Agronomic characterization of anaerobic digestates with near-infrared spectroscopy.

Anaerobic digestion is an increasingly widespread process for organic waste treatment and renewable energy production due to the methane content of the biogas. This biological process also produces a digestate (i.e., the remaining content of the waste after treatment) with a high fertilizing potential. The digestate composition is highly variable due to the various organic wastes used as feedstock, the different plant configurations, and the post-treatment processes used. In order to optimize digestate spreading on agricultural soils by optimizing the fertilizer dose and, thus, reducing environmental impacts associated to digestate application, the agronomic characterization of digestate is essential. This study investigates the use of near infrared spectroscopy for predicting the most important agronomic parameters from freeze-dried digestates. A data set of 193 digestates was created to calibrate partial least squares regression models predicting organic matter, total organic carbon, organic nitrogen, phosphorus, and potassium contents. The calibration range of the models were between 249.8 and 878.6 gOM.kgDM-1, 171.9 and 499.5 gC.kgDM-1, 5.3 and 74.1 gN.kgDM-1, 2.7 and 44.9 gP.kgDM-1 and between 0.5 and 171.8 gK.kgDM-1, respectively. The calibrated models reliably predicted organic matter, total organic carbon, and phosphorus contents for the whole diversity of digestates with root mean square errors of prediction of 70.51 gOM.kgDM-1, 34.84 gC.kgDM-1 and 4.08 gP.kgDM-1, respectively. On the other hand, the model prediction of the organic nitrogen content had a root mean square error of 7.55 gN.kgDM-1 and was considered as acceptable. Lastly, the results did not demonstrate the feasibility of predicting the potassium content in digestates with near infrared spectroscopy. These results show that near infrared spectroscopy is a very promising analytical method for the characterization of the fertilizing value of digestates, which could provide large benefits in terms of analysis time and cost.

Relating Near-Infrared Light Path-Length Modifications to the Water Content of Scattering Media in Near-Infrared Spectroscopy: Toward a New Bouguer-Beer-Lambert Law.

In near-infrared spectroscopy (NIRS), the linear relationship between absorbance and an absorbing compound concentration has been strictly defined by the Bouguer-Beer-Lambert law only for the case of transmission measurements of nonscattering media. However, various quantitative calibrations have been successfully built both on reflectance measurements and for scattering media. Although the lack of linearity for scattering media has been observed experimentally, the sound multivariate statistics and signal processing involved in chemometrics have allowed us to overcome this problem in most cases. However, in the case of samples with varying water content, important modifications of scattering levels still make calibrations difficult to build due to nonlinearities. Moreover, even when calibration procedures are successfully developed, many preprocessing methods used do not guarantee correct spectroscopic assignments (in the sense of a pure chemical absorbance). In particular, this may prevent correct modeling and interpretation of the structure of water. In this study, dynamic near-infrared spectra acquired during a drying process allow the study of the physical effects of water content variations, with a focus on the first overtone OH absorbance region. A model sample consisting of aluminum pellets mixed with water allowed us to study this specifically, without any other absorbing interaction terms related to the dry mass-absorbing constituents. A new formulation of the Bouguer-Beer-Lambert law is proposed, by expressing path length as a power function of water content. Through this new formulation, it is shown that a better and simpler prediction model of water content may be developed, with more precise and accurate identification of water absorbance bands.

Balancing Microalgae and Nitrifiers for Wastewater Treatment: Can Inorganic Carbon Limitation Cause an Environmental Threat?

The first objective of this study is to assess the predictive capability of the ALBA (ALgae-BActeria) model for a pilot-scale (3.8 m2) high-rate algae-bacteria pond treating agricultural digestate. The model, previously calibrated and validated on a one-year data set from a demonstrative-scale raceway (56 m2), successfully predicted data from a six-month monitoring campaign with a different wastewater (urban wastewater) under different climatic conditions. Without changing any parameter value from the previous calibration, the model accurately predicted both online monitored variables (dissolved oxygen, pH, temperature) and off-line measurements (nitrogen compounds, algal biomass, total and volatile suspended solids, chemical oxygen demand). Supported by the universal character of the model, different scenarios under variable weather conditions were tested, to investigate the effect of key operating parameters (hydraulic retention time, pH regulation, kLa) on algae biomass productivity and nutrient removal efficiency. Surprisingly, despite pH regulation, a strong limitation for inorganic carbon was found to hinder the process efficiency and to generate conditions that are favorable for N2O emission. The standard operating parameters have a limited effect on this limitation, and alkalinity turns out to be the main driver of inorganic carbon availability. This investigation offers new insights in algae-bacteria processes and paves the way for the identification of optimal operational strategies.

