(Downloads - 0)
For more info about our services contact : help@bestpfe.com
Table of contents
Chapter 1. Anaerobic Digestion in Europe and in France.
1.1 Chapter Guidelines
1.2 Technical and Graphical Abstracts
1.3 World Energy Challenge
1.4 Biogas over European Union
1.5 France, a Potential Vector of Growth for the European Anaerobic Digestion Sector
1.6 Contents of the Thesis
Chapter 2. Materials and Methods
2.1 Materials and Methods Guidelines
2.2 Titrimetric Methods to Determine Ammonia Nitrogen, Volatile Fatty Acids and Inorganic Carbon Concentrations
2.2.1 Experimental Titration Device
2.2.2 Titration Protocol
2.2.3 Analytical Methods for Reference Data
2.2.4 Titration Model
2.2.5 Signal Processing Coupling pH and Electrical Conductivity Measurements
2.3 Analytical Methods for Solid Waste Characterization
2.3.1 Biochemical Composition of Solid Waste
2.3.2 Bio-accessibility Assessment by Chemical Sequential Extraction
2.3.3 Anaerobic digestion experiments
2.4 Spectroscopic Analyses
2.4.1 Near Infrared
2.4.2 3D Fluorescence
2.5 Solid Waste Analyzed
2.5.1 Samples Analyzed for Fast Spectroscopic Characterization
2.5.2 Samples Analyzed for Correlation Analyses
2.6 Correlation Analysis and Regression Models
2.6.1 Pearson’s Correlation and Cosine
2.6.2 Principal Component Analysis
2.6.3 Partial Least Square Regression Model and Performance
2.7 Dynamic Anaerobic Digestion Models
2.7.1 Dynamic Models: Modified ADM1
2.7.2 ADM1 Modelling Approach Using NIRs
Chapter 3. Combining pH and Electrical Conductivity Measurements to Improve Titrimetric Methods to Determine Ammonia Nitrogen, Volatile Fatty Acids and Inorganic Carbon Concentrations
3.1 Chapter Guidelines
3.2 Technical and Graphical Abstracts
3.3 Introduction of the Chapter
3.3.1 Key Parameters to Estimate the Biological State of Anaerobic Digestion Processes
3.3.2 Available Sensors for VFA, IC and TAN Concentrations Measurement
3.4 Materials and Methods Related to this Chapter
3.5 Results of the Existing Methods
3.5.1 Estimation of VFA and IC
3.5.2 Estimation of TAN Using Non-Linear Resolution
3.6 Accurate Estimation of VFA, IC and TAN Concentrations by Coupling pH and Electrical Conductivity Measurement.
3.6.1 Building of a Decision Tree
3.6.2 Example of a Titration Using SNAC
3.6.3 Discussion of the Advantages between the Existing Methods and SNAC
3.7 SNAC Prototype
3.8 Conclusion
Chapter 4. Relations between Biochemical Composition and Anaerobic Digestion Performances of Solid Waste
4.1 Chapter Guidelines
4.2 Technical and Graphical Abstracts
4.3 Introduction of the Chapter
4.3.1 Analytical Methods for Biochemical Characterization of Substrates
4.3.2 Biodegradability and Methane Production Rate Estimation
4.4 Materials and Methods Related to this Chapter
4.5 Validation of Biochemical Analyses on Solid Waste
4.6 Dataset Exploration Using a Principal Component Analysis
4.7 Variables Correlation Exploration Using a Principal Component Analysis
4.8 Variables Correlation Analysis using Pearson Correlation Coefficients
4.9 Discussion about Variables Correlation Analysis
4.10 Predictability of the Kinetics of Methane Production from Biochemical Composition
4.11 Conclusion on the Existing Relation between the Biochemical Composition and the Methane Production Performances
Chapter 5. Characterization of the Solid Waste Biochemical Composition and Anaerobic Digestion Performances Using Spectroscopic Analyses
5.1 Chapter Guidelines
5.2 Technical and Graphical Abstracts
5.3 Introduction of the Chapter
5.3.1 BMP Estimation on Early Biogas Production
5.3.2 Spectroscopic Analyses
5.4 Materials and Methods Related to this Chapter
5.5 Comparison of 3D Fluorescence and Near Infrared Spectroscopy for Biodegradability Prediction
5.6 Fast Characterization of Solid Waste Biochemical Composition with Near Infrared Spectroscopy
5.6.1 Combinations of the Calibration Model Using PLS Regression
5.6.2 Model Validation on an Independent Dataset
5.6.3 Discussion Regarding the Selected Model
5.7 Prediction of the Methane Production Rate in Batch Conditions Using NIR Spectroscopy
5.7.1 Prediction of the Methane Yield
5.7.2 Prediction of the Methane Production Time
5.7.3 Methane Production Rate Prediction
5.7.4 Simple Indicator of Methane Production Performances
5.8 Confidence Interval Determination Using Spectrum Distance from the Calibration Set
5.9 Conclusion on NIRs Characterization
Chapter 6. Parallel Study of PLS b Coefficients and Near Infrared Wavelengths to Assess Molecules Contribution to Chemical Oxygen Demand, Methane Production Yield and Kinetics.
6.1 Chapter Guidelines
6.2 Technical and Graphical Abstracts
6.3 Introduction of the Chapter
6.4 Materials and Methods Related to this Chapter
6.5 Homogenization of the Chemometric Treatment
6.6 b Coefficients Analysis and Molecules Contribution to the Predicted Parameters
6.7 Relations between the b Coefficients of the Models
6.8 Conclusion
Chapter 7. Challenging the Simultaneous Hydrolysis Concept andFast Implementation of ADM1 for the Anaerobic Co-digestion Performances Simulation
7.1 Chapter Guidelines
7.2 Technical and Graphical Abstracts
7.3 Introduction of the Chapter
7.4 Materials and Methods Related to this Chapter
7.5 Modelling Hydrolysis: Simultaneous versus Sequential Biodegradation of theHydrolysable Fractions
7.5.1 Definition of Simultaneous and Sequential Concepts
7.5.2 Results Obtained on Several Substrates
7.5.3 Fractions Biodegradability: Case Studies on Apple and Wheat Straw
7.5.4 Case of Continuous Reactor
7.5.5 Conclusion on Hydrolysis Modelling
7.6 ADM1 Implementation Assisted by Near Infrared Spectroscopy for the Anaerobic Digestion Performances Simulation
7.6.1 ADM1 Calibration from NIR Prediction
7.6.2 Discussion on the MPR Prediction Using NIR
7.7 Example of Industrial Application
7.8 Conclusion
Chapter 8. General Conclusion and Outlooks
8.1 Conclusion
8.2 Outlooks
8.3 Projected development
Chapter 9. References
