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A set of preliminary experiments (light intensity 1000-4000 lux, temperature 19-31°C and pH 5-9) were carried out to adjust the range of selected variables and find their effects on the study of growth, biomass productivity , lipid and lipid content. productivity. The globally optimized reaction conditions for SCM were temperature 285.21 °C, time 25.57 min, and MeOH:oil molar ratio-23.47 resulted in 98.12 % conversion of microalgae oil to biodiesel. This combined approach of producing biodiesel and microalgae biogas together presents not only a way of sustainable fuel production, but also helps stabilize waste and generate additional income.

2.1 (a) Biomass productivity, lipid content and lipid productivity of freshwater microalgal species. b) Biomass productivity, lipid content and lipid productivity of marine microalgal species. 4.3 (a) Effect of parameters on lipid accumulation of microalgae CG12 as observed experimentally, RSM and ANN models. 139 7.3 (a) RSM-based CCD-generated array mode for experimentation and. their corresponding experimental yield and validation through ANN in CG12. b) RSM-based CCD-generated array mode for experimentation and their corresponding experimental yield and validation through ANN in GS12. b) ANOVA analysis performed for GS12. b) Sensitivity analysis performed for GS12.

4.7 3D response surface plots for process parameter and its effect on lipid accumulation of microalgae (a,b,c) CG12 and (d,e,f) GS12.

Foreword

Biodiesel has similar energy efficiency and tremendous potential for use in compression ignition engines (Knothe et al., 2015). Recently, the third generation of biodiesel, i.e., the production of microalgae biodiesel, has been reported as a promising way to circumvent the problems associated with the first and second generation (Chuah et al., 2017; Piemonte et al. , 2016). Further, it was also supported that genetic engineering and mass cultivation will be the main advance for the development of microalgae biodiesel (Sheehan et al., 1998).

Moreover, microalgae have several other advantages over oilseed feed materials, such as being incompetent with soil and food market, having high oil yield, minimizing exhaust gas emissions, being useful in CO2 mitigation and wastewater remediation (Chisti, 2007; Mata et al., 2010). ; Rodolfi et al., 2009). The advantages associated with microalgae have shifted the paradigm of biofuel research more towards microalgae-based biofuel production (Cuellar–Bermudez et al., 2015). The bio-refinery concept of microalgal biomass provides a self-subsidizing model for high-value co-product synthesis in addition to biodiesel as depicted in Figure 1.2 (Srirangan et al., 2012).

In fact, not only biodiesel can be used to produce different forms of biofuels, in fact, the entire algal biomass can be used to produce several forms of biofuels (Mussgnug et al., 2010; Yen et al., 2013).

Biodiesel

Biodiesel is simply a liquid fuel derived from vegetable oils and fats, which has similar combustion characteristics to regular petroleum diesel. The advantages of biodiesel include renewable, easy to produce, have positive fossil energy footprint, superior emission characteristics, compatible with existing engines and support domestic agriculture (Nautyal et al., 2014; Pradhan et al., 2008). The commercial fuel quality of biodiesel is measured by the American Society for Testing and Materials.

The standards ensure that biodiesel must reach to complete the reaction, it must not have traces of glycerin, catalyst and alcohol. In addition, it also certifies that it must be free of free fatty acids (FFA) and have a low sulfur content. Biodiesel can be used in its pure form as well as mixed with petroleum diesel.

The aforementioned advantages of biodiesel have made it possible to replace conventional diesel fuel with a significant reduction in greenhouse gas (GHG) emissions (Chuah et al., 2017; Piemonte et al., 2016).

Microalgae as an alternate

The aforementioned advantages of biodiesel have made it possible to replace conventional diesel fuel with a significant reduction in greenhouse gas (GHG) emissions (Chuah et al., 2017; Piemonte et al., 2016). sod., 2012; Talukdar et al., 2011). The biochemical and thermal characteristics of Chlorella species existing in this region account for 9.46% carbohydrates, 43.22% proteins and 28.82% lipids, indicating its utility as a source of bioenergy (Phukan et al., 2011). It has high specific growth rate, huge amount of biomass and biochemical composition representing total lipids of 57.14% and hydrocarbon content of 52.6%, which indicated its perspective for biofuel production (Talukdar et al., 2013).

