The work described here was carried out in the Department of Chemical Engineering, Monash University, in 2010 and has not been published elsewhere. The study describes the kinetics of chlorophyll extraction from T. suecica using acetone or methanol as an extractant. The three parameters investigated in order to optimize the extraction process were storage temperature of the biomass prior to chlorophyll extraction, level of intracellular water in the biomass during chlorophyll extraction, and average temperature during chlorophyll extraction.

3.2 Materials and Methods

3.2.1 Chemicals and Reagents

Chlorophyll a and chlorophyll b standards were purchased from Sigma-Aldrich Pty. Ltd (Australia). Organic solvents (100% acetone and 100% methanol) were analyti­cal grade.

Table 4 Previous studies on HPLC fractionation of chlorophylls extracted from phytoplankton

Study Mobile phase Stationary phase

Jeffrey [23] First dimension: 0.8% «-propanol in light petroleum (by volume) Sucrose

Second dimension: 20% chloroform in light petroleum (by volume)

Jeffrey et al. [24] 90:10 (v/v) methanol:acetone for 8 min at a flow rate 1 mL/min 3 pm C18 Pecosphere

Pre-injection mix of sample 3:1 (v/v) sample: 0.5 M ammonium acetate Jeffrey et al. [24] Solvent A is 80:20 (v/v) methanol:0.5 M ammonium acetate 3 pm C18 Pecosphere

Solvent В is 90:10 methanol: acetone

Elution order: 0-3 min: solvent A; 3-17 min: solvent B. flow rates: 1 mL/min Pre-injection mix of sample 3:1 (v/v) sample: 0.5 M ammonium acetate

Jeffrey et al. [24] Solvent A is 80:20 (v/v) methanol:0.5 M ammonium acetate 3 pm C18 Pecosphere

Solvent В is 90:10 (v/v) acetonitrile:water Solvent C is ethyl acetate Elution order:

0-4 min: linear gradient from 100% A to 100% В 4-18 min: linear gradient to 20% В and 80% C 18-21 min: linear gradient to 100% В 21-24 min: linear gradient to 100% A 24-29 min: isocratic flow of 100% A

Lynn Co and Three different solvent systems were experimented Silica Gel

Schanderl [27] Solvent system 1 (modified Bauer solvents):

First dimension is benzene: petroleum ether: acetone (10:2.5:2 v/v/v).

Second dimension is benzene: petroleum ether: acetone: methanol (10:2.5:1:0.25 v/v/v)

Solvent system 2:

First dimension is benzene: petroleum ether: acetone: methanol (10:2.5:1:0.25 v/v/v).

Second dimension is petroleum ether: acetone: «-propanol

(8:2:0.5 v/v/v)

Solvent system 3:

First dimension is benzene: petroleum ether: acetone (10:2.5:2 v/v/v).

Second dimension is petroleum ether: acetone: «-propanol

(8:2:0.5 v/v/v)

In this book chapter, we presented some of the bioactive compounds that can be obtained from algae (macro — and microalgae) with potential use as functional food ingredients. The description did not attempt to be exhaustive since, considering the huge biodiversity of algae and the strong influence of growing conditions on bioac­tive formation, the list of compounds and combination could be countless. On the other hand, we try to give an overview of the enormous possibilities of algae as natural reactors able to synthesize a myriad of compounds of different polarities and with different physiological effects on human health. Many of these compounds can be major components, such as proteins, lipids, and carbohydrates and other minor components (metabolites) generated to protect algal cells against stress conditions. Most of them are useful for the food industry as macronutrients (fiber, proteins, etc.) while others have an enormous future as functional ingredients to prevent or even improve the health status of a human being.

In this chapter, we also presented new technologies to extract valuable com­pounds from algae, these processes have in common their “green” label, the possi­bility of improving the efficiency through process optimization, the removal of toxic solvents, the improved cost efficiency and the enhancement of selectivity and isola­tion steps. Several examples are described in the text demonstrating the usefulness and the advantages of such processes compared to conventional extraction ones. But, this step cannot be considered isolated but integrated in a more holistic concept of what should be a sustainable process considering algae as raw materials.

