PRODUCTION OF BIOETHANOL BY USING PRETREATED COCONUT HUSK AS CARBON SOURCE

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  • Department: Chemical Engineering
  • Project ID: CNG0136
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  • Pages: 120 Pages
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PRODUCTION OF BIOETHANOL BY USING PRETREATED COCONUT HUSK AS CARBON SOURCE
ABSTRACT

In the current study, coconut husk, a lignocellulosic biomass, was employed as the feedstock for production of bioethanol. The powderised coconut husks were subjected to thermal pretreatment, chemical pretreatment and microwave-assisted-alkaline (MAA) pretreatment prior to enzymatic and hydrolysis process. The composition profile of coconut husks was significantly altered upon the MAA pretreatment as compared to the untreated sample, with the cellulose content increasing from 18-21% to 38-39% while lignin content decreased from 46-53% to 31-33%. Enzymatic hydrolysis of MAA-pretreated coconut husk also achieved the highest yield of fermentable sugars (measured as glucose) with 0.279 g sugar/g coconut husk. Scanning electron microscopy (SEM) imaging also proved the obvious and significant disruption of coconut husks’ structure. The results demonstrated that the combination of microwave radiation with alkaline solution was effective in altering the physical structures of coconut husks. Hence, MAA-
 pretreated coconut husk was chosen as the substrate for subsequent hydrolysis and fermentation process.For the optimization of simultaneous saccharification and bioethanol fermentation process, the critical variables that affected bioethanol production were identified by using Plackett-Burman design and tested using the analysis of variance (ANOVA). The factors with p-value less than 0.05 in this test were coconut husk loading (p = 0.0087) and pectinase loading (p = 0.0198). These two significant factors were further optimized using a Central Composite Design (CCD). The maximum response predicted from the model would yield 0.0525 g ethanol per g coconut husk daily under the optimal conditions of 3.06 g MAA-pretreated coconut husks, 0.58 mL cellulase, 0.38 mL pectinase and 1 g yeast extract in 100 mL of medium (pH 6) incubated at 30oC. The experimental result gave bioethanol productivity of approximately 0.0593 g ethanol per g coconut husks daily, which was 13% higher than the estimated value (0.0525 g ethanol per g coconut husk). The results of validation experiments proved the usefulness and effectiveness of CCD as an optimization tool in enhancement of bioethanol production from indigenous renewable resources.
   TABLE OF CONTENTS   
CHAPTER            
1    INTRODUCTION    
    1.1    Energy Sources    
    1.2    Problem Statement    
    1.3    Scope of Study    
    1.4    Research Objectives    
2    LITERATURE REVIEW    
    2.1    Energy Crisis    
    2.2    Bioethanol as Alternative of Fossil Fuel    
        2.2.1    Feedstock for Bioethanol Production    
    2.3    Overview of Coconut Palm    
        2.3.1    Coconut Husk    
    2.4    Compositions of Lignocellulosic Materials    
        2.4.1    Cellulose    
        2.4.2    Hemicellulose    
        2.4.3    Lignin    
    2.5    Lignocelluloses Bioconversion Technology    
        2.5.1    Pretreatment Process    
        2.5.2    Saccharification  Process    
        2.5.3    Fermentation Process    
    2.6    Batch Production of Bioethanol    
    2.7    Factors Affecting Bioethanol Fermentation by Yeast    
        2.7.1    Temperature    
        2.7.2    pH    
        2.7.3    Carbon Source    
        2.7.4    Nitrogen Source    
    2.8    Concluding Remarks    
 3    GENERAL MATERIALS AND METHODS    
    3.1    Chemical Reagents    
    3.2    Microorganism and Maintenance    
    3.3    Inoculums Preparation    
    3.4    Analytical Procedures    
        3.4.1    Determination of Reducing Sugar Concentration    
        3.4.2    Determination of Ethanol Concentration    
        3.4.3    Determination of Ethanol Productivity    
        3.4.4    Viable Cell Counts    
    3.5    Experimental Designs of Project Works    
1.    COMPARISON OF PRETREATMENT STRATEGIES ON 49 CONVERSION OF COCONUT HUSK FIBER TO
FERMENTABLE SUGARS    
4.1    Introduction    
4.2    Materials and Methods    
    4.2.1    Collection and Processing of Coconut Husk    
    4.2.2    Pretreatments on Coconut Husk    
    4.2.3    Enzymatic Hydrolysis Process    
    4.2.4    Characterisation of Pretreated Coconut Husk    
    4.2.5    Scanning Electron Microscopy (SEM) Analysis    
    4.2.6    Data analysis    
4.3    Results and Discussions    
    4.3.1    Effect  of  Different  Pretreatment  Techniques    
        Coconut Husk for Production of Reducing Sugar    
    4.3.2    Characterization of Pretreated Coconut Husk    
    4.3.3    Comparison of Pretreatment Techniques    
    4.3.4    Scanning Electron Microscope (SEM) Analysis    
4.4    Concluding Remarks    
1.    STATISTICAL OPTIMISATION OF BIOETHANOL 72 PRODUCTION USING MAA-PRETREATED COCONUT
    HUSK            
    5.1    Introduction        
    5.2    Materials and Methods        
        5.2.1    Optimization of Simultaneous Saccharification        
            and Fermentation Process        
        5.2.2    Gas Chromatography-Mass Spectrometry (GC-        
            MS) Analysis        
        5.2.3    Data Analysis        
    5.3    Results and Discussions        
        5.3.1    Screening of Significant Factors by Plackett-        
            Burman Design        
        5.3.2    Path of Steepest Ascent        
        5.3.3    Optimization of Ethanol Productivity by using        
            Response Surface Methodology (RSM)        
        5.3.4Validation of Bioethanol Fermentation using    
        Optimized Condition    
        5.3.5Gas Chromatography-Mass Spectrometry    
        (GC-MS) Analysis of Bioethanol    
    5.4    Concluding Remarks    
6    CONCLUSIONS   AND   RECOMMENDATIONS   FOR    
    FUTURE RESEARCH    
    6.1    Conclusions    
    6.2    Recommendations for Future Research    
REFERENCES    
APPENDIX   
                                
