It is well known that despite the bioactive (beneficial) compounds, several toxic compounds can be accumulated in algae and microalgae. Compounds like alka­loids, domoic acid, azaspiracid, brevetoxin, okadaic acid, pectenotoxin, or micro — cystins have been described.

Therefore, sometimes it is required to perform some toxicological tests mainly based in the mouse bioassay. Article 5 of a European Commission Decision dated 15 March 2002, laying down rules related to maximum permitted levels of certain biotoxins and methods of analysis for marine bivalve molluscs and other seafood states: “When the results of the analyses performed demonstrate discrepancies between the different methods, the mouse bioassay should be considered as the reference method.” The basic procedure involves i. p. injection of an extract of the sample containing the toxin and observing the symptoms. A deeper review on toxi­cological analysis can be read in the book edited by Gilbert and §enyuva “Bioactive compounds in Foods” [42] .

4.2.1 Cyanobacteria

In contrast to many algae, the main component of cyanobacteria is proteins. They also lack a hard polysaccharide-based cell wall. These properties explain the higher digestibility of cyanobacterium species. Two genera, Arthrospira (Spirulina) and Anabaena, have been studied as a potential feedstock for the ADP. The BMP assay for a cyanobacterium mixture collected from Lake Dian resulted in a higher meth­ane yield of 0.37 L/gVS (HRT 35 days) with a methane fraction of 60-65% in the biogas [155]. The methane yield during batch digestion of Arthrospiraplatensis and Arthrospira maxima species varied from 0.29 to 0.33 L/gVS corresponding to 68-77% of the theoretical methane yield [156-158].

Samson and LeDuy studied the digestion of A. maxima in a continuous reactor and concluded that A. maxima can be the sole substrate for stable methane produc­tion. Municipal anaerobic sewage sludge can easily adapt to the cyanobacterium feedstock, and the observed methane yield was 0.26 L/gVS at an OLR of 0.97 gVS/ L-day, HRT of 33 days, and T at 30°C [159]. Despite high ammonia and fatty acids concentrations (2.5 and 2 g/L respectively), methane production was stable possibly due to high alkalinity (8 g/L) and pH of 7.55.

The incoming VS concentration, OLR, and HRT have a large influence on AD stability and methane yield with A. maxima (Fig. 9) [160]. The methane yield and

Tabic 18 Characteristics of AD of brown seaweeds

M. pyrifera (21.5% mannitol content from TS)

M. pyrifera (8.3% mannitol content from TS)

M. pyrifera (ground)

M. pyrifera (ground, desalted)

M. pyrifera (ground control) M. pyrifera (ground. N and P added)

M. pyrifera M. pyrifera M. pyrifera M. pyrifera added)

M. pyrifera adopted sludge)

Table 18 (continued I

M. pyrifera (ground, inoculum D: Л + marine sediments)

M. pyrifera (ground, inoculum E: analogous to D. developed at room T)

pyrifera (ground, control) pyrifera (ground) pyrifera (ground) pyrifera (21.5% mannitol content from TS >

M. pyrifera S. fluitans

Sargassum tenerrimum

L. hyperborea L. saccharina A. nodosum

18

IS

BMP biomethane potential; CSTR continuous stirred-tank reactor; SCSTR semi-continuous stirred-tank reactor; NMVFR non-mixed vertical flow reactor; USR upflow solids reactor; BFR baffle-flow reactor; ASBR anaerobic sequencing batch reactor; UFA upflow anaerobic filter “Estimated from data given in the paper

bVS reduction estimated from data given in the paper using an equation VS red. = [L(CH4 / gVS)] / [L(CH4 / gVS)]^^

“Methane yield estimated from biogas yield given in the paper using a CH4/biogas ratio of 0.5 dEstimated from data given in the paper using total work volume 6 L and VS/TS ratio of 0.6

methane volumetric production rate were 0.04-0.36 L/gVS and 0.17-0.8 L/L-day, respectively. The maximum methane yield was obtained at HRT equal to 30 days, VS concentration of 20 gVS/L, and the OLR of 0.67 gVS/L-day. Despite a high concentration of ammonia (1.9-7.1 g/L) and volatile acids (up to 23.2 g/L), the methane production was stable with the exception of operation with HRT of 5 days and high feed concentration at HRT of 10 days. The average methane content of the biogas was in range of 69-71%. At high OLRs, it dropped to 46-60%, which is evidence for inhibition of methanogens. A stable ADP occurred when the alkalinity was high (7.2-29 g CaCO3/L) (Table 19).

