Suivi et contrôle de la digestion anaérobie à partir de la SPIR et de la production de biogaz : évaluation des méthodes chimiométriques adaptées

In France, anaerobic digestion is based on co-digestion of various organic co-substrates. This induces a significant variability (quantitative and qualitative) of the substrates, thus requiring equipment and monitoring that take such specificities into account. In this context, the development of new sensors for the online monitoring of anaerobic digestion appears as a major contributing factor to the enhancement and development of the process. Near-infraRed spectroscopy (NIRS) has been identified as an interesting method for the online monitoring of the process. Therefore, the main objectives of this thesis are (1) to develop and evaluate optical sensors based on NIRS and (2) to develop and evaluate different chemometric methods suited to the monitoring of the anaerobic digestion process using data produced by the optical sensors and all other available sources of data. To this end, two approaches were tested in this work. A prediction approach in which chemometric methods such as PLS, SO-PLS and SO-CovSel were tested, mainly with infrared spectra acquired from codigestion experiments. This served to predict specific parameters that are identified as relevant indicators of failures in AD plants (i.e. VFA, LCFA and NH4+). A second approach allowed the monitoring of the global fingerprint of the digester, based on the acquired spectra and biogas production rate (BPR) kinetics. The MSPC methods based on PCA used in this second approach (Static PCA and MWPCA) have shown great potential for the detection of early warnings of instabilities in the monitoring of anaerobic digestion.Le modèle de la méthanisation en France, basé sur la co-digestion de différents co-substrats organiques, nécessite des équipements et un suivi prenant en compte cette spécificité conduisant à une forte variabilité quantitative et qualitative des intrants. La mise au point de nouveaux capteurs pour le suivi en ligne de la méthanisation est donc un élément majeur qui permettra d’accompagner et d’améliorer son développement. Dans ce cadre, la spectroscopie proche infrarouge (SPIR) a été identifiée comme une méthode prometteuse pour le suivi en ligne du procédé. Ainsi, les principaux objectifs de cette thèse sont donc (1) de développer et d’évaluer des capteurs optiques basés sur la SPIR et (2) de développer et d’évaluer les différentes méthodes chimiométriques adaptées au suivi du procédé pour le traitement et l’analyse des données obtenues par les capteurs optiques et plus largement sur l’ensemble des données disponibles. Pour cela, deux approches ont été testées. Une approche de prédiction dans laquelle les méthodes chimiométriques telles que PLS, SO-PLS et SOCovSel ont été testées, principalement à partir des spectres infrarouges issus des expérimentations de codigestion, pour prédire des paramètres spécifiques AGV, AGLC et NH4+ qui sont des indicateurs pertinents de dysfonctionnement dans les installations de digestion anaérobie. Une seconde approche a permis de suivre l’évolution globale du digesteur aussi bien à partir des spectres que des cinétiques de production du biogaz. Les méthodes MSPC basées sur l’ACP (ACP statique et MWPCA) utilisées dans cette seconde approche ont montré de nombreuses potentialités pour la mise en évidence d’alerte précoce de dysfonctionnement dans le suivi de la digestion anaérobie

Monitoring and control of anaerobic digestion from NIRS and biogas production : evaluation of adapted chemometric methods

