Manipulation of the source-sink relationship provides us with an additional approach for growth enhancement, where increased sink potency can result in enhanced growth rates. Sucrose synthase (SuSy), sucrose phosphate synthase (SPS), invertase, UDP-glucose pyrophosphorylase (UGPase), and CesA com­plexes can each act as rate-limiting factors for carbon allocation towards cellulose synthesis [52].

UDP-glucose is the direct substrate for cellulose synthesis. SuSy catalyses the cleavage of sucrose to yield fructose and UDP-glucose which is then channeled to the CesA complex [32]. Increasing levels of UDP-glucose should increase cellulose synthesis rates and consequently stimulate photo-assimilation and biomass accumu­lation. The manipulation of enzymes that are involved in UDP-glucose metabolism for increased cellulose synthesis is described in the following examples. Invertase catalyses the cleavage of sucrose to glucose and fructose and enhances the UDP- glucose levels by elevating glucose levels inside the cell [52] . Furthermore, SPS recycles fructose to generate sucrose phosphate and acts in conjunction with sucrose phosphate phosphatase to provide a constant substrate for SuSy [52] . The resultant decreased cytoplasmic fructose concentrations also promote SuSy activity, by pre­venting product inhibition of SuSy [44] . Heterologous expression of invertase in tobacco plants resulted in a significant increase in biomass and more specifically of cellulose content [15]. Moreover, SPS overexpression led to enhanced plant growth, biomass accumulation, and fiber elongation in tobacco plants [87]. UGPase also increases UDP-glucose concentration. Transgenic tobacco plants simultaneously overexpressing UGPase, SuSy. and SPS demonstrated up to a 50% increase in growth rate compared to controls. [26].

As described above, noncovalent structural variation results in heterogeneity in cellulose reactivity, as does variation in reactivity at internal vs. terminal glycosidic bonds. The corresponding differences in reactivity towards different enzymes provide the potential for synergistic enhancements in reactivity among complementary enzymes (Figs. 4 and 5). The presence of hemicellulases further increases the potential for synergy.

Early studies on mixtures of cellulase components of fungi (typically catalytic domains fused with CBMs) demonstrated that some enzyme combinations lead to higher activities than the isolated components, although these synergistic effects often showed complex concentration dependences [4, 61, 79, 80]. These concentra­tion dependences were often interpreted as a mixture of specific and nonspecific binding to insoluble cellulosic substrate, and also of physical formation of multien­zyme complexes [79]. Although pairwise synergy in trans was established in these early studies, generalities and underlying principles were not.

A number of subsequent studies have confirmed synergy in trans between non- cellulosomal cellulases and have suggested some general features. One very com­prehensive study that demonstrated synergy in trans is from David Wilson’s group at Cornell [34]. Purified noncellulosomal enzymes from the fungus Hypocrea jecorina (the teleomorph to anamorphic Trichoderma reesei) and the bacterium Thermobifida fusca (formerly named Thermomonosporafusca) were assayed sepa­rately and mixed in various combinations on a variety of cellulosic substrates. Although for several pairs (particularly endocellulases) the activities did not exceed that expected from a combination of isolated enzymes, other combinations (mostly

pairs and triples) showed substantial enhancement of activity (i. e., synergy). Synergistic mixtures include combinations of exocellulases and combinations of endocellulases and exocellulases, some of which produced a five — to sevenfold enhancement.

One way to evaluate the relationship between synergy and the endocellulase — exocellulase composition is to represent the mole fraction of exocellulases in a par­ticular enzyme cocktail, i. e.,

_ X [exo

%exo X [exo]i +X [ end ] j (6)

Plotting synergistic enhancement vs. cexo for the data from Wilson’s study ([34]; see Fig. 6) reflects the reactivity patterns described above.

Although there is considerable variation in synergy at a given value of cexo, a general trend can be seen in which activity is maximal around cexo = 0.64, i. e., a 2:1 ratio of exocellulase to endocellulase.

A more recent optimization study of t rans synergy among the cellulases of a related fungus, Trichoderma veridi (an anamorph of Hypocrea rufa), against steam — exploded corn stover revealed a similar level of synergy [86]. By using multiple regression techniques in which activities are represented with a combination of lin­ear-, quadratic-, and cross-terms, an optimal cexo value of 0.64 was determined. Since these two studies used different enzymes, the exact agreement in cexo between the two studies is likely to be partly coincidental. Nonetheless, it is clear from both studies that synergy is optimized with a mixture of exocellulases and endocellu — lases, and suggestive that synergy can be maximized by biasing toward exocellu — lases. This bias has also been seen in earlier studies [52, 70]. However, one study has shown maximal synergy in enzyme mixes biased toward endocellulases [4] .

