scholarly journals Robust Data-Driven Soft Sensors for Online Monitoring of Volatile Fatty Acids in Anaerobic Digestion Processes

Processes ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 67 ◽  
Author(s):  
Pezhman Kazemi ◽  
Jean-Philippe Steyer ◽  
Christophe Bengoa ◽  
Josep Font ◽  
Jaume Giralt
Keyword(s):  
Fatty Acids ◽  
Anaerobic Digestion ◽  
Real Time ◽  
Volatile Fatty Acids ◽  
Synthetic Data ◽  
Data Driven ◽  
Organic Load ◽  
Support Vector ◽  
Soft Sensors ◽  
Artificial Neural Network Ann

The concentration of volatile fatty acids (VFAs) is one of the most important measurements for evaluating the performance of anaerobic digestion (AD) processes. In real-time applications, VFAs can be measured by dedicated sensors, which are still currently expensive and very sensitive to harsh environmental conditions. Moreover, sensors usually have a delay that is undesirable for real-time monitoring. Due to these problems, data-driven soft sensors are very attractive alternatives. This study proposes different data-driven methods for estimating reliable VFA values. We evaluated random forest (RF), artificial neural network (ANN), extreme learning machine (ELM), support vector machine (SVM) and genetic programming (GP) based on synthetic data obtained from the international water association (IWA) Benchmark Simulation Model No. 2 (BSM2). The organic load to the AD in BSM2 was modified to simulate the behavior of an anaerobic co-digestion process. The prediction and generalization performances of the different models were also compared. This comparison showed that the GP soft sensor is more precise than the other soft sensors. In addition, the model robustness was assessed to determine the performance of each model under different process states. It is also shown that, in addition to their robustness, GP soft sensors are easy to implement and provide useful insights into the process by providing explicit equations.

scholarly journals Rapid Two Stage Anaerobic Digestion of Nejayote through Microaeration and Direct Interspecies Electron Transfer

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1614
Author(s):  
David Valero ◽  
Carlos Rico ◽  
Raul Tapia-Tussell ◽  
Liliana Alzate-Gaviria
Keyword(s):  
Fatty Acids ◽  
Anaerobic Digestion ◽  
Volatile Fatty Acids ◽  
Uasb Reactor ◽  
Organic Load ◽  
Great Abundance ◽  
Conductive Material ◽  
Direct Interspecies Electron Transfer ◽  
Interspecies Electron Transfer ◽  
Granulated Activated Carbon

Corn is one of the main food products in Mexico. The elaboration of corn-derived products generates wastewater with a high organic load (nejayote). Anaerobic digestion is an indicated treatment for wastewater with high organic loads. The results of this study show that the application of microaeration in the hydrolysis-fermentative reactor increased the percentage of volatile fatty acids (VFA) available in the medium by 62%. The addition of a conductive material, such as granulated activated carbon (GAC), promotes DIET (Direct interspecies electrons transfer) in the methanogenic UASB reactor increasing the methane yield by 55%. Likewise, a great diversity of exoelectrogenic bacteria, with the ability to donate electrons DIET mechanisms, were developed in the GAC biofilm, though interestingly, Peptoclostridium and Clostridium (17.3% and 12.75%, respectively) were detected with a great abundance in the GAC biofilm. Peptoclostridium has not been previously reported as a participant in DIET process.

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

2020 ◽  
Vol 81 (8) ◽  
pp. 1740-1748 ◽  
Author(s):  
Pezhman Kazemi ◽  
Jaume Giralt ◽  
Christophe Bengoa ◽  
Jean-Philippe Steyer
Keyword(s):  
Anaerobic Digestion ◽  
Control Charts ◽  
Volatile Fatty Acids ◽  
Principal Component ◽  
Data Driven ◽  
Detection Methods ◽  
Support Vector ◽  
Statistical Control ◽  
Excellent Performance ◽  
Small Magnitude

Abstract 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.