Insights into bioflocculation of filamentous cyanobacteria, microalgae and their mixture for a low-cost biomass harvesting system.

Cyanobacteria and microalgae are considered as interesting feedstocks for either the production of high value bio-based compounds and biofuels or wastewater treatment. Nevertheless, the high costs of production, mainly due to the harvesting process, hamper a wide commercialization of industrial cyanobacteria and microalgae based products. Recent studies have found in autoflocculation and bioflocculation promising spontaneous processes for a low-cost and environmentally sustainable cyanobacteria and microalgae biomass harvesting process. In the present work, bioflocculation process has been studied for three different inocula: filamentous cyanobacteria, microalgae and their mixture. Their cultivation has been conducted in batch mode using two different cultivation media: synthetic aqueous solution and urban wastewater. The removal of nutrients and flocculation process performance were monitored during the entire cultivation time. Results have proved that bioflocculation and sedimentation processes occur efficiently for filamentous cyanobacteria cultivated in synthetic aqueous solution, whereas such processes are less efficient in urban wastewater due to the specific characteristics of this medium that prevent bioflocculation to occur. Besides different efficiencies associated to cultivation media, this work highlighted that bioflocculation of sole microalgae is not as effective as when they are cultivated together with filamentous cyanobacteria.

Bioflocculation and settling studies of native wastewater filamentous cyanobacteria using different cultivation systems for a low-cost and easy to control harvesting process.

Bioflocculation phenomena for filamentous cyanobacteria were studied and analysed in two different cultivation systems (i.e. based on air-bubbling and on shaking) and for different initial biomass concentrations. Floc formation and biomass settling were monitored during batch cultivation tests according to an innovative protocol. Results showed that the two cultivation systems enhanced two different flocculation behaviours: air bubbling led to the formation of small and dense flocs, while the shaking table resulted in larger (14 mm2 vs 4 mm2) but mechanically weaker flocs. Floc analysis evidenced that the different mixing systems also affected the speciation of biomass. A mathematical model was developed to simulate and predict the settling performance during the bioflocculation process of filamentous cyanobacteria. Natural settling was examined at different phases of biomass growth. Optimal conditions were obtained at the end of the exponential growth phase, when 70% of the total cultivated biomass could be recovered.

Microalgae-bacteria consortia in high-rate ponds for treating urban wastewater: Elucidating the key state indicators under dynamic conditions.

On-line performance indicators of a microalgae-bacteria consortium were screened out from different variables based on pH and dissolved oxygen on-line measurements via multivariate projection analysis, aiming at finding on-line key state indicators to easily monitor the process. To fulfil this objective, a pilot-scale high-rate pond for urban wastewater treatment was evaluated under highly variable conditions, i.e. during the start-up period. The system was started-up without seed of either bacterial or microalgal biomass. It took around 19 days to fully develop a microalgal community assimilating nutrients significantly. Slight increases in the biomass productivities in days 26-30 suggest that the minimum time for establishing a performant bacteria-microalgae consortium could be of around one month for non-inoculated systems. At this point, the process was fully functional, meeting the European discharge limits for protected areas. The results of the statistical analyses show that both the pH and the dissolved oxygen concentration represent accurately the biochemical processes taking place under the start-up of the process. Both pH and dissolved oxygen represented accurately also the performance of the high-rate algal pond, being affordable, easily-implemented, options for monitoring, control and optimization of industrial-scale processes.

Data-driven fault detection methods for detecting small-magnitude faults in anaerobic digestion process.

Early detection of small-magnitude faults in anaerobic digestion (AD) processes is a mandatory step for preventing serious consequence in the future. Since volatile fatty acids (VFA) accumulation is widely suggested as a process health indicator, a VFA soft-sensor was developed based on support vector machine (SVM) and used for generating the residuals by comparing real and predicted VFA. The estimated residual signal was applied to univariate statistical control charts such as cumulative sum (CUSUM) and square prediction error (SPE) to detect the faults. A principal component analysis (PCA) model was also developed for comparison with the aforementioned approach. The proposed framework showed excellent performance for detecting small-magnitude faults in the state parameters of AD processes.

Fault detection and diagnosis in water resource recovery facilities using incremental PCA.