 LIST OF TABLES
Table        Page
2.1    Comparison of first and second generation bioethanol    
2.2    Bioethanol production from various lignocellulosic    
    feedstock    
2.3    Comparison of lignocellulose in several sources on dry    
    basis    
2.4    The common pretreatments and their possible effects    
3.1    Formulation of NDF solution    
3.2    Formulation of ADF solution    
4.1    Cellulose, hemicellulose and lignin contents of the    
    pretreated coconut husks    
5.1    Experimental range and levels of independent variables in    
    the Plackett-Burman experiment    
5.2    Plackett-Burman design matrix representing the coded    
    values for 7 independent variables    
5.3    Path of steepest ascent experiment design    
5.4    Levels of the factors tested in central composite design    
5.5    The central composite design of RSM for optimization of    
    bioethanol production    
5.6    Plackett-Burman design matrix representing 7 independent    
    variables and the response    
 5.7    Statistical analysis of the model (ANOVA)    
5.8    Step size for substrate and pectinase loading    
5.9    Experiment design and results for the path of steepest    
    ascent    
5.10    The Central Composite Design and results of RSM for    
    optimization of bioethanol production    
5.11    Model summary and analysis of variance (ANOVA) for    
    the quadratic model   
 LIST OF FIGURES
Figure        Page
2.1    Cocos nucifera L.    
2.2    Cross-section of the fruit of Cocos nucifera L.    
2.3    Coconut husk    
2.4    A schematic diagram of plant cell wall showing cellulose    
    fibrils laminated with hemicellulose and lignin polymers    
2.5    The structure of cellulose    
2.6    The structure of hemicelluloses    
2.7    ρ-coumaryl (1), coniferyl (2) and sinapyl (3) alcohols:    
    dominant building blocks of the three dimensional lignin    
2.8    Schematic presentation of effects of pretreatment on    
    lignocellulosic biomass    
2.9    General nature of batch culture    
3.1    Glucose standard curve    
3.2    Standard curve for ethanol determination    
3.3    Protocol in performing serial dilution    
3.4    Overall process in bioethanol production by using coconut    
    husk as lignocellulosic raw material   
 4.1    Level of reducing sugar released from coconut husk with    
    two different particle sizes after enzymatic hydrolysis    
    process    
4.2    Level of reducing sugar produced through hydrolysis of    
    thermally-treated coconut husk    
4.3    Level of reducing sugars using acid pretreated coconut husk    
4.4    Level of reducing sugars produced through hydrolysis of    
    alkaline-treated (5% w/v of NaOH for 24 hours) coconut    
    husk    
4.5    Level of reducing sugars produced through hydrolysis of    
    microwave-assisted-alkaline-treated coconut husk    
4.6    Maximum level of reducing sugars produced from the    
    pretreated coconut husk    
4.7    SEM images of coconut husk after several pretreatment    
    process    
5.1    Schematic diagram of simple distillation process    
5.2    Pareto chart    
5.3    Main effect plots    
5.4    Response surface curve for bioethanol productivity showing    
    the interaction between substrate and pectinase loading    
5.5    Profile of enzymatic hydrolysis and bioethanol fermentation    