The high cost of biofuel production and low efficiency of captured energy are major factors that limit the large-scale use of algae for biofuels. The integration of the ADP into the production of other high-value products (e. g., food supplements, phar­maceuticals, and clean water) from algae is likely to make AD economically attrac­tive for biofuel generation.

5.3.1 AD Integrated into Other Algal Biofuel Production Pathways

There are several algae to biofuel conversion technologies, such as lipids extraction followed by transesterification, thermochemical hydroprocessing, phototrophic microbial fuel cell (PMFC), and algal hydrogen production. These processes gener­ate large quantities of waste algal biomass, residues, or by-products. The ADP is a prospective technology that can convert these waste materials into valuable fuel.

The assessment of the production potential of hydrates requires predictions of their complex behavior. The reliability and accuracy of these predictions hinges on the following three factors: (1) the availability of robust numerical simulators that describe the dominant processes and phenomena, (2) knowledge of the parameters and relationships that quantify the physical processes (usually obtained from labo­ratory experiments and/or from field tests either by direct measurement or through history-matching) and the thermophysical properties of all the components of the simulated system, and (3) the availability of field and laboratory data for the valida­tion of the numerical models. The complexity of the coupled processes involved in the dissociation reaction does not permit the use of analytical models either for direct predictions or for the verification of the numerical models except under lim­ited conditions, i. e., at early times and after significant approximations.

Thus, the role of numerical simulation is critically important, and is practically the only tool that allows the assessment of the gas production potential of hydrates. It allows the design of laboratory and field experiments, can provide answers (or, at a minimum, general behavior trends) to very complicated problems at a very rea­sonable cost before necessitating substantial investments for field operations, and allows investigation of a wide range of alternative (“what-if ’) scenarios that would be impossible to explore otherwise. Note that even if there are no field or laboratory data for code validation and only very sketchy data describing the properties and physical processes in the system, numerical simulation can provide very important insights (provided the underlying physics are correct and representative of the simu­lated processes) because it makes it possible to determine technical feasibility, to establish envelopes of possible solutions, to determine sensitivity to particular parameters and processes, and to identify promising target zones of hydrates for development.

Knowledge of electrical properties of GH-bearing media is useful in hydrate pros­pecting and monitoring HBS undergoing changes during gas production. Either electrical conductivity or permittivity can be used to distinguish between water and non-water pore filling materials such as hydrate and gas. Electrical conductivity is dominated by the conductivity of the pore fluid; however, surface conduction must be considered for high surface area sediments [81]. Under conditions where hydrate forms or dissociates, the pore fluid conductivity will change due to freshening (hydrate dissociation) or ion exclusion (hydrate formation). Because the effect of ionic concentration is much weaker for the permittivity, this may be the more reli­able indicator in many circumstances. The systematic examination of the effects of THF hydrate on the electrical properties of various media [104, 106] provided use­ful qualitative insights, but applicability to methane systems has not been deter­mined. No comprehensive study has been performed for methane HBS, studies on which has been limited to measurements of electrical resistivity of a few samples [182-185].

5.2.3 Geophysical Properties: Wave Velocities and Attenuation

These are critically important in the exploration, detection, and production monitoring of GH. Compressional (P-) and shear (S-) wave speeds have been measured in a variety of medium/hydrate combinations [6, 219], but these did not involve CH4 and the results have qualitative value for HBS studies. Waite et al. [208] measured the P — and S-wave velocities of methane hydrates in Ottawa sand at different SH. These hydrates were formed using the excess gas method and cemented the grains of the sand, resulting in very stiff samples. No systematic tests examining P — and

S-wave velocities for a variety of porous media types at a range of methane SH and pore-filling habits have been published, but such tests are now in progress.