In this sense, we can think about algae (mainly microalgae) as (1) a sustainable source of mass and energy, since their processing meets the requirements for energy efficiency (transformation, growing biomass [164]; (2) a supply of clean energy for the future if overproduction of oil is obtained that can be lately used for large-scale biodiesel production [112, 192]; (3) an efficient CO2 sequestrant for greenhouse gas emissions control (Kyoto Protocol) [167, 200]; and (4) a valuable source of bioac­tives [11,131].

If we are able to think about a whole process involving the optimization of all these steps: efficient production of biomass using CO2 formed by combustion of fossil fuels in thermoelectric power plants, extraction of valuable bioactives using environmentally friendly processes to obtain high added value products that, on the other hand, leave intact residues, and process of oily fraction of biomass to produce biofuels, we will be able to work toward a sustainable, efficient, and economically viable process with many important positive implications for the economy, the envi­ronment and the human health. But, to reach this goal, it is mandatory to work with multidisciplinary teams involving scientists with expertise from phycology, molec­ular biology, agronomy, chemical engineering, food science and technology, envi­ronmental chemistry, economics, and so on.

Other nondirect benefits from this sustainable process are: the recovery of lands unsuitable for agricultural purposes, since the requirements for algae are less demanding, the advancement of genetic engineering basic studies, since more knowledge is needed to select and manipulate the most convenient strains and genes to overproduce the substances of interest, and a more efficient use of energy and sunlight. Working on sustainable processes is one of the best ways of investing in our future and in our planet’s future.

Organic compounds organized into structurally complex parts of cells are significantly less biodegradable compared to pure compounds and simple com­pound mixtures, possibly due to lower accessibility to enzymes [207]. Many studies have shown that thermal pretreatment increases solubilization of particulate organic fractions and partially hydrolyzes polymeric organic molecules. The products formed during pretreatment of pure macromolecules, as well as components of pri­mary sludge (PS) and WAS, at temperatures ranging from 130 to 220°C, was recently studied [209] . The main findings of this study are: (1) no caramelization (pyrolysis) or significant hydrolysis of starch and cellulose to mono — or dimeric reducing sugars occurred at temperatures lower than 220°C; (2) breakdown of pro­teins to smaller peptides is accompanied by significant ammonia release at tempera­tures higher than 150°C, that can lead to inhibition of methanogens; (3) unsaturated lipids are hydrolyzed mostly to VFA (acetic and propionic) while saturated lipids form long fatty acids (LFA) (valeric, capronic, heptanic); (4) amount of LCFA and products with different degrees of oxidation (aldehydes, ketones, alkanes, alkenes, alcohols) increases with increasing treatment temperature (especially for tempera­tures higher than 170°C). Some of these compounds can be toxic to microorgan­isms, especially to methanogens [62, 234].

Bougrier and colleagues classified thermal pretreatment regimes into two groups, based on their temperature range, duration, and the impact on methane (biogas) yield [196]. The first group is characterized by moderate temperature in the range from 70 to 120°C and treatment duration time from 30 min to several days. The outcome is a 20-30% increase in methane (biogas) yield. The second group is characterized by

higher temperatures in the range of 160-180°C and shorter treatment time of 1-60 min with a 40-100% increase in biogas yield. Increasing the pretreatment tem­perature to 200°C reduced the bioconvertibility of all tested pure nitrogenous com­pounds (amino acids mix, RNA, DNA, collagen) and all tested carbohydrates (ribose, deoxyribose, glucose) and increased the toxicity. Stuckey and McCarty viewed ther­mal pretreatment as the sum of two separate processes: the first is the hydrolysis of complex polymeric compounds to soluble biodegradable molecules; and the second is the formation of refractory and toxic compounds from simple degradable mole­cules [207]. This trend was found to be true for tested amino acids, nucleotides and sugars with few exceptions (arginine, guanine, thymine). The pretreatment tempera­ture around 170-175°C was found to be optimal for biodegradation of WAS due to formation of less biodegradable and toxic compounds at temperatures 200°C and higher [207, 235, 236].