According to one of the various embodiments, a designer Calvin-cycle-channeled pathway is created that takes the Calvin-cycle intermediate product, 3-phosphoglycer — ate, and converts it into 1-pentanol, 1-hexanol, and/or 1-heptanol by using, for exam­ple, a set of enzymes consisting of (as shown with the numerical labels 34,35,03-05, 36-41, 39, 39′-43′, 39′-43′, 12′, and 39"-43 in Fig. 8): NADPH-dependent glyceral — dehyde-3-phosphate dehydrogenase 34, NAD-dependent glyceraldehyde-3-phosphate dehydrogenase 35, phosphoglycerate mutase 03, enolase 04, pyruvate kinase 05, cit — ramalate synthase 36, 2-methylmalate dehydratase 37, 3-isopropylmalate dehydratase 38, 3-isopropylmalate dehydrogenase 39, 2-isopropylmalate synthase 40, isopropyl — malate isomerase 41, 3-isopropylmalate dehydrogenase 39, designer isopropylmalate synthase 40′, designer isopropylmalate isomerase 41′, designer 3-isopropylmalate dehydrogenase 39′, designer 2-keto acid decarboxylase 42′, short-chain alcohol dehy­drogenase 43′, hexanol dehydrogenase 12′ , designer isopropylmalate synthase 40", designer isopropylmalate isomerase 41", designer 3-isopropylmalate dehydrogenase 39", designer 2-keto acid decarboxylase 42", and designer short-chain alcohol dehy­drogenase 43". This designer pathway works with the Calvin cycle using photosyn­thetically generated ATP and NADPH for photobiological production of 1-pentanol (CH3CH2CH2CH2CH2OH), 1-hexanol (CH, CH2CH2CH2CH2CH2OH), and/or 1-hep­tanol (CH3CH2CH2CH2CH2CH2CH2OH) from carbon dioxide (CO2) and water (H2O) according to the following process reactions:

10CO2 + 12H2O ^ 2CH3CH2CH2CH2CH2OH + 15O2 (11)

6CO2 + 7H2O ^ CH3CH2CH2CH2CH2CH2OH + 9O2 (12)

14CO2 + 16H2O ^ 2CH3CH2CH2CH2CH2CH2CH2OH + 21O2 (13)

According to another embodiment, a designer Calvin-cycle-channeled pathway is created that takes the intermediate product, 3-phosphoglycerate, and converts it into 1-pentanol, 1-hexanol, and/or 1-heptanol by using, for example, a set of enzymes consisting of (as shown with the numerical labels 34,35,03,04,45-52,40, 41,39,39′-43′, 39′-43′, 12′, and 39"-43" in Fig. 8): NADPH-dependent glyceralde — hyde-3-phosphate dehydrogenase 34, NAD-dependent glyceraldehyde-3-phosphate dehydrogenase 35, phosphoglycerate mutase 03, enolase 04, phosphoenolpyruvate carboxylase 45, aspartate aminotransferase 46, aspartokinase 47, aspartate-semial­dehyde dehydrogenase 48 , homoserine dehydrogenase 49 , homoserine kinase 50, threonine synthase 51 , threonine ammonia-lyase 52 , 2-isopropylmalate synthase 40 , isopropylmalate isomerase 41 , 3-isopropylmalate dehydrogenase 39, designer isopropylmalate synthase 40′, designer isopropylmalate isomerase 41′, designer 3-isopropylmalate dehydrogenase 39′, designer 2-keto acid decarboxylase 42′, short-chain alcohol dehydrogenase 43′ , hexanol dehydrogenase 12′ , designer iso­propylmalate synthase 40", designer isopropylmalate isomerase 41", designer 3-isopropylmalate dehydrogenase 39", designer 2-keto acid decarboxylase 42", and designer short-chain alcohol dehydrogenase 43".