Influence of hydrothermal pretreatment conditions, typology of anaerobic digestion system, and microbial profile in the production of volatile fatty acids from olive mill solid waste

2021 ◽  
Vol 9 (2) ◽  
pp. 105055
Author(s):  
Yasmim Arantes da Fonseca ◽  
Nayara Clarisse Soares Silva ◽  
Adonai Bruneli de Camargos ◽  
Silvana de Queiroz Silva ◽  
Hector Javier Luna Wandurraga ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Anaerobic Digestion ◽  
Solid Waste ◽  
Volatile Fatty Acids ◽  
Hydrothermal Pretreatment ◽  
Microbial Profile ◽  
Olive Mill Solid Waste ◽  
Pretreatment Conditions ◽  
Olive Mill

scholarly journals Structure of Microbial Communities When Complementary Effluents Are Anaerobically Digested

2021 ◽  
Vol 11 (3) ◽  
pp. 1293
Author(s):  
Ana Eusébio ◽  
André Neves ◽  
Isabel Paula Marques
Keyword(s):  
Anaerobic Digestion ◽  
Microbial Communities ◽  
Volatile Fatty Acids ◽  
Olive Mill Wastewater ◽  
Organic Load ◽  
Rrna Gene ◽  
Bacterial Populations ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing ◽  
Olive Mill

Olive oil and pig productions are important industries in Portugal that generate large volumes of wastewater with high organic load and toxicity, raising environmental concerns. The principal objective of this study is to energetically valorize these organic effluents—piggery effluent and olive mill wastewater—through the anaerobic digestion to the biogas/methane production, by means of the effluent complementarity concept. Several mixtures of piggery effluent were tested, with an increasing percentage of olive mill wastewater. The best performance was obtained for samples of piggery effluent alone and in admixture with 30% of OMW, which provided the same volume of biogas (0.8 L, 70% CH4), 63/75% COD removal, and 434/489 L CH4/kg SVin, respectively. The validation of the process was assessed by molecular evaluation through Next Generation Sequencing (NGS) of the 16S rRNA gene. The structure of the microbial communities for both samples, throughout the anaerobic process, was characterized by the predominance of bacterial populations belonging to the phylum Firmicutes, mainly Clostridiales, with Bacteroidetes being the subdominant populations. Archaea populations belonging to the genus Methanosarcina became predominant throughout anaerobic digestion, confirming the formation of methane mainly from acetate, in line with the greatest removal of volatile fatty acids (VFAs) in these samples.

Increasing 2 -Bio- (H2 and CH4) production from food waste by combining two-stage anaerobic digestion and electrodialysis for continuous volatile fatty acids removal

2021 ◽  
Vol 129 ◽  
pp. 20-25
Author(s):  
Gamal K. Hassan ◽  
Rhys Jon Jones ◽  
Jaime Massanet-Nicolau ◽  
Richard Dinsdale ◽  
M.M. Abo-Aly ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Anaerobic Digestion ◽  
Food Waste ◽  
Volatile Fatty Acids ◽  
Two Stage ◽  
Ch4 Production

scholarly journals Control and estimation of anaerobic digestion processes using hydrogen and volatile fatty acids measurements

2018 ◽  
Vol 78 (10) ◽  
pp. 2027-2035 ◽  
Author(s):  
M. Sbarciog ◽  
G. Giovannini ◽  
R. Chamy ◽  
A. Vande Wouwer
Keyword(s):  
Fatty Acids ◽  
Anaerobic Digestion ◽  
Hydrogen Concentration ◽  
Volatile Fatty Acids ◽  
Control Structure ◽  
Tight Control ◽  
Detailed Model ◽  
Control Scheme ◽  
Estimation And Control ◽  
And Control

Abstract The anaerobic digestion (AD) technology is widely used in the treatment of waste and wastewater. To ensure the treatment efficiency and to increase the production of biogas, which can be reused as a renewable energy source, a good understanding of the process and tight control are needed. This paper presents an estimation and control scheme, which can be successfully used in the operation of the AD process. The process is simulated by the ADM1 model, the most complex and detailed model developed so far to characterize AD. The controller and the observer, which provides estimates of the unmeasurable variables needed in the computation of the control law, are designed based on a simplified model developed in a previous work. Since it has been shown that hydrogen concentration is an accurate and fast indicator of process stability, it was chosen as controlled variable. Aside from the hydrogen concentration, the only measurement employed by the proposed control structure is the volatile fatty acids concentration. Simulation results prove the effectiveness of the proposed control structure.

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