Le modèle de la méthanisation en France, basé sur la co-digestion de différents co-substrats organiques, nécessite des équipements et un suivi prenant en compte cette spécificité conduisant à une forte variabilité quantitative et qualitative des intrants. La mise au point de nouveaux capteurs pour le suivi en ligne de la méthanisation est donc un élément majeur qui permettra d’accompagner et d’améliorer son développement. Dans ce cadre, la spectroscopie proche infrarouge (SPIR) a été identifiée comme une méthode prometteuse pour le suivi en ligne du procédé. Ainsi, les principaux objectifs de cette thèse sont donc (1) de développer et d’évaluer des capteurs optiques basés sur la SPIR et (2) de développer et d’évaluer les différentes méthodes chimiométriques adaptées au suivi du procédé pour le traitement et l’analyse des données obtenues par les capteurs optiques et plus largement sur l’ensemble des données disponibles. Pour cela, deux approches ont été testées. Une approche de prédiction dans laquelle les méthodes chimiométriques telles que PLS, SO-PLS et SOCovSel ont été testées, principalement à partir des spectres infrarouges issus des expérimentations de codigestion, pour prédire des paramètres spécifiques AGV, AGLC et NH4+ qui sont des indicateurs pertinents de dysfonctionnement dans les installations de digestion anaérobie. Une seconde approche a permis de suivre l’évolution globale du digesteur aussi bien à partir des spectres que des cinétiques de production du biogaz. Les méthodes MSPC basées sur l’ACP (ACP statique et MWPCA) utilisées dans cette seconde approche ont montré de nombreuses potentialités pour la mise en évidence d’alerte précoce de dysfonctionnement dans le suivi de la digestion anaérobie.In France, anaerobic digestion is based on co-digestion of various organic co-substrates. This induces a significant variability (quantitative and qualitative) of the substrates, thus requiring equipment and monitoring that take such specificities into account. In this context, the development of new sensors for the online monitoring of anaerobic digestion appears as a major contributing factor to the enhancement and development of the process. Near-infraRed spectroscopy (NIRS) has been identified as an interesting method for the online monitoring of the process. Therefore, the main objectives of this thesis are (1) to develop and evaluate optical sensors based on NIRS and (2) to develop and evaluate different chemometric methods suited to the monitoring of the anaerobic digestion process using data produced by the optical sensors and all other available sources of data. To this end, two approaches were tested in this work. A prediction approach in which chemometric methods such as PLS, SO-PLS and SO-CovSel were tested, mainly with infrared spectra acquired from codigestion experiments. This served to predict specific parameters that are identified as relevant indicators of failures in AD plants (i.e. VFA, LCFA and NH4+). A second approach allowed the monitoring of the global fingerprint of the digester, based on the acquired spectra and biogas production rate (BPR) kinetics. The MSPC methods based on PCA used in this second approach (Static PCA and MWPCA) have shown great potential for the detection of early warnings of instabilities in the monitoring of anaerobic digestion

Detection of early imbalances in semi-continuous anaerobic co-digestion process based on instantaneous biogas production rate

International audienceThe aim of this study was to investigate the use of biogas production rate kinetics for the monitoring of anaerobic co-digestion. Recent extensive studies of degradation pathways showed that acetoclastic methanogenesis is not always the main pathway. Hydrogenotrophic methanogenesis and syntrophic acetate oxidation can also dominate, mostly for operating conditions with high concentrations of ammonia or volatile fatty acids ' These conditions are also known to cause instability in the digester's operation especially in co-digestion due to substrate variability. Therefore, co-digestion experiments were conducted with several co-substrates using a continuously stirred 35-L tank reactor. Degradation pathways and their potential shifts were identified by monitoring variations in biogas production rate kinetics using a principal component analysis model. The shifts in the degradation pathways were used to monitor the process. These shift points were found to provide early warnings of instabilities in the anaerobic co-digestion process

Fault detection with moving window PCA using NIRS spectra for monitoring the anaerobic digestion process

Principal component analysis (PCA) is a popular method for process monitoring. However, most processes are time-varying, thus older samples are not representative of the current process status. This led to the introduction of adaptive-PCA based monitoring, such as moving window PCA (MWPCA). In this study, near-infrared spectroscopy (NIRS) responses to digester failures were evaluated to develop a spectral data processing tool. Tests were performed with a spectroscopic probe (350-2,500 nm), using a 35 L mesophilic continuously stirred tank reactor. Co-digestion experiments were performed with pig slurry mixed with several co-substrates. Different stresses were induced by abruptly increasing the organic load rate, changing the feedstock or stopping the stirring. Physicochemical parameters as well as NIRS spectra were acquired for lipid, organic and protein overloads experiments. MWPCA was then applied to the collected spectra for a multivariate statistical process control. MWPCA outputs, Hotelling T2 and residuals Q statistics showed that most of the induced dysfunctions can be detected with variations in these statistics according to a defined criterion based on spectroscopic principles and the process. MWPCA appears to be a multivariate statistical method that could help in decision support in industrial biogas plants

Multi-block SO-PLS approach based on infrared spectroscopy for anaerobic digestion process monitoring