Samson and LeDuy studied the influence of thermal pretreatment on solubiliza­tion and methane yield from cyanobacterium A. maxima at 50, 100, and 150°C for a 1-h contact time [233] . Thermal pretreatment at all temperatures was favorable for COD solubilization. The COD values increased by 1.8, 1.7, and 2.3 fold com­pared to nontreated samples (Fig. 12a). Solubilization of the COD reached 36.2%, 40%, and 50%, respectively. The levels of solubilization of thermal pretreated sam­ples were somewhat higher than values determined for WAS. Solubilization of WAS increased from 8.1 to 17.6% (from 2.25 to 4.9 g/L) after thermal pretreatment dur­ing 30 min at 121°C [201].

The thermal treatment resulted in no benefit or inhibited the yield of methane and VS reduction (Fig. 12b). Similarly, thermal treatment of WAS during 30 min at 121°C resulted in a significant increase of COD (more than 100%). The methane yield and VS reduction increased as well and reached 135.2% and 132.1%, respec­tively, compared to the untreated control [201]. Pretreatment of Chlorella at 80°C decreased the methane production by 19% [237].

In contrast, thermal pretreatment of unicellular algae harvested from the effluent of a high-rate sewage oxidation pond at temperatures from 40 to 120°C and treat­ment duration of 30 min increased the methane yield [238]. The methane yield increased from approximately 0.14 to 0.17 L/gVS at 50°C and to approximately 0.25 L/gVS at 100-120°C. The methane yield increased with temperature and reached a maximum value at 100°C. The authors also reported the influence of treat­ment duration (from 1 to 120 h) and biomass concentration (from 3.7 to 22.5%) on methane yield at 100°C. The maximum methane yields were observed for a pre­treatment duration of 8 h (0.3 L/gVS, 15% increase) and with a pretreated algae concentration of 3.7%.

Drying

The water content of macroalgae is in the range of 80-95% [79, 124, 144, 239], and centrifuged microalgae have a water content of 90-95% [157]. Biomass drying is energy intensive, but is considered if storage or transportation is necessary before

AD. Drying of biomass by heating at 105°C for 24 h had a negative influence on methane yield with C. kessleri and C. reinhardtii [157]. The decrease in biogas yield from C. kessleri and C. reinhardtii compared to a nondried control were 23 ± 2.8% and 20 ± 2.7%, respectively. The authors hypothesized that easily digestible VS were lost during the drying process or became inaccessible for enzymatic attack. Consequently, AD of nondried biomass is more feasible and recommended. Technologically, it is beneficial to couple algae cultivating and AD facilities.

Commercial-scale production of methane from algae requires the process to be eco­nomically feasible. Life-cycle assessment and calculation of net energy ratio (NER) are common methods to evaluate techno-economical parameters of biofuel produc­tion technology.

Although the available body of information on production from hydrates is still limited, there is sufficient information to begin identifying particular features, prop­erties, conditions, and production methods that are linked to a higher gas production potential and increase the desirability of hydrate deposits, and to use this informa­tion to develop a set of guidelines for the selection of promising production targets.

5.1 Desirable Features and Conditions

These include the following [125]:

• Large formation k and j, which are almost invariably associated with sandy and gravely formations that are characterized by low P, S and S, leading to

cap ’ wir’ gir

relatively high permeability to gas and aqueous flow.

• Medium SH (i. e.,30% < SH < 60%) corresponds to optimal QP in terms of magnitude and length of time to attain it. The effect of SH on production is not monotonic, but a complex function of SH and the timeframe of observation. A lower SH has the advantage of higher keff, leading to an earlier evolution of gas and a larger initial QP [131,132]. The disadvantages of a lower SH may include a larger water production and a lower total gas production because of early exhaustion of the resource. A high SH leads to slower evolution of gas and lower initial QP, but a higher maximum QP and total production.