Because of the static nature of conventional principal component analysis (PCA), natural process variations may be interpreted as faults when it is applied to processes with time-varying behavior. In this paper, therefore, we propose a complete adaptive process monitoring framework based on incremental principal component analysis (IPCA). This framework updates the eigenspace by incrementing new data to the PCA at a low computational cost. Moreover, the contribution of variables is recursively provided using complete decomposition contribution (CDC). To impute missing values, the empirical best linear unbiased prediction (EBLUP) method is incorporated into this framework. The effectiveness of this framework is evaluated using benchmark simulation model No. 2 (BSM2). Our simulation results show the ability of the proposed approach to distinguish between time-varying behavior and faulty events while correctly isolating the sensor faults even when these faults are relatively small.

Modelling non-ideal bio-physical-chemical effects on high-solids anaerobic digestion of the organic fraction of municipal solid waste.

This study evaluates the main effects of including 'non-ideal' bio-physical-chemical corrections in high-solids anaerobic digestion (HS-AD) of the organic fraction of municipal solid waste (OFMSW), at total solid (TS) between 10 and 40%. As a novel approach, a simple 'non-ideal' module, accounting for the effects of ionic strength (I) on the main acid-base equilibriums, was coupled to a HS-AD model, to jointly evaluate the effects of 'non-ideality' and the TS content dynamics on the HS-AD bio-physical-chemistry. 'Non-ideality' influenced the pH, concentration of inhibitors (i.e. NH3), and liquid-gas transfer (i.e. CO2), particularly at higher TS (i.e. ≥ 20%). Meanwhile, fitting the experimental data for batch assays at 15% TS showed that HS-AD of OFMSW might be operated at I ≥ 0.5 M. Therefore, all HS-AD simulations should account for 'non-ideal' corrections, when assessing the main inhibitory mechanisms (i.e. NH3 buildup and acidification) potentially occurring in HS-AD of OFMSW.

Influence of process dynamics on the microbial diversity in a nitrifying biofilm reactor: Correlation analysis and simulation study.

For engineers, it is interesting to gain insight in the effect of control strategies on microbial communities, on their turn influencing the process behavior and its stability. This contribution assesses the influence of process dynamics on the microbial community in a biofilm reactor for nitrogen removal, which was controlled according to several strategies aiming at nitrite accumulation. The process dataset, combining conventional chemical and physical data with molecular information, was analyzed through a correlation analysis and in a simulation study. During nitrate formation, an increased nitrogen loading rate (NLR) resulted in a drop of the bulk liquid oxygen concentration without resulting in nitrite accumulation. A biofilm model was able to reproduce the bulk liquid nitrogen concentrations in two periods before and after this increased NLR. As the microbial parameters calibrated for the ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) in both periods were different, it was concluded that the increased NLR governed an AOB and NOB population shift. Based on the molecular data, it was assumed that each period was typified by one dominant AOB and probably several subdominant NOB populations. The control strategies for nitrite accumulation influenced the bulk liquid composition by controlling the competition between AOB and NOB. Biotechnol. Bioeng. 2016;113: 1962-1974. © 2016 Wiley Periodicals, Inc.

Vertebrate bacterial gut diversity: size also matters.

BACKGROUND: One of the central issues in microbial ecology is to understand the parameters that drive diversity. Among these parameters, size has often been considered to be the main driver in many different ecosystems. Surprisingly, the influence of size on gut microbial diversity has not yet been investigated, and so far in studies reported in the literature only the influences of age, diet, phylogeny and digestive tract structures have been considered. This study explicitly challenges the underexplored relationship connecting gut volume and bacterial diversity. RESULTS: The bacterial diversity of 189 faeces produced by 71 vertebrate species covering a body mass range of 5.6 log. The animals comprised mammals, birds and reptiles. The diversity was evaluated based on the Simpson Diversity Index extracted from 16S rDNA gene fingerprinting patterns. Diversity presented an increase along with animal body mass following a power law with a slope z of 0.338 ± 0.027, whatever the age, phylogeny, diet or digestive tract structure. CONCLUSIONS: The results presented here suggest that gut volume cannot be neglected as a major driver of gut microbial diversity. The characteristics of the gut microbiota follow general principles of biogeography that arise in many ecological systems.

Comparison of Chlorella vulgaris and cyanobacterial biomass: cultivation in urban wastewater and methane production.

Anaerobic digestion of microalgae is hampered by its complex cell wall. Against this background, cyanobacteria cell walls render this biomass as an ideal substrate for overcoming this drawback. The aim of the present study was to compare the growth of two cyanobacteria (Aphanizomenon ovalisporum and Anabaena planctonica) and a microalga (Chlorella vulgaris) in urban wastewater when varying the temperature (22, 27 and 32 °C). Cyanobacterial optimal growth for both strains was attained at 22 °C, while C. vulgaris did not show remarkable differences among temperatures. For all the microorganisms, ammonium removal was higher than phosphate. Biomass collected was subjected to anaerobic digestion. Methane yield of C. vulgaris was 184.8 mL CH4 g COD in(-1) while with A. ovalisporum and A. planctonica the methane production was 1.2- and 1.4-fold higher. This study showed that cyanobacteria growth rates could be comparable to microalgae while presenting the additional benefit of an increased anaerobic digestibility.