    by Saccharomyces cerevisiae at optimum conditions    
5.6    Gas Chromatography-Mass Spectrometry analysis   
CHAPTER 1
INTRODUCTION
1.1         Energy Sources
In recent years, the negative impacts of fossil fuels such as global warming, greenhouse gases emissions and the fast depletion of fossil resources have resulted in an increased interest in the research of alternate power or sustainable energy such as biofuel (Palma et al., 2012). Bioethanol has been considered a better choice than conventional fuels, as it reduces the dependence on reserves of crude oil. Bioethanol also promises cleaner combustion, lower emissions of air pollutants, high octane rating and more resistant to engine knock, which may overall lead to a healthier environment because it is carbon neutral and essentially free from sulfur and aromatics (Bailey, 1996; Prasad et al., 2007; Gupta et al., 2009).
Today, bioethanol is one of the most dominant biofuel and its global production has increased sharply since year 2000. Generally, current production of bioethanol comes from sugar and starch-based materials such as sugarcane and grains (Dermirbas, 2009). However, considering the growing demand for human food,
 lignocellulosic biomass has arisen as a more suitable feedstock for bioethanol production and a viable long-term option for bioethanol production as compared to the other two groups of raw material (Hamelinck et al., 2005). Lignocellulosic material is the most abundant plant biomass resources that can be used in bioethanol production industry. Examples of lignocelluloses are woody biomass, logging residues, energy crops (i.e. switchgrass and poplar), agricultural residues (i.e. wheat straw, rice straw and corn stover), agricultural by-products (i.e. rice hull, sugarcare bagasse) and municipal solid waste (Tan et al., 2008; Duku et al., 2011).
The lignocellulosic feedstock used in the current study for bioethanol production was the coconut husk. Coconuts are abundantly growing in coastal areas of all tropical countries. In Malaysia, about 115,000 ha of land were being used for coconut plantation in Year 2010 (Sulaiman et al., 2013). It was estimated that approximately 5.3 tons of coconut husk will become available per hectare of coconut. Some of the coconut husk was used as fibre source for rope and mats but most of the coconut husks are routinely disposed of after the coconut water is sold (Tan et al., 2008). This makes coconut husk a cheap and potential substrate that could be used for bioethanol production due to the presence of relatively high levels of cellulose and hemicelluloses in it (van Dam et al., 2004).
 1.2         Problem Statement

PRODUCTION OF BIOETHANOL BY USING PRETREATED COCONUT HUSK AS CARBON SOURCE
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  • Type: Project
  • Department: Chemical Engineering
  • Project ID: CNG0136
  • Access Fee: ₦5,000 ($14)
  • Chapters: 6 Chapters
  • Pages: 120 Pages
  • Methodology: Anova
  • Reference: YES
  • Format: Microsoft Word
  • Views: 3.1K
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    Details

    Type Project
    Department Chemical Engineering
    Project ID CNG0136
    Fee ₦5,000 ($14)
    Chapters 6 Chapters
    No of Pages 120 Pages
    Methodology Anova
    Reference YES
    Format Microsoft Word

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