• The most desirable targets can be easily identified from the inspection of the phase diagram (Fig. 14). The larger T provides a larger source of sensible heat to support the endothermic dissociation, and a larger initial P allows a larger pres­sure drop, leading to larger production rates. Thus, (a) hydrates that occur along the equilibrium line are very desirable, and (b) the desirability increases with an increasing equilibrium P (and, consequently, T). The production potential decreases as the stability of the hydrate deposit at its initial conditions increases (as quantified by the pressure differential DP = P-Pe at the prevailing reservoir T). In practical terms: we target the deepest, warmest reservoirs that are as close as possible to equilibrium conditions. In addition, the deeper reservoirs have larger overburdens and are therefore less prone to adverse geomechanical impacts.

• For reservoirs with the same hydraulic properties, SH, and P: the warmest possi­ble deposit is the most desirable. For reservoirs with the same hydraulic proper­ties, SH, and T: the reservoir with the lowest possible P is the most desirable.

• In terms of deposit classes: All other conditions and properties being equal, Class 1 deposits appear to be the most promising targets for gas production because of the thermodynamic proximity to the hydration equilibrium. Additionally, the existence of a free gas zone guarantees gas production even when the hydrate contribution is small.

• Class 2 and Class 3: Class 2 deposits can attain high production rates, but are also burdened by longer lead times of very little gas production; Class 3 deposits may yield gas earlier and can attain significant production rates, but there are indica­tions that these are lower than in Class 2. The relative merits of these two types will likely be determined by site-specific conditions.

• All classes: The difficulties of site access notwithstanding deeper and warmer oceanic accumulations appear to be more productive than permafrost ones they can have (a) a higher T (14°C is the maximum equilibrium temperature observed in permafrost-associated deposits) and a larger sensible heat available for disso­ciation and (b) a higher P, increasing the depressurization effectiveness, in addi­tion to (c) the beneficial dissociating effect of salt.

• All classes: The importance of impermeable or near-impermeable upper bound­aries cannot be overemphasized.

• In terms of production method: Depressurization appears to have a clear advantage in all three classes.

Similar to water resources, plants grown as open systems require significant fertil­izer loads to optimize biomass yield (Table 2). Brazilian sugarcane utilizes as little as 20% of applied nitrogen [34]; the remainder is largely lost to water supplies with the attendant negative impact on the surrounding environment [14]. The require­ment for nutrient complexity within soil often requires crop rotation and precludes year-over-year high biomass productivities available with closed-system bioreactors.

To the extent that growth can be separated from production, rapid CO2 fi xation is possible in an Electrofuels approach with low nutrient requirements, since relatively little biomass is produced per volume of fuel. These requirements are further dimin­ished through nutrient recycling within the biorefinery. At least some other advanced biofuels systems also address this issue; notable examples include slow growing woody biomass (with no external nutrient requirements) and other closed system photobioreactors [49, 60].

We are optimizing the chemical properties of soluble Mo-polypyridine electrocata­lysts for water-to-hydrogen conversion to increase turnover frequency and stability in microbial growth media. We are also seeking improvements to minimize electro­chemical overpotential for H2 production. In particular, we are targeting the incor­poration of electron-withdrawing groups at the axial and equatorial pyridine donors as well as methine bridges. Additionally, we are developing synthetic routes to more potential ligand frameworks where all the pyridines can be differentially functional­ized. The overall goal is to move the reduction potentials of these complexes to more positive values, which may lead to a decrease in the overpotential for catalytic reduction of water to hydrogen. We are also testing conditions and electrode materi­als that will allow R. eutropha to grow autotrophically with H2 generated in situ from electricity by the MoPy5 electrocatalyst.

As mentioned in the Introduction, we are pursuing two strategies to use these catalysts to generate H2 electrochemically for autotrophic growth and biofuel pro­duction. These strategies involved tethering the electrocatalyst to the electrode sur­face and to the surface of R. eutropha by expressing heterologous proteins on the surface that will bind metal complexes (Fig. 5). These two strategies will be evalu­ated in comparison to standard methods for electrolysis of H2O to generate H2 and O2 for R. eutropha growth.