Another high oil-producing microalga Chlorella ellipsoidea in this region was cultivated in different nutrient media for biomass and lipid production. A large number of reports available in the literature where microalgae species are reported for their high biomass and lipid content. A critical review of the microalgae species and its perspective in relation to biofuel application was highlighted by Mata et al., (2010), suggesting the importance of the biofuel production potential of different microalgae species as presented.

The huge difference between microalgal strains can be easily observed in their biomass and lipid content.

Table 2.1 (a): Biomass productivity, lipid content and lipid productivity of freshwater microalgae species

Factors affecting microalgae growth and lipid accumulation

Light
Temperature
pH
Salt
Nutrients

Light is an essential energy source for microalgal autotrophic growth and photosynthetic activity (Blair et al., 2014; Richardson et al., 1983). Furthermore, it was also concluded that the composition of monounsaturated fatty acid (MUFA) content increased under high light intensity (Liao et al., 2017). Increasing the temperature reduces the total unsaturated fatty acid in microalgae, which is necessary to maintain membrane fluidity (Wei et al., 2015).

In addition, it has been suggested that temperature above 40 °C may be detrimental to the growth of microalgae (Sánchez et al., 2008). Moreover, at a higher temperature (36 °C), the presence of a large amount of sugars and lipids was observed (Christov et al., 2001). However, the use of sodium acetate (NaAc) and sodium sulfite (Na2SO3) showed relatively less lipid accumulation (Xia et al., 2014).

Another recent report presented the latest advances in microalgae biofuel combined with wastewater treatment (Salama et al., 2017).

Table 2.2: Lipid content of microalgae under various salts.

Optimization strategies

Moreover, single-factor optimization is time-consuming, tedious process and produces erroneous results (Marudhupandi et al., 2016). In the algae culture system, RSM coupled with central composite design (CCD) is popularly used as a tool to model the probable curvatures as measured responses and provides good fit to the linear responses (Saeidi et al., 2016). It fundamentally transforms input passing through a network of weighted interconnect neurons into output predicted to the best of its ability (Ahmad et al., 2013).

It was also suggested that ANN can be chosen to optimize process parameters and can accurately explain the non-linear relationship (Sarve et al., 2015). However, limited reports are available in the literature, where RSM and ANN models have been developed and studied together for optimizing the upstream process of microalgae culture conditions for biofuel production (Dineshkumar et al., 2015). It creates solutions to the problem available in the search space using its genetic operator, selection, crossover and mutation (Fayyazi et al., 2015).

Furthermore, GA considers many points in the search space simultaneously despite determining a single point, reducing the chance of convergence to local minima (Fayyazi et al., 2015).

Conversion of oil to fatty acid methyl ester

Therefore, with the passage of generation, the fittest individual population survives and the best fit optimized state is created globally (Kadiyala et al., 2010). Nowadays, process system engineering becomes essential for establishing a sustainable and less energy intensive method (Nasir et al., 2013; Nicoletti et al., 2009). Conventionally transesterification (vegetable oils) is carried out using homogeneous (sulfuric acid, sodium hydroxide and potassium hydroxide), heterogeneous (sulfated zirconium, MgO, CaO, etc.) and enzymatic (lipase) catalysts (Meher et al., 2006) .

Therefore, various technologies for biodiesel production have been adopted for improved recovery, intensification and waste reduction through process system engineering (Banos et al., 2011; . Nasir et al., 2013). Mostafaei et al., (2013) reported an improvement in the conversion of waste cooking oil to methyl esters using ultrasonic approach (89 % yield) compared to conventional stirring technique (50 % yield). Under supercritical conditions, short-chain alcohols such as methanol and ethanol are hydrophobic and triglycerides dissolve well in them (Qiang Li et al., 2013).

Therefore, there is no issue of soap formation, catalyst efficiency and consumption, and biodiesel yield (Borugadda and Goud, 2012; Warabi et al., 2004).