These pathways (Fig. 8) share a common feature of using an NADPH-dependent glyceraldehyde-3-phosphate dehydrogenase 34 and an NAD-dependent glyceralde- hyde-3-phosphate dehydrogenase 35 as a mechanism for NADPH/NADH conver­sion to drive production of 1-pentanol, 1-hexanol, and/or 1-heptanol through a designer Calvin-cycle-channeled pathway in combination with a designer hydrocar­bon chain elongation pathway (40′, 41′, 39′). This embodiment also takes the advan­tage of the broad substrate specificity (promiscuity) of 2-isopropylmalate synthase 40, isopropylmalate isomerase 41, 3-isopropylmalate dehydrogenase 39, 2-keto acid decarboxylase 42, and short-chain alcohol dehydrogenase 43 so that they can be used also as: designer isopropylmalate synthase 40′ , designer isopropylmalate isomerase 41′, designer 3-isopropylmalate dehydrogenase 39′, designer 2-keto acid decarboxylase 42′, and short-chain alcohol dehydrogenase 43′; isopropylmalate synthase 40 , designer isopropylmalate isomerase 41", designer 3-isopropylmalate dehydrogenase 39", designer 2-keto acid decarboxylase 42", and designer short — chain alcohol dehydrogenase 43", In this case, proper selection of a short-chain alcohol dehydrogenase with certain promiscuity is also essential. To improve prod­uct specificity, it is a preferred practice to use substrate specific designer enzymes.

There are three critical processes of production and three outputs that have to be considered; they are: (1) oil preparation, (2) transesterification reaction, and (3) post­reaction processing. In process control, we must ensure that both quantitative and qualitative product specification and economic performance meet health, safety, and environmental regulations. The tasks of control system are to ensure the stability of process, to minimize the influence of disturbance and perturbation, and to optimize the overall performance [19]. Figure 3 shows a schematic diagram of process control approach of integrated Jatropha biodiesel processing and detoxification process.

The following is a sequence of steps that could be employed to develop pro­cess control for a cost-effective and environmentally friendly Jatropha biodiesel production [60]:

1. Constructing a process flow diagram which identifies the major process operation.

2. Developing a strategy to improve the quality of Jatropha seed input. This strategy involves preharvest treatments and postharvest handling and technology.

3. Identifying the output characteristics that will be achieved.

INPUT PROCESS OUTPUT

4. Determining the principle process that will be applied for every output characteristics.

5. Identifying detection methods used to detect production problems and to prevent causes in the determined process.

6. Evaluating and analyzing cost feasibility of the process while always fulfilling health, safety, and environmental regulations.

7. Reviewing various possible actions for production system improvements.

Ronald Halim, Razif Harun, Paul A. Webley, and Michael K. Danquah

Abstract Rapid increase of atmospheric carbon dioxide together with depleted supplies of fossil fuel has led to an increased commercial interest in renewable fuels. Due to their high biomass productivity, rapid lipid accumulation and high carbohydrate storage capacity, microalgae are viewed as promising feedstocks for carbon-neutral biofuels. This chapter discusses process engineering steps for the production of biodiesel and bioethanol from microalgal biomass (harvesting, dewa­tering, pre-treatment, lipid extraction, lipid transmethylation, anaerobic fermenta­tion). The suitability of microalgal lipid compositions for biodiesel conversion and the feasibility of using microalgae as raw materials for bioethanol production will also be evaluated. Specific to biodiesel production, the chapter provides an updated discussion on two of the most commonly used technologies for microalgal lipid extraction (organic solvent extraction and supercritical fluid extraction) and evalu­ates the effects of biomass pre-treatment on lipid extraction kinetics.

1 Introduction

As a response to climate change and rising fuel prices, the search for sustainable and renewable fuels is becoming increasingly important. Even though biomass-derived fuels, such as biodiesel and bioethanol, are believed to deliver positive environmen­tal, social and economic outcomes compared to fossil fuels, they share similar prob­lems, such as lack of availability and the requirement for a substantial arable land which competes with terrestrial food crops and heightens concern over food afford­ability [11, 18,66].

R. Halim • R. Harun • P. A. Webley • M. K. Danquah (*)

Bio Engineering Laboratory (BEL), Department of Chemical Engineering, Monash University, Victoria 3800, Australia

e-mail: michael. danquah@eng. monash. edu. au; kobinadanquah@yahoo. com

J. W. Lee (ed.), Advanced Biofuels and Bioproducts, DOI 10.1007/978-1-4614-3348-4_25, 601

© Springer Science+Business Media New York 2013

Microalgae are currently considered to be one of the most promising alternative source for biofuels [56]. Microalgae can be grown in either saline water or freshwa­ter with extremely high diversity of strains. Since they do not require arable land, they do not compete with food crops [64] . They also serve as an effective carbon sequestration platform due to their high CO2 conversion efficiencies and offer higher areal productivity when compared to other biomass [57].