Acknowledgments This work is funded by the ARPA-E Electrofuels program. We would also like to thank the Joint BioEnergy Institute (JBEI) for the use of its facilities and equipment; JBEI is supported by the Office of Science, Office of Biological and Environmental Research, of the U. S. Department of Energy. Work at Lawrence Berkeley National Laboratory is performed under the auspices of the U. S. Department of Energy through contract DE-AC02-05CH11231.

[1] The interest to be paid on these loans was lower than the rate of inflation which resulted in a nega­tive real interest rate.

[2] Theoretically one can produce 0.684 L of ethanol with 1 kg of sugar which is fairly close to the value established by the decree 76,593.

[3] Enzyme inactivation can result from a variety of irreversible processes, such as nonspecific adsorption to substrate, aggregation related to unfolding, and covalent chemical modification. These irreversible processes are favored by the relatively harsh conditions (high temperature and/ or acidic or alkaline pH) used for pretreatments that increase digestibility.

[4] This is particularly notable given that most GH families in Table 1 include numerous enzymes with noncellulolytic activities.

[5] Since modification is likely to be somewhat random, the odds of getting a block of i unmodified sugars in a row is nonzero, but it is likely to be quite small. Assuming each of the three hydroxyls per anhydroglucose are equally reactive and that their reaction does not influence reactivity of proximal hydroxyl groups, the probability is (1 — 0.7/3)3i = 0.673i. For i = 3, this is 0.09, and drops by a factor of 0.45 for every additional unmodified anhydroglucose.

[6]Endocellulase activity should strongly decrease the viscosity of CMC solutions by greatly decreasing chain length, whereas exocellulase activity should have little effect on viscosity.

[7] enzymes

[8]LD is lethal dose. The LD50 is the dose that kills half (50%) of the animals tested. The animals are usually rats or mice, although rabbits, guinea pigs, hamsters, and so on are sometimes used.

[9] Primary energy consumption comprises commercially traded fuels only, and excluding fuels such as wood, peat, animal waste, geothermal, wind and solar power generation.

T. M. Mata (*) • C. A.V. Costa

Laboratory for Process, Environmental and Energy Engineering (LEPAE),

Faculty of Engineering, University of Porto (FEUP), R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal e-mail: tmata@fe. up. pt

A. A. Martins

Center for Transport Phenomena Studies (CEFT) , Faculty of Engineering,

University of Porto (FEUP) , R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal

[11] K. Sikdar

National Risk Management Research Laboratory, Office of Research and Development,

U. S. Environmental Protection Agency, 26 West Martin Luther King Drive,

Cincinnati, OH 45268, USA

N. S. Caetano

Laboratory for Process, Environmental and Energy Engineering (LEPAE),

Faculty of Engineering, University of Porto (FEUP), R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal

Department of Chemical Engineering, School of Engineering (ISEP),

Polytechnic Institute of Porto (IPP), R. Dr. Antonio Bernardino de Almeida, s/n, 4200-072 Porto, Portugal

J. W. Lee (ed.), Advanced Biofuels and Bioproducts, DOI 10.1007/978-1-4614-3348-4_31, 745

© Springer Science+Business Media New York 2013

G. J. Moridis (H) • J. Rutqvist • T. Kneafsey • M. T. Reagan • M. Kowalsky Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA e-mail: GJMoridis@lbl. gov

T. S. Collett

U. S. Geological Survey, Denver, CO 80225, USA

R. Boswell

National Energy Technology Laboratory, Morgantown, WV 26507, USA

[13] Hancock

RPS Energy, Calgary, AB, Canada T2P 3T6 C. Santamarina

Georgia Institute of Technology, Atlanta 30332, GA M. Pooladi-Darvish

University of Calgary, Calgary, Canada T2N 1N4 E. D. Sloan • C. Coh

Colorado School of Mines, Golden, CO 80401, USA

J. W. Lee (ed.), Advanced Biofuels and Bioproducts, DOI 10.1007/978-1-4614-3348-4_37, 977

© Springer Science+Business Media New York 2013

[14] The NASA estimate, based on a Congressional Budget Office report, A Budgetary Analysis of NASA’s New Vision for Space, found the Apollo program cost in 2005 dollars to be approximately $170 billion. The estimate includes costs for research and development; procurement of rockets, command and lunar modules; management; facilities, including construction and upgrading; and flight operations.