Like most alcohols, IBT is expected to be toxic to microbial biocatalysts. Removal of the IBT as it is formed will help avoid product inhibition and maintain high reac­tor productivity. Thus, in situ product recovery will be an integral part of the biore­actor design effort. Because the physical properties of IBT are similar to those of

gas inlet

Ho ow fibers with attached ce s

Shell-side gas outlet

Tube-side gas inlet

n-butanol, methods developed to remove n-butanol from fermentation broths are also likely to work for IBT. A variety of adsorbents have proven effective at recover­ing n-butanol from fermentation broths [92-94], including polymeric resins, which adsorb n-butanol through hydrophobic interactions [95]. Hydrophilic polymers, like polyamides, polyurethanes and polyesters showed weak n-butanol adsorption. In addition, low-alumina zeolites, such as silicalite, effectively adsorb alcohols from dilute solutions. After the butanol has been adsorbed, it can be recovered from the resin by heat desorption. This desorption technique is less energy intensive (~2,000 kcal/kg alcohol) than steam stripping (~6,000 kcal/kg alcohol) or gas strip­ping (~5,000 kcal/kg alcohol) [93].

Chiara Samori and Cristian Torri

Abstract Lipid extraction is a critical step in the development of biofuels from microalgae. The use of toxic and polluting organic solvents should be reduced and the sustainability of the extraction procedures improved in order to develop an industrial extraction procedure. This could be done by reducing solvent amounts, avoiding use of harmful solvents, or eliminating the solvent at all. Here we describe two new processes to extract hydrocarbons from dried and water-suspended samples of the microalga Botryococcus braunii. The first one is a solvent-based procedure with switchable polarity solvents (SPS), a special class of green solvents easily convertible from a non-ionic form, with a high affinity towards non-polar compounds as B. braunii hydrocarbons, into an ionic salt after the addition of CO2 , useful to recover hydrocarbons. The two SPS chosen for the study, based on equimolar mixtures of 1,8-diazabicyclo-[5.4.0]-undec-7-ene (DBU) and an alcohol (DBU/octanol and DBU/ethanol), were tested for the extraction efficiency of lipids from freeze-dried B. braunii samples and compared with volatile organic solvents extraction. The DBU/octanol system was further evaluated for the extraction of hydrocarbons directly from algal culture samples. DBU/octanol exhibited the highest yields of extracted hydrocarbons from both freeze-dried and liquid algal samples (16 and 8.2%, respectively, against 7.8 and 5.6% with traditional organic solvents). The second procedure here proposed is the thermochemical conversion of algal biomass by using pyrolysis; this process allowed to obtain three valuable fractions, exploitable for energy purpose, fuel production, and soil carbon storage: a volatile fraction (37% on dry biomass weight), a solid fraction called biochar (38%) and, above all, a liquid fraction named bio-oil (25%), almost entirely composed by hydrocarbon-like material, thus directly usable as fuel.

C. Samori (*) • C. Torri

Interdepartmental Research Centre for Environmental Sciences (CIRSA), University of Bologna, via S. Alberto 163, 48123 Ravenna, Italy e-mail: chiara. samori3@unibo. it; cristian. torri@unibo. it