Due to its extensive use in the mariculture and the food supplement industry, microalgal biochemical composition has been thoroughly investigated [16, 20, 21, 28, 53] . Even though their exact biochemical constituents are known to substan­tially depend on classes and species, microalgae generally consists of 4-64 wt.% carbohydrates, 6-71 wt.% protein and 2-40 wt.% lipids on the basis of dry biomass [6,51]. The biochemical composition of some microalgal strains are listed in Table 1 [5]. The high lipid and carbohydrate content of microalgal biomass facilitates its potential use as a biodiesel and bioethanol feedstock. The lipids are extracted out and converted to biodiesel, whilst the carbohydrates can be used in anaerobic yeast fermentation to produce bioethanol.

This chapter examines microalgae bioprocesses engineering for biodiesel and bioethanol production. It covers the downstream processes that are needed to pro­duce biofuels from microalgae with an emphasis on the lipid extraction methods for biodiesel conversion, and the fermentation process for bioethanol production.

Pyrolysis technology relates to the heating of organic or fossil sources of solid carbon in a very low oxygen environment to temperatures over 400°C. The resulting thermal decomposition yields solid char, liquid bio-oils and tars, and syngas. The reaction conditions can be engineered to change the product ratios and properties [8, 15] as illustrated in Fig. 2 . Pyrolysis technologies that optimize for bio-oil production facilitate fast heating rates, from ambient to highest heating temperature in seconds, and are therefore described as fast pyrolysis. Utilization of fast pyrolysis for biochar and bio-oil production has been the subject of a recent investigation [28]. The focus of this chapter, however, is on slow-pyrolysis technology, which via more steady heating rates, from ambient to highest heating temperature in minutes to hours, optimizes for the production of syngas and biochar. In modern systems designed for commercial biochar production, such as that operated by Pacific Pyrolysis Pty Ltd (see Fig. 3) bio-oil produced is cracked to syngas to circumvent the necessity to market or dispose of a bio-oil [16].

The utilization of slow pyrolysis for the production of charcoal is one of the oldest industries known to society [21] . Traditional systems vent all volatiles directly to the atmosphere and have very limited process controls. This results in environmentally damaging air pollution and risks to human health and safety [1, 9, 17, 37]. Modern slow-pyrolysis technology developers need to conform to the relevant regulatory and economic requirements. This means that high environmental standards need to be met and losses of potentially valuable products to the atmosphere eliminated.

Characteristics targeted by developers of modern slow-pyrolysis technologies for the economical and sustainable production of biochar include [8, 9, 28, 39]:

• Energy efficiency: continuous feed rather than batch processing, exothermic operation without air infiltration (i. e., pyrolysis conditions rather than gasification/ combustion), waste heat recovery and recycling, utilization of insulation, lagging, and refractory.

• Reduced pollution: air emissions managed (i. e., no smoke, low NOx burners, low organic pollutants such as dioxins, etc.).

• Improved biochar yields and quality: slow pyrolysis rather than gasification or fast pyrolysis (see Fig. 2), process control to ensure consistent product quality.

• Operability: decreased labor requirement (i. e., automated materials handling, continuous operation, etc.), steady-state operation resulting in control of product quality and quantity, high workplace health, and safety standards.

• Feedstock flexibility: allowing broader range of low-cost feedstocks to be processed.

• Scalability: sufficient size to reach the required economies-of-scale while small enough to not be limited by biomass availability.

Adequate precautions need to be taken to ensure that environmental standards are upheld. For example, technology should be designed to prevent the formation of toxic compounds such as PAHs and dioxins. There is extensive literature on the reaction conditions conducive to the formation of PAHs [3, 34, 43] and dioxins [24,27,29,36], which can be referred to. It should be noted that these are usually in reference to more commonly employed thermal-conversion technologies such as gasifiers and incinerators; however, this knowledge can be adopted for pyrolysis reactor design.

It is clearly demonstrated in previous studies that fast pyrolysis of cellulose will generate a range of anhydro-oligosaccharides, resulting from random cleavage of the polymer chain [48, 75, 78, 79]. Anhydro-oligosaccharides are potential for a number of possible uses, such as the preparation of glycoconjugates, the so-called anti-adhesive drugs, and so on.