International audienceNear infrared spectroscopy combined with multivariate calibration such as partial least squares regression is a promising technique for on-line monitoring of anaerobic digesters. Different substrates are used in digesters, depending on their availability and their methanogen potential, to optimize the process. In Europe, the feedstock for anaerobic digesters is dominated by slurry and food waste which are respectively highly biodegradable and fat-containing substrates. The monitoring of the anaerobic digestion process based on digestates coming from these substrates presents some difficulties. The digestion of highly biodegradable substrates comes with the presence of water, which hinders spectroscopic calibration. And fat-containing substrates could lead to the accumulation of long chain fatty acids which are quite difficult to detect in the infrared region. While all existing studies have explored adapted spectroscopic measurements to improve the process monitoring, this study investigated the use of NIRS combined with multi-block analysis to track important anaerobic digestion stability parameters. Infrared measurements can come from several sources in the process monitoring. In addition, sequential and orthogonalized partial least squares have proven their ability of exploiting the underlying relation between several data blocks. These multi-block methods are powerful chemometric tools which can be applied in the monitoring of anaerobic digestion. Polarization light spectroscopy which is also known to improve the comprehension of scattering media like the digestate was also studied. © 2019 Elsevier B.V

Multi-block data analysis for online monitoring of anaerobic co-digestion process

Anaerobic digestion is a chemical process whose purpose is to maximize biogas production whilst concomitantly treating organic waste mostly through co-digestion due to the variety of substrates. To avoid failures, the process requires the monitoring of several parameters and / or inhibitors. The existing strategies and methods used in the process monitoring still lack sensitivity and robustness, when taken individually. The current study investigated the use of sequential and orthogonalized partial least squares (SO-PLS) regression to relate these parameters to several blocks of data coming for near infrared spectroscopy, chemical routine analysis and kinetics of biogas production. The models produced were able to extract relevant information from each block's data and discard redundancies. Moreover, to meet biogas plant operators' requirements, variable selection was performed on the infrared blocks using a recent method: SO-CovSel. SO-CovSel is a method resulting from coupling SO-PLS and Covariance Selection (CovSel) method. The method has been demonstrated to be suitable for multi-response calibration purposes with infr ared calibration. It has provided good predictions and an interesting interpretation of wavelengths involved in the monitoring of the relevant parameters of stability in anaerobic co-digestion

Fast at-line characterization of solid organic waste: Comparing analytical performance of different compact near infrared spectroscopic systems with different measurement configurations

International audienceFast characterization of solid organic waste using near infrared spectroscopy has been successfully developed in the last decade. However, its adoption in biogas plants for monitoring the feeding substrates remains limited due to the lack of applicability and high costs. Recent evolutions in the technology have given rise to both more compact and more modular low-cost near infrared systems which could allow a larger scale deployment. The current study investigates the relevance of these new systems by evaluating four different Fourier transform near-infrared spectroscopic systems with different compactness (laboratory, portable, micro spectrometer) but also different measurement configurations (polarized light, at distance, in contact). Though the conventional laboratory spectrometer showed the best performance on the various biochemical parameters tested (carbohydrates, lipids, nitrogen, chemical oxygen demand, biochemical methane potential), the compact systems provided very close results. Prediction of the biochemical methane potential was possible using a low-cost micro spectrometer with an independent validation set error of only 91 NmL(CH4).gTS-1 compared to 60 NmL(CH4).gTS-1 for a laboratory spectrometer. The differences in performance were shown to result mainly from poorer spectral sampling; and not from instrument characteristics such as spectral resolution. Regarding the measurement configurations, none of the evaluated systems allowed a significant gain in robustness. In particular, the polarized light system provided better results when using its multi-scattered signal which brings further evidence of the importance of physical light-scattering properties in the success of models built on solid organic waste

On-site substrate characterization in the anaerobic digestion context: A dataset of near infrared spectra acquired with four different optical systems on freeze-dried and ground organic waste

International audienceThe near infrared spectra of thirty-three freeze-dried and ground organic waste samples of various biochemical composition were collected on four different optical systems, including a laboratory spectrometer, a transportable spectrometer with two measurement configurations (an immersed probe, and a polarized light system) and a micro-spectrometer. The provided data contains one file per spectroscopic system including the reflectance or absorbance spectra with the corresponding sample name and wavelengths. A reference data file containing carbohydrates, lipid and nitrogen content, biochemical methane potential (BMP) and chemical oxygen demand (COD) for each sample is also provided. This data enables the comparison of the optical systems for predictive model calibration based for example on Partial Least Squares Regression (PLS-R) [1], but could be used more broadly to test new chemometrics methods. For example, the data could be used to evaluate different transfer functions between spectroscopic systems [2]. This dataset enabled the research work reported by Mallet et al. 2021 [3]