scholarly journals Biogas productivity of anaerobic digestion process is governed by a core bacterial microbiota

2020 ◽  
Vol 380 ◽  
pp. 122425 ◽  
Author(s):  
Yu Tao ◽  
Mustafa Evren Ersahin ◽  
Dara S.M. Ghasimi ◽  
Hale Ozgun ◽  
Haoyu Wang ◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Anaerobic Digestion Process ◽  
Digestion Process ◽  
Bacterial Microbiota ◽  
Biogas Productivity

Determinant impact of waste collection and composition on anaerobic digestion performance: industrial results

2000 ◽  
Vol 41 (3) ◽  
pp. 291-297 ◽  
Author(s):  
C. Saint-Joly ◽  
S. Desbois ◽  
J-P. Lotti
Keyword(s):  
Anaerobic Digestion ◽  
Waste Collection ◽  
Biogas Yield ◽  
Anaerobic Digestion Process ◽  
Digestion Process ◽  
Waste Composition ◽  
Site Characteristics ◽  
Volatile Solids ◽  
Biogas Productivity

The performance of the anaerobic digestion process depends deeply on the quality of the waste to be treated. This has been already demonstrated at the lab-scale. The objective of this study is to confirm this result at the industrial scale, with very long representative period and with the same process, the Valorga process. According to the waste quality and the collection type and even with the same conditions of fermentation, the biogas yield can vary by a factor of 1.5 when it is expressed (under normal conditions of pressure and temperature) in m3 biogas/t fresh waste, and by a factor of 2 when it is expressed in m3 CH4/t volatile solids. So, the biogas performance does not characterise a process since it is deeply governed by waste composition. This biogas productivity becomes a pertinent parameter only with consistent and relevant hypothesis and/or analytical results on the waste composition which depends on the collection procedure, the site characteristics and the season.

A Mathematical Model for the Anaerobic Digestion Process Applied to a Mixture of Night Soil and Septic Tank Sludge

1986 ◽  
Vol 18 (7-8) ◽  
pp. 239-248 ◽  
Author(s):  
Sung Ryong Ha ◽  
Dwang Ho Lee ◽  
Sang Eun Lee
Keyword(s):  
Mathematical Model ◽  
Anaerobic Digestion ◽  
Biomass Concentration ◽  
Gas Production ◽  
Septic Tank ◽  
Volatile Acid ◽  
Hydraulic Residence Time ◽  
Anaerobic Digestion Process ◽  
Digestion Process ◽  
Proposed Model

Laboratory scale experiments were conducted to develop a mathematical model for the anaerobic digestion of a mixture of night soil and septic tank sludge. The optimum mixing ratio by volume between night soil and septic tank sludge was found to be 7:3. Due to the high solids content in the influent waste, mixed-liquor volatile suspended solids (MLVSS) was not considered to be a proper parameter for biomass concentration, therefore, the active biomass concentration was estimated based on deoxyribonucleic acid (DNA) concentration in the reactor. The weight ratio between acidogenic bacteria and methanogenic bacteria in the mixed culture of a well-operated anaerobic digester was approximately 3:2. The proposed model indicates that the amount of volatile acid produced and the gas production rate can be expressed as a function of hydraulic residence time (HRT). The kinetic constants of the two phases of the anaerobic digestion process were determined, and a computer was used to simulate results using the proposed model for the various operating parameters, such as BOD5 and volatile acid concentrations in effluent, biomass concentrations and gas production rates. These were consistent with the experimental data.

scholarly journals Linearization in the Large of the Anaerobic Digestion Process Using a Reduced-Order Koopman Operator

2020 ◽  
Vol 53 (2) ◽  
pp. 16840-16845
Author(s):  
Camilo Garcia-Tenorio ◽  
Mihaela Sbarciog ◽  
Eduardo Mojica-Nava ◽  
Alain Vande Wouwer
Keyword(s):  
Anaerobic Digestion ◽  
Koopman Operator ◽  
Reduced Order ◽  
Anaerobic Digestion Process ◽  
Digestion Process

Enhancing anaerobic digestion process with addition of conductive materials

Chemosphere ◽  
2021 ◽  
pp. 130449
Author(s):  
Yiwei Liu ◽  
Xiang Li ◽  
Shaohua Wu ◽  
Zhao Tan ◽  
Chunping Yang
Keyword(s):  
Anaerobic Digestion ◽  
Anaerobic Digestion Process ◽  
Conductive Materials ◽  
Digestion Process

Techniques for Quantifying Methane Production Potential in the Anaerobic Digestion Process

2021 ◽  
Author(s):  
Miguel Casallas-Ojeda ◽  
Sully Meneses-Bejarano ◽  
Ronald Urueña-Argote ◽  
Luis Fernando Marmolejo-Rebellón ◽  
Patricia Torres-Lozada
Keyword(s):  
Anaerobic Digestion ◽  
Methane Production ◽  
Production Potential ◽  
Anaerobic Digestion Process ◽  
Digestion Process ◽  
Methane Production Potential

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

2005 ◽  
Vol 52 (1-2) ◽  
pp. 419-426 ◽  
Author(s):  
C.A. Aceves-Lara ◽  
E. Aguilar-Garnica ◽  
V. Alcaraz-González ◽  
O. González-Reynoso ◽  
J.P. Steyer ◽  
...  
Keyword(s):  
Experimental Data ◽  
Anaerobic Digestion ◽  
Quadratic Programming ◽  
Kinetic Parameters ◽  
Parameters Estimation ◽  
Fixed Bed Reactor ◽  
Accurate Estimation ◽  
Successive Quadratic Programming ◽  
Anaerobic Digestion Process ◽  
Digestion Process

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.

Sign in / Sign up

Export Citation Format

Share Document