A state of the art of metabolic networks of unicellular microalgae and cyanobacteria for biofuel production.

The most promising and yet challenging application of microalgae and cyanobacteria is the production of renewable energy: biodiesel from microalgae triacylglycerols and bioethanol from cyanobacteria carbohydrates. A thorough understanding of microalgal and cyanobacterial metabolism is necessary to master and optimize biofuel production yields. To this end, systems biology and metabolic modeling have proven to be very efficient tools if supported by an accurate knowledge of the metabolic network. However, unlike heterotrophic microorganisms that utilize the same substrate for energy and as carbon source, microalgae and cyanobacteria require light for energy and inorganic carbon (CO2 or bicarbonate) as carbon source. This double specificity, together with the complex mechanisms of light capture, makes the representation of metabolic network nonstandard. Here, we review the existing metabolic networks of photoautotrophic microalgae and cyanobacteria. We highlight how these networks have been useful for gaining insight on photoautotrophic metabolism.

Modelling of anaerobic digestion of microalgae biomass: Effect of overloading perturbation.

Anaerobic digestion (AD) of microalgae is an intriguing approach for bioenergy production. The scaling-up of AD presents a significant challenge due to the systematic efficiency losses related to process instabilities. To gain a comprehensive understanding of AD behavior, this study assessed a modified version of the anaerobic digestion model No1 (ADM1) + Contois kinetics to represent microalgae AD impacted by overloading. To this end, two new inhibition functions were implemented: inhibition by acetate for acidogenesis/acetogenesis and total volatile fatty acids for hydrolysis. This proposed ADM1 modification (including Contois kinetics) simulated AD behavior during the stable, disturbed and recovery periods, showing that the inhibition functions described in the original ADM1 cannot explain the AD performance under one of the most common perturbations at industrial scale (overloading). The findings underscore the importance of refining the inhibitions present in original ADM1 to better capture and predict the complexities of microalgae AD against overloading.

Retention time and organic loading rate as anaerobic co-digestion key-factors for better digestate valorization practices: C and N dynamics in soils.

The growing use of anaerobic co-digestion (AcoD) in processing organic waste has led to a significant digestate production. To effectively recycle digestate back into soils, it is crucial to understand how operational variables in the AcoD process influence the conversion of organic matter (OM). To address this, a combination of biochemical fractionation and various soil incubation tests were employed to assess the stability of OM in digestates generated from anaerobic continuous reactors fed with a food waste-hay mixture and operating at different hydraulic retention times (HRT) and organic loading rates (OLR). This study revealed that digester performance and operating parameters impacted carbon dynamics in soils. A decrease in the carbon mineralization in soils when increasing the HRT was reported (48 ± 4 % for 70 days compared to 59 ± 1 % for 42 days). Specific HRT and OLR values were found to be linked to carbon accessibility and complexity, confirming that longer HRT lead to higher OM removal and increased complexity in soluble OM, despite minor discrepancies in relative carbon distribution. Furthermore, comparable rates of nitrogen mineralization in soils were observed for all digestates, consistent with the accessibility of nitrogen from the particulate OM. Nevertheless, AcoD converted substrates with the potential to immobilize nitrogen in soils into fast-acting fertilizers. In summary, this study underscores the importance of controlling the AcoD performances to evaluate the suitability of digestates for sustainable agricultural practices.

Aqueous phase recycling: impact on microalgal lipid accumulation and biomass quality.

The potential success of microalgal biofuels greatly depends on the sustainability of the chosen pathway to produce them. Hydrothermal liquefaction (HTL) is a promising route to convert wet algal biomass into biocrude. Recycling the resulting HTL aqueous phase (AP) aims not only to recover nutrients from this effluent but also to use it as a substrate to close the photosynthetic loop and produce algal biomass again and process this biomass again into new biocrude. With that purpose, the response to AP recycling of five Chlorellaceae strains was monitored over five cultivation cycles. After four successive cycles of dynamic growth under nutrient-replete conditions, the microalgae were cultivated for a prolonged fifth cycle of 18 days in order to assess the impact of the AP on lipid and biomass accumulation under nutrient-limited conditions. Using AP as a substrate reduced the demand for external sources of N, S, and P while producing a significant amount of biomass (2.95-4.27 g/L) among the strains, with a lipid content ranging from 16 to 36%. However, the presence of the AP resulted in biomass with suboptimal properties, as it slowed down the accumulation of lipids and thus reduced the overall energy content of the biomass in all strains. Although Chlorella vulgaris NIES 227 did not have the best growth on AP, it did maintain the best lipid productivity of all the tested strains. Understanding the impact of AP on microalgal cultivation is essential for further optimizing biofuel production via the HTL process.