J. W. Lee (ed.), Advanced Biofuels and Bioproducts, DOI 10.1007/978-1-4614-3348-4_27, 651

© Springer Science+Business Media New York 2013

1 Introduction

The need to replace fossil fuels with fuels derived from renewable biomass is cur­rently focused on biodiesel from oleaginous plant seeds and ethanol from sugar — cane/corn; however, this first-generation biofuels, primarily produced from food crops and mostly oil seeds, are limited in their ability to achieve targets for biofuel production, climate change mitigation, and economic growth; moreover, the recent dramatic increase of food stocks prices has become a worldwide emergency. Because of these environmental and social concerns, the attention is recently shift­ing towards the development of next-generation biofuels mainly produced from non-food feedstock [1], by converting for example the highly abundant and wide­spread non-edible lignocellulosic fraction of plants. A further exploitable source of biofuels relies on the aquatic environment, specifically on micro and macroalgae; lipids, which include acylglycerols and hydrocarbons, represent the most valuable fraction of microalgal biomass as their high energy content per mass unit is similar to conventional fuels. Several oleaginous microalgae (with lipid content exceeding 20% of their dry weight) have been exploited to this purpose [2], and the biodiesel obtained has been claimed to be more convenient than conventional biodiesel from plant seeds [3, 4]. Benefits rising from the utilization of aquatic over terrestrial bio­mass include: (1) higher sunlight use efficiency (about 5% vs. 1.5% [5]), (2) utiliza­tion of marginal areas (e. g. desert and coastal regions), (3) possible coupling with other activities (e. g. wastewater treatment, CO2 sequestration) [6-9], (4) minor dependence on climatic conditions, (5) availability of a larger number of species, and (6) easier genetic manipulation to modify chemical composition (e. g. lipid con­tent) [10]. However, the industrial development of fuels from microalgae is still hampered by higher overall costs with respect to both fossil fuel and first generation of biofuels counterparts: operating open ponds and bioreactors are expensive and the harvesting of algal biomass is energy costly [11]. For this reason, the net energy balance from microalgae cultivation is still debated [12, 13]. Moreover, besides the cost of growing and collecting microalgae, downstream processes are to be taken into account to evaluate the overall productivity. Botryococcus braunii is a freshwa­ter colonial green microalga proposed as a future renewable source of fuels because it is capable of producing high levels of liquid hydrocarbons [14]. There are three main B. braunii races, each one synthesizing different types of olefinic hydrocar­bons: the A, B, and L races. The A race (Fig. 1) accumulates linear olefins, odd numbered from C23 to C31, chiefly C27, C29, and C31 dienes or trienes; some studies have revealed that oleic acid is the direct precursor of these specific olefins [15] and that decarboxylation of very long chain fatty acid derivatives, activated by a b-sub — stituent, is the final step which leads to the formation of the terminal unsaturation [16]. The B race produces polyunsaturated triterpenes (botryococcenes), while the L race synthesizes one single tetraterpenoid hydrocarbon named lycopadiene [17, 18]. Both A and B races contain similar amounts of lipids (approximately 30% on a dry weight basis), but with a very different composition: in the A race hydrocarbons, non-polar lipids and polar lipids are, respectively, 25, 60, and 15% of the total lipids,

Fig. 1 Botryococcus braunii, A race

whereas in the B race the percentages are 71, 9, and 20%, clearly indicating that one quarter of the dried biomass of the B race is composed by hydrocarbons [19].

Specifically for B. braunii, the bulk ofhydrocarbons is located in external cellular pools and it can be recovered from algal biomass by means of physical process, named cold press and typically used to extract more traditional food oils as olive oil, and by means of chemical process (extraction with solvents) or both [20]. The chemical pro­cess, mainly used for the extraction of industrial oils such as soybean and corn oils, is generally based on an extraction with n-hexane, to obtain vegetable oil in higher yields and with a faster and less expensive process [21] . However, the existing solvent approach is characterized by several problematic aspects, such as the high solvent/ biomass ratio, solvent hazard (including solvent toxicity, volatility, and flammability) and large solvent losses (e. g. in the extraction process of soybean oil, n-hexane losses are 1 kg per tonne of beans processed [22]). Because of this general lack of “green­ness” in the chemical extractive processes, in the last years different efforts have been made to reduce the use of toxic and polluting organic solvents and to improve the sustainability of the extraction procedures from aquatic and terrestrial biomass, for example by using supercritical fluids [23, 24].

Here we present two novel methods for the extraction of lipids from B. braunii, comparing the extraction efficiency of the new processes with those of traditional organic solvents. The first method [25] is a solvent-based process, more sustainable than the traditional solvent extraction because it involves the use of switchable polar­ity solvents (SPS) [26, 27], a “new” class of green solvents, considerable as reversible ionic liquids, with the unique and advantageous feature of having switching solubility behaviour, correlated with reversible polarity. This feature can be successfully exploited in practical applications as extraction procedures or chemical reactions, bypassing the cumbersome need to change solvent in each step of the process itself.

