The use of biogas as fuel for transportation, electricity generation, heating and in cooking stoves, justify its production as alternative fuel to natural gas. Waste, posing serious danger to the environment, especially chicken manures (CM) containing disease-causing microorganisms, if utilized via anaerobic digestion to generate biogas will go a long way in mitigating its effect. This work, hence, desires to turn the detrimental health challenges that these microbes could cause humans and animals to generate useful by-products.
Therefore, this work aims at studying the kinetics of biogas production using CM. The objectives entail utilizing a bench-scale digester to produce biogas; studying the growth kinetics of microorganisms acting on the feedstock; profile the gas generated and using POLYMATH regression tool to study comparatively, the modified Gompertz, Cone, Transfert and Logarithmic biogas yield kinetic models. The method followed involves feeding the digester with 7 kg of CM after proximate analysis, determining the biomass concentration and daily gas production over a 40 days retention period using the biogas and cell growth data in models to describe the conditions inside the digesting system and the biogas potential of the CM substrate and lastly, analyzing the raw gas produced to know its constituent gases.
Table of Contents
1. Introduction
1.1 Background of the Study
1.2 Aim and Objectives of the Study
1.3 Statement of the Problem
1.4 Significance of the Study
1.5 Scope of the Study
2. Literature Review
2.1 Chicken Manure (CM) Utilization
2.1.1 Environmental Impacts of Chicken Manure
2.1.2 Availability of Chicken Manure Feedstock
2.2 Biodigester for Biogas Production
2.3 Anaerobic Digestion of Chicken Manure
2.3.1 Stages of Degradation and Factors Affecting Gas Production
2.3.2 Kinetic Study
2.4 Microbial Growth Kinetics
2.4.1 Determination of Cell Numbers by Serial Dilution
2.4.2 Microbial Growth Curve
2.4.3 Substrate Utilization Model
2.5 Existing Growth Kinetic Models
2.5.1 Monod Equation
2.5.2 Substrate Inhibition Model
2.5.3 Kinetic Model Without Inhibition
2.6 Kinetics of Biogas Production
2.6.1 Modified Gompertz Model
2.6.2 Cone, Transfert and Logistic Model
2.6.3 Less Common Biogas Kinetic Model
2.6.4 Cumulative Biogas Measurement
2.7 POLYMATH and Regression Parameters
3. Methodology
3.1 Materials and Equipment Used
3.2 Bioreactor Setup
3.3 Feedstock Preparation and Characterization
3.4 Digester Start-Up
3.4.1 Process Start-Up
3.4.2 Temperature and pH Measurement
3.5. Microbial Count
3.5.1. Determination of Microbial Concentration
3.5.2 Serial Dilution
3.5.3 Preparation of Culture Media
3.5.4 Pour Plate Technique
3.5.5 Colonic Counting
3.6 Cumulative Biogas Measurement
3.7 Growth Kinetics
3.7.1 Growth Curve Plot
3.7.2 Finding Generation Time and Decay Constant
3.7.3 Substrate Concentration Determination
3.7.4 Material Balance
3.7.5 Generating Appropriate Data for Monod Plot
3.8 Kinetic Parameter Estimation
4. Result and Discussion
4.1 Manure Properties on Anaerobic Digestion
4.1.1 Presence of Metallic Nutrient
4.1.2 Influence of Proximate Analysis Data of Chicken Manure
4.2 Effect of Biodigester Condition
4.2.1 pH and Temperature Effect
4.2.2 Biogas Yield
4.3 Analysis of Growth Kinetics
4.3.1 Microbial Growth Phases
4.3.2 Effect of Substrate Concentration on Specific Growth Rate
4.4 POLYMATH Kinetic Data Fitting
4.4.1 Growth Model and Comparison of Regression Parameter
4.4.2 Biogas Kinetics Model Fitting
5. Conclusion and Recommendations
5.1 Conclusion
5.2 Recommendations
Research Objectives and Focus
This study focuses on analyzing the kinetics of biogas production using chicken manure as a feedstock, with the primary objective being the optimization of biogas yield through a comprehensive kinetic analysis of microbial growth and substrate degradation performance.
- The production of biogas utilizing a bench-scale anaerobic digester.
- The investigation of microbial growth kinetics during feedstock degradation.
- The comparative kinetic evaluation of various mathematical models, including the modified Gompertz, Cone, Transfert, and Logarithmic models.
- The application of POLYMATH regression software for processing empirical data and determining critical kinetic parameters.
- The analysis and profiling of produced gas constituents to evaluate fuel potential.
