of the processes, instrumentation, computer systems and control theory. However, many developments have not been addressed here, such as sewer control, drinking water treatment and water distribution control. It is hoped that this review can stimulate new attempts to more effectively apply control and automation in water systems in the coming years.

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.

Biofilm model calibration and microbial diversity study using Monte Carlo simulations.

Mathematical models are useful tools for studying and exploring biological conversion processes as well as microbial competition in biological treatment processes. A single-species biofilm model was used to describe biofilm reactor operation at three different hydraulic retention times (HRT). The single-species biofilm model was calibrated with sparse experimental data using the Monte Carlo filtering method. This calibrated single-species biofilm model was then extended to a multi-species model considering 10 different heterotrophic bacteria. The aim was to study microbial diversity in bulk phase biomass and biofilm, as well as the competition between suspended and attached biomass. At steady state and independently of the HRT, Monte Carlo simulations resulted only in one unique dominating bacterial species for suspended and attached biomass. The dominating bacterial species was determined by the highest specific substrate affinity (ratio of µ/KS ). At a short HRT of 20 min, the structure of the microbial community in the bulk liquid was determined by biomass detached from the biofilm. At a long HRT of 8 h, both biofilm detachment and microbial growth in the bulk liquid influenced the microbial community distribution.

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.

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.

Modelling micro-pollutant fate in wastewater collection and treatment systems: status and challenges.

This paper provides a comprehensive summary on modelling of micro-pollutants' (MPs) fate and transport in wastewater. It indicates the motivations of MP modelling and summarises and illustrates the current status. Finally, some recommendations are provided to improve and diffuse the use of such models. In brief, we conclude that, in order to predict the contaminant removal in centralised treatment works, considering the dramatic improvement in monitoring and detecting MPs in wastewater, more mechanistic approaches should be used to complement conventional, heuristic and other fate models. This is crucial, as regional risk assessments and model-based evaluations of pollution discharge from urban areas can potentially be used by decision makers to evaluate effluent quality regulation, and assess upgrading requirements, in the future.

Benchmark simulation models, quo vadis?

As the work of the IWA Task Group on Benchmarking of Control Strategies for wastewater treatment plants (WWTPs) is coming to an end, it is essential to disseminate the knowledge gained. For this reason, all authors of the IWA Scientific and Technical Report on benchmarking have come together to provide their insights, highlighting areas where knowledge may still be deficient and where new opportunities are emerging, and to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The paper focuses on the topics of temporal and spatial extension, process modifications within the WWTP, the realism of models, control strategy extensions and the potential for new evaluation tools within the existing benchmark system. We find that there are major opportunities for application within all of these areas, either from existing work already being done within the context of the benchmarking simulation models (BSMs) or applicable work in the wider literature. Of key importance is increasing capability, usability and transparency of the BSM package while avoiding unnecessary complexity.

SoilFract: A mechanistic model accounting for the fate of exogenous organic matter in soil carbon and nitrogen cycles.

As its use in agriculture grows, the fate of digestate in soil raises concerns on many different levels. In particular, the degradability of its organic matter when spread on soil is still an ongoing topic. In an effort to better understand the processes and dynamics of digestate soil incubation, C and N mineralization kinetics obtained in 358 days long laboratory incubations during decomposition of digestates were simulated using a dynamic model. The model includes twelve compartments related through processes including 18 parameters. The main novelty of this model is the use of accessibility-related variables to describe the fate of exogenous organic matter in soil, thus enabling a detailed understanding of its outcome in soil. Model calibration on cattle manure digestate incubation resulted in the estimation of parameter values. The newly calibrated model was then tested on an energy crop digestate incubation experiment. The model was able to reproduce accurately the experimental behavior of most variables.

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.

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.

Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy.

The COST/IWA Benchmark Simulation Model No 1 (BSM1) has been available for almost a decade. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the research work related to the benchmark simulation models has resulted in more than 300 publications worldwide demonstrates the interest in and need of such tools within the research community. Recent efforts within the IWA Task Group on "Benchmarking of control strategies for WWTPs" have focused on an extension of the benchmark simulation model. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pretreatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In this paper, the finalised plant layout is summarised and, as was done for BSM1, a default control strategy is proposed. A demonstration of how BSM2 can be used to evaluate control strategies is also given.

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.

The algal trophic mode affects the interaction and oil production of a synergistic microalga-yeast consortium.

The use of non-food feedstocks to produce renewable microbial resources can limit our dependence on fossil fuels and lower CO2 emissions. Since microalgae display a virtuous CO2 and O2 exchange with heterotrophs, the microalga Chlamydomonas reinhardtii was combined with the oleaginous yeast Lipomyces starkeyi, known for their production of oil, base material for biodiesel. The coupled growth was shown to be synergistic for biomass and lipid production. The species were truly symbiotic since synergistic growth occurred even when the alga cannot use the organic carbon in the feedstock and in absence of air, thus depending entirely on CO2-O2 exchange. Since addition of acetate as the algal carbon source lowered the performance of the consortium, the microbial system design should take into account algal mixotrophy. The mixed biomass was found be suitable for biodiesel production, and whereas lipid production increased in the consortium, yields should be improved in future studies.

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 (Pmax) 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.

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.

Combined anaerobic digestion and biological nitrogen removal for piggery wastewater treatment: a modelling approach.

In order to deal with the environmental problems associated with animal production industrialization and at the same time considering energy costs increasing, a piggery wastewater treatment process consisting of combined anaerobic digestion and biological nitrogen removal by activated sludge was developed. This contribution presents a modelling framework in order to optimize this process. Modified versions of the well established ASM1 and ADM1 models have been used. The ADM1 was extended with biological denitrification. pH calculation and liquid gas-transfer were modified to take into account the effect of associated components. Finally, two interfaces (ADMtoASM and ASMtoADM) were built in order to combine both models. These interfaces set up the COD, nitrogen, alkalinity and charge fractionation between both models. However, for the mass balances between both models, some hypotheses were considered and might be evaluated.