Figure 2.2: The empirical reaction of transesterification.

Microalgae biorefinery

The energetic balance of the microalgae biofuel process can be developed by the high calorific value of methane (Uggetti et al., 2017). Golueke et al., (1957) first reported a methane yield of 170–320 ml/g VS from AD of microalgae Chlorella and Scenedesmus grown on wastewater. The disproportion of the C/N ratio below 20 leads to the secretion of harmful ammonia (NH3) in the digester, which has an inhibitory effect on the methanogenic bacteria, resulting in a discrepancy of the accumulation of volatile fatty acids (VFA) in the digester (Sreekrishnan et al., 2004; Wang, et al., 2012).

Co-digestion of different environmental wastes has shown that better methane production potential can be achieved by using an optimal ratio of substrates than by using a single organic material (Lee et al., 2013). Therefore, this association of microalgae biomass with agricultural residues such as rice straw, wheat straw (WS), rice husk (RH), etc. Knowledge of biodegradation kinetics and methane production could be useful for predicting methane from a specific substrate and can provide information for optimal mixing to improve biomethane potential (Cecchi et al., 1991).

Most studies do not consider the economic aspect of the biofuel production process from microalgae.

Table 2.6: Microalgae species co–digested with various biomass for methane production

Research gap

Although, with those great efforts, microalgae biodiesel is not yet on the market and lags behind conventional biodiesel production processes. The comprehensive literature review suggests that very few measures have been taken to market microalgae biofuels considering the techno-economic aspect. To date, no comprehensive report has been presented that addresses all aspects of increasing productivity, reducing processing steps and waste utilization in a biorefinery concept.

Consolidation of all the above-mentioned efforts can be a good measure to develop a technical, economic and sustainable microalgae biodiesel. Therefore, the present thesis tried and tried to cover all the major challenges of microalgae biodiesel commercialization. Most of the study used artificial media for the cultivation of microalgae, which unnecessarily increased the cost of production.

The integration of co-product synthesis together with biodiesel is a prerequisite for the production of sustainable biodiesel from microalgae.

Objectives

Thesis organization

Materials

Chemicals
Media composition
Sample collection from waste stream

Experimental techniques

Species identification
Growth study
Total chlorophyll content
Nile red staining
Lipid extraction and quantification
Transesterification
Supercritical methanol transesterification
Anaerobic digestion reactor assembly
Biochemical methane potential
Theoretical methane yield
Specific methanogenic activity and biodegradability

Optimization strategies

Response surface methodology
Artificial neural network
Genetic algorithm

Analytical techniques

Proximate and ultimate analysis
Fourier transform-infrared spectroscopy
Calorific value
Thermo-gravimetric analysis
Thin layer chromatography
Nuclear magnetic resonance spectroscopy
Gas chromatography
Gas chromatography-mass spectroscopy

Miscellaneous methods

Total solids
Volatile solids
Chemical oxygen demand
Volatile fatty acid

Isolation and identification of microalgae
Growth study
Microalgae cultivation under varying culture conditions for enhanced lipid
Optimization of physiochemical parameters using RSM and its validation

Single factor optimization
Response surface methodology
Artificial neural network

Comparison of estimation capabilities of RSM and ANN
Fatty acid composition
Evaluation of biodiesel properties of microalgae oil
Summary

Further, the preliminary experimentation strategy was discussed to study the growth profile of selected microalgae species under different physical (light, temperature and pH) and chemical (BG-11, BBM, AM, Chu) conditions. The study also includes further optimization of the cultivation conditions (physico-chemical parameters) obtained from the preliminary experimentation from the experiment design to prepare an experimental matrix using RSM followed by CCD. The interactive effect of parameters on microalgae lipid accumulation and optimization of process parameters are also presented in this chapter.

Growth study of microalgae under various salt concentration

Estimation of chlorophyll content

Lipid estimation

Determination of fatty acid composition

Summary

Scale up studies

Conversion of microalgae oil to FAME

Evaluation of significant factors using CCD

Effect of process parameters on transesterification conversion efficiency 117