Two-stage alkaline-enzymatic pretreatments to enhance biohydrogen production from sunflower stalks.

Because of their rich composition in carbohydrates, lignocellulosic residues represent an interesting source of biomass to produce biohydrogen by dark fermentation. Nevertheless, pretreatments should be applied to enhance the solubilization of holocelluloses and increase their further conversion into biohydrogen. The aim of this study was to investigate the effect of thermo-alkaline pretreatment alone and combined with enzymatic hydrolysis to enhance biohydrogen production from sunflower stalks. A low increase of hydrogen potentials from 2.3 ± 0.9 to 4.4 ± 2.6 and 20.6 ± 5.6 mL of H2 g(-1) of volatile solids (VS) was observed with raw sunflower stalks and after thermo-alkaline pretreatment at 55 °C, 24 h, and 4% NaOH and 170 °C, 1 h, and 4% NaOH, respectively. Enzymatic pretreatment alone showed an enhancement of the biohydrogen yields to 30.4 mL of H2 g(-1) of initial VS, whereas it led to 49 and 59.5 mL of H2 g(-1) of initial VS when combined with alkaline pretreatment at 55 and 170 °C, respectively. Interestingly, a diauxic effect was observed with sequential consumption of sugars by the mixed cultures during dark fermentation. Glucose was first consumed, and once glucose was completely exhausted, xylose was used by the microorganisms, mainly related to Clostridium species.

Application of optimized alkaline pretreatment for enhancing the anaerobic digestion of different sunflower stalks varieties.

The use of lignocellulosic residues such as sunflower stalks (SS) for the production of bioenergy such as methane is a promising alternative to fossil fuels. However, their recalcitrant structure justifies the use of pretreatment to enhance the accessibility of holocelluloses and their further conversion into methane. First, different conditions of alkaline pretreatment (i.e. duration and NaOH concentration (g/100 g TS) at a fixed temperature of 55 degrees C) were tested to enhance the methane potential of the stalks of the Serin sunflower (193 mL of methane per gram of volatile solids (VS)). The greatest improvement to the methane potential (262 mL CH4 g(-1) VS) was observed at 55 degrees C, 24 h, 4 g NaOH/100 g TS. Fourier Transform Infrared spectra highlighted an accumulation of lignin in the digestate and the degradation of holocelluloses during the anaerobic process, both for pretreated and untreated SS. In a second stage, this optimum condition for alkaline pretreatment (55 degrees C, 24 h, 4 g NaOH/100 g TS) was applied to the stalks of three other varieties of sunflower. Alkaline pretreatment was effective in the delignification of the stalks of the different sunflower varieties, with lignin reduction varying from 23.3% to 36.3% VS. This reduction of lignin was concomitant with the enhancement of methane potential as compared to that of raw SS, with an increase ranging from 29% to 44% for the different SS.

Dark fermentation and microalgae cultivation coupled systems: Outlook and challenges.

The implementation of a sustainable bio-based economy is considered a top priority today. There is no doubt about the necessity to produce renewable bioenergy and bio-sourced chemicals to replace fossil-derived compounds. Under this scenario, strong efforts have been devoted to efficiently use organic waste as feedstock for biohydrogen production via dark fermentation. However, the technoeconomic viability of this process needs to be enhanced by the valorization of the residual streams generated. The use of dark fermentation effluents as low-cost carbon source for microalgae cultivation arises as an innovative approach for bioproducts generation (e.g., biodiesel, bioactive compounds, pigments) that maximizes the carbon recovery. In a biorefinery context, after value-added product extraction, the spent microalgae biomass can be further valorised as feedstock for biohydrogen production. This integrated process would play a key role in the transition towards a circular economy. This review covers recent advances in microalgal cultivation on dark fermentation effluents (DFE). BioH2 via dark fermentation processes and the involved metabolic pathways are detailed with a special focus on the main aspects affecting the effluent composition. Interesting traits of microalgae and current approaches to solve the challenges associated to the integration of dark fermentation and microalgae cultivation are also discussed.