Excerpt from the Book
2.4 Microbial Growth Kinetics
In CM, there are mostly three types of micro-organisms, namely, Salmonella spp., Escherichia coli (E. coli), and Cryptosporidium. During anaerobic batch fermentation of CM, these microorganisms grow under a variety of physical, chemical, and nutritional conditions. They do so, by extracting nutrients from the medium (CM slurry) and converting them into biological compounds. This changes is accomplished through a cell’s use of a number of dissimilar enzymes in a strings of reactions to produce metabolic products, which either remain in the cell (intracellular), providing the cell with energy or be secreted from the cells (extracellular) as bioproducts (Liu, 2017). Growth therefore, is believed to mean, both replication of cells and change in cell size. The growth and multiplication of microorganism in controlled environments, thus arouse the interest of microbiologists, biochemical engineers and, cell-growth experts, as they instigate bioprocess simulation and control scheme design (González-figueredo et al., 2018). Generally, according to UlukardeŞler and Atalay (2018), kinetics of microorganisms growth can be investigated in two ways. One, is to measure the substrate concentrations during experiment, a procedure that is tiring and consumes a lot of time and a second, faster and easier methods that entails measuring the gas production rates in the course of the synthesis. Clearly, microbial growth and substrate consumption rates are two parameters anaerobic digestion kinetics models focuses on (Tena et al., 2021).
For bioreactors operating in batch mode, kinetics of biogas production is proportional to specific growth rate of methanogenic microorganism inside the digester (Noori and Ismail, 2019; Venkateshkumar et al., 2020). Two types of microbial growth models can be distinguished (González-figueredo et al., 2018): Structured Kinetic Models (SKMs) describing changes in cell population and classified into chemically structured models, morphologically structured models and, genetically structured models and, Unstructured Kinetic Models (UKMs) representing the metabolic behavior of the biomass cell production. The significance of these growth models are to estimate the growth of microorganisms under environmental conditions (Hawkins et al., 2019), predict the behavior of biochemical reactions (González-figueredo et al., 2018), assist engineers to design and control biological processes (Muloiwa et al., 2020) and, to determine the performance parameters influencing the product yield (Gallipoli et al., 2020).
Summary of Chapters
Chapter One (Introduction): Covers the background of kinetic modeling in anaerobic digestion, the significance of chicken manure as a feedstock, and the specific objectives of the research.
Chapter Two (Literature Review): provides a comprehensive overview of chicken manure properties, biodigester technology, microbial growth kinetics, and existing kinetic models used to analyze biogas production.
Chapter Three (Methodology): details the experimental setup, feedstock characterization, microbial counting techniques, and the mathematical framework for cumulative biogas measurement and kinetic data generation.
Chapter Four (Result and Discussion): presents the experimental results regarding manure properties, biogas yield, microbial growth analysis, and the implementation of POLYMATH for model regression and goodness-of-fit testing.
Chapter Five (Conclusion and Recommendations): summarizes the findings of the study and offers suggestions for future research, including the use of alternative feedstocks and advanced control systems.
Keywords
Anaerobic Digestion, Biogas Production, Chicken Manure, Kinetic Modeling, Microbial Growth, Monod Model, Modified Gompertz Model, POLYMATH, Biomass Concentration, Substrate Utilization, Batch System, Cumulative Biogas Yield, Methanogen, Bioreactor, Regression Analysis
Frequently Asked Questions
What is the core focus of this research?
The research is dedicated to studying the kinetics of biogas production using chicken manure as the primary feedstock to optimize yield through mathematical modeling.
Which key topics does the work address?
The work covers theoretical frameworks for microbial growth, experimental anaerobic digestion processes, evaluation of diverse kinetic models, and statistical data fitting for biogas optimization.
What is the primary goal of the study?
The primary goal is to study the kinetics of biogas production using a bench-scale digester and to build a reliable model to predict and optimize biogas output.
Which scientific methods are employed?
The study employs experimental anaerobic batch fermentation, proximate analysis of feedstock, serial dilution techniques for microbial counting, and regression analysis using the POLYMATH software.
What is analyzed in the main body of the work?
The main body analyzes the physical and chemical properties of chicken manure, discusses the microbial growth phases within the digester, and evaluates various mathematical models for substrate utilization and gas production.
Which keywords characterize the work?
Key terms include Anaerobic Digestion, Chicken Manure, Kinetic Modeling, Monod Model, Gompertz Model, and Biogas Potential.
How does the study address nutrient insufficiency in cattle manure?
The study identifies the need for nutrient balance and explores the potential of chicken manure as a rich, sole-feedstock source, overcoming common bottlenecks through rigorous kinetic analysis and temperature-pH control.
Why is the Modified Gompertz model mentioned prominently?
It is highlighted as one of the most effective and popular models for simulating batch organic waste decomposition because of its robustness in linking cumulative biogas production to hydraulic retention time.
Which role does the POLYMATH software play?
POLYMATH is used as the computational backbone to solve complex differential equations and non-linear regression problems for estimating unknown kinetic parameters of the biogas models.
What are the implications for industrial scale-up?
The study provides quantitative kinetic estimates and statistical validation of models that facilitate the prediction of digester behavior, which is essential for transitioning from laboratory-scale experiments to efficient industrial-scale applications.
- Citar trabajo
- Abdulhalim Musa Abubakar (Autor), 2023, Kinetic Study of Biogas Production from Chicken Manure, Múnich, GRIN Verlag, https://www.grin.com/document/1349009