The second method is based on the thermochemical conversion of B. braunii biomass by using pyrolysis [28], in order to obtain, directly and in one step process, a liquid fraction rich in lipids, a gaseous fraction useful for energy purposes, and a soil-amending co-product called biochar [29] .

The solar receiver tubing must have a specified length so that photosynthetic growth can be optimised. It has been shown that the maximum tube length relies on three parameters: liquid velocity, dissolved oxygen concentration and the rate of oxygen production by photosynthesis. Generally, a tube run in a photobioreactor should not surpass 80 m. However, the maximum length of tubing is dependent on solar inten­sity, biomass concentration, liquid flow rate and initial oxygen concentration at the tubing entrance [22]. Molina Grima et al. [23] states that “other than “scale up” by multiplication of identical tubular modules, the only way to increase volume is by increasing length and/or diameter”. Ten years on, the debate over scale-up is still prevalent, with no clear solution readily available. A possible solution to scale-up is to make use of current cultivation designs and employ several cultivation units to produce a significant amount of biomass. However, the process must produce enough biomass such that it will offset extensive equipment costs.

The annual costs represent a range of expenses incurred in the running of the plant from payroll charges to maintenance costs. The most significant of these costs is depreciation, which is calculated using the FCI based on 10-year plant life as rec­ommended in Peters et al. [26] . All other annual costs were calculated using the methods specified in Molina Grima et al. [21] with the exception of labour, supervi­sion, wastewater treatment, and goods and services tax. Labour was assumed to be constant, with 12 employees working during the day and 3 working at night, each charged at the standard labour hourly rate given in ENR (US $34.16). Supervision was also assumed to be constant, with two managers working during the day and one at night, charged at the skilled labour hourly rate again outlined in ENR (US $44.99). Wastewater treatment cost was also estimated based on the costing data reported by Molina Grima et al. [21]. Finally, goods and services taxes were charged at a rate of 10%, reflecting the tax codes applicable to Australia.

In all LC studies, a reference flow is needed to which all other modeling flows of the system will be related [13]. This flow must be a quantitative measure and for some industries, e. g., steel, the choice is usually obvious like X kg steel at the foundry. In other cases, including algae-to-energy systems, this decision can be more complicated. Recent studies have selected a wide variety of functional units (FU) including volume of biodiesel, dry mass of algae produced, kilometers of truck transport, and total energy embedded in the algae assuming the biomass is burned (see Table 2). All of these FUs are valid bases from which to evaluate algae LC, but this diversity in FUs does not make for straightforward comparison between studies. The lack of consensus on a standard FU reflects the lack of indus­try agreement on what the best products to make with the algae will be. Some of the assumptions about goal and scope setting carry over into the functional unit since a FU of liters of biodiesel will inherently exclude the value that could come from a by-product such as ethanol.

LEmEMD

5% RMEE Boundary

Fig. 2 Many studies assume that the upstream impacts of delivering fertilizers and carbon dioxide should not be included. A cut off of 5% was assigned to LC contributions that would be neglected in the analysis (from Sander and Murthy [24])

In LCA more broadly, FUs sometimes require that a performance constraint be applied in order to normalize between dissimilar systems. A carpet, for example, is quieter than a wood floor, even if the latter is more durable. Using a square meter of flooring as the functional unit may overlook performance characteristics (noise buffering and durability) that will ultimately impact the analysis [1]. In the case of algae, performance constraints are certainly limiting in a few important ways. When benchmarking algae to other terrestrial crops, it is useful to apply an FU that is com­monly accepted by the biofuels industry. Though bushels of corn or liters of ethanol do not apply directly, analogs are possible. For example, algae might be compared in terms of dried biomass generated per unit area or liters of biodiesel produced per unit area per time. Energy content can be used as an FU, though it can overlook important differences between biomass. Algae may have a high heating value com­parable to switchgrass though in practice, converting algae to usable fuel is quite a bit more straightforward.