Microalgal biomass requires pre-treatment before fermentation to enhance bioetha­nol production. Biomass pre-treatment process is a major contributing factor to bio­ethanol production cost. The carbohydrates of microalgae are stored inside the cell walls and between the intercellular matrices [60]. Thus, it is necessary to rupture the microalgal cell walls so that the entrapped carbohydrates can be released and, if

Fig. 12 Process flow diagram of bioethanol production from microalgae

necessary, broken down into simple sugars to be utilized in the fermentation process. Cell disruption methods can be classified as mechanical, chemical and biological [44,47, 58]. Each of these methods is able to liberate the sugar molecules.

The usage of a strong acid instead of a strong base is better suited for high acidity feedstocks, a situation normally found in waste oils and fats, making it possible to avoid the oil pre-treatment operation and providing high conversion rates with no soap formation [19, 49]. Nevertheless, it is seldom used due to its longer reaction times and higher temperatures required, when compared to the alkali-catalyzed pro­cess, and it is more corrosive to the process equipment [1, 19]. For example, Kulkarni and Dalai [56] report 88 and 95% conversion obtained, respectively, for 48 and 96 h reaction time.

Also, a higher methanol to oil molar ratio is needed to promote high equilibrium conversions of triglycerides to esters, which generally increases the production costs, due to an increase in the volume needed for the reactor and the separation of glycerol that becomes more difficult. Kulkarni and Dalai [56] report that 98% con­version is obtained for a methanol:oil molar ratio of 30:1 by comparison with a 87% conversion for a molar ratio of 6:1.

Among the several acid catalysts (e. g. sulphuric, sulfonic, phosphoric, or hydro­chloric acid) that can be used, sulphuric acid is the most common. Zhang et al. [101] evaluated economically both the alkali-catalyzed and the acid-catalyzed process, con­cluding that though the first one, using virgin vegetable oil, has the lowest fixed capital cost, the second one, using waste frying oil, is more economically feasible overall.

Kulkarni and Dalai [56] present the effect of various parameters on the acid — catalyzed transesterification, showing that the FFA and moisture content of oils are the parameters that most affect the reaction conversion. For instance, with less than

0. 5% water the conversion is above 90%, and for 3 or 5% of moisture the conversion is, respectively, 32 and 5%. The FFA effect is not so accentuated allowing one to obtain 90, 80, and 60% conversion for 5, 15, and 33% of FFA content, respectively.

Bhatti et al. [13] studied the effect of various parameters in the production of biodiesel from animal fats, concluding that the optimum conditions for 5 g of chicken and mutton tallow are, respectively, a temperature of 50 and 60°C, 1.25 and

2.5 g of H2SO4, and an oil:methanol molar ratio of 1:30 and 1:30, yielding

99.1 ± 0.71% and 93.21 ± 5.07% of methyl esters, after 24 h, in the presence of acid. Gas chromatographic analysis showed a total of 98.29 and 97.25% fatty acids in chicken and mutton fats, respectively.

Centrifugation is the preferred method for harvesting algal cells [2, 20, 21]. However, centrifugation can be extremely energy intensive, especially when considering large volumes. Centrifugation involves the application of centripetal acceleration to sepa­rate the algal culture into regions of greater and lesser densities. Once separated, the algae can be removed from the culture by simply decanting the supernatant spent medium. Filters can also be used during centrifugation to enhance the separation of the supernatant from the medium. Mohn [20] compared the appropriateness of dif­ferent makes and brands of centrifuges for dewatering of microalgae. Key parame­ters included in the study consisted of the concentration factor produced, energy consumption, relative cost, operation mode and reliability.