Although fast pyrolysis is a known technique to produce anhydro-oligosaccharides from cellulose, very limited studies have been carried out to produce the oligomers as a target product. Piskorz et al. [73] initiated a flash pyrolysis study on this target product. Compared with conventional fast pyrolysis aiming at the maximum bio-oil yield, the production of anhydro-oligosaccharides required stricter reaction condi­tions: higher pyrolysis temperature (850-1,200°C) together with shorter residence time (35-75 ms). The short residence time was used to inhibit the conversion of large oligomers to monomer and dimer anhydrosaccharides. Anhydro — oligosaccharides in the range of G2-G7 were successfully produced with the yield up to near 20 wt%. These oligomers could be recovered as water soluble fraction from the reaction solid residues. Moreover, substantial amounts of larger oligomers (>G7) could also be produced but difficult to be identified.

Furthermore, if single anhydro-oligosaccharides can be produced and recovered, they should be more valuable than the mixed anhydro-oligosaccharides, but no reports are available in this research field at present.

Carbon-rich microspheres can be formed by the HTC of sugar solution if treated for several minutes to hours at 180-200°C. Titirici et al. had studied the HTC of carbo­hydrate model compounds such as glucose and xylose. Their study reported the elemental carbon in the microsphere as 64 and 68% from glucose and xylose, respectively [119]. HTC of sugars is a potential alternative to produce uniform carbon- rich microspheres [120]. Kumar et al. studied the HTC of glucose solution to produce the carbon microspheres from soluble organic compounds (Fig. 13). The precipitated solids were globular with their diameter ranging from 0.2 to 2 pm and

having a higher heating value (HHV) of 24.8 MJ/kg which is comparable to lignin’s HHV (24-26 MJ/kg) [62]. Glucose in hydrothermal medium at relatively low tem­perature (180-200°C) range and longer residence time (order of few hours) under­goes mainly dehydration and partial fragmentation (C-C bond breaking) reactions.

The intermediate compounds are mainly furan-like compounds, organic acids, and aldehydes [55] . Furan-like ring compounds may undergo polymerization via aldol condensation to form soluble polymers. Aromatization of soluble polymers takes place under the reaction condition and when the aromatic clusters in aqueous solution reach the critical supersaturation point, they precipitate as carbon-rich microspheres. The process can be a novel tool for recovering the water-soluble oxygenated hydrocarbons as high heating value carbon-rich microspheres. The yield of these microspheres depends on the sugar contents in liquid solution subjected to HTC. Majority of sugar compounds present in the liquid undergoes polycondensa­tion and dehydration processes resulting in carbon-rich microspheres.

Co supported catalysts were prepared using SiO2 (D11-11 SBET = 136 m2 g-1) as a sup­port. The support was impregnated with an aqueous solution of cobalt nitrate to get a catalyst containing 20 wt% of Co (expressed as metallic cobalt); whereas, bimetal­lic catalysts were prepared by co-impregnation of the support with aqueous solution of cobalt nitrate and the precursor of the second metal in appropriate amount to obtain 20 wt% of Co and 0.1 and 0.5 wt% of M (being M = Cu, Zn, Re or Ru). As precursor of the second metal, Cu(NO3)2, Zn(NO3)2, NH4ReO4 and RuCl3*xH2O were used. The solids were dried overnight at 120°C and then calcined at 300°C (Co-Re and Co-Ru) or 500°C (Co-Cu and Co-Zn). The reduction was carried out in flowing hydrogen at 500°C, prior characterization or catalytic evaluation.

We investigated the influences of introducing method of SiO2 and its quantity on the reactive performance of Fe catalysts. Table 2 lists results of some catalysts. The con­tents of promoter Zn, K and Cu in catalyst were arranged by uniform design. CO conversion of these catalysts is distributed in a wide range. It reflects marked influence of promoter composition on catalyst performance. CH4 selectivity is only influenced by promoter K content, and it decreases with increased K content. CO2 selectivity is not completely relied on CO conversion. For example, Z8K3C6/FS10-I and Z6K2C2/ FS15-I have similar CO conversion, but their CO2 selectivity is different.

The molar ratio of H2/CO in reactor outlet is given in Table 2 for the studied cata­lysts. All of them are higher than the H2/CO ratio in reactor inlet. Such increase of H2 content is resulted from WGS activity of Fe catalyst. It brings out H2-rich tail gas after FT synthesis reaction.

In order to improve the converting efficiency of syngas in FT synthesis and pro­duce profitable chemicals, some kinds of FT synthesis process have been projected

[65] . It needs catalysts having corresponding performance to construct a desired process. The catalysts we studied are able to meet the requirement due to their per­formance distributed in wide range.