3.1 Classification of Gas Hydrate Deposits

Natural GH accumulations are divided into three main classes [124] based on sim­ple geologic features and the initial reservoir conditions. Class 1 deposits are com­posed of two layers: the HBL and an underlying two-phase fluid zone containing mobile gas and liquid water [129, 125] . Class 2 deposits comprise two zones: an HBL, overlying a zone of mobile water (hereafter referred to as WZ). Class 3 accu­mulations are composed of a single zone, the hydrate interval (HBL), and are char­acterized by the absence of an underlying zone of mobile fluids. In Classes 2 and 3, the entire HBL may be well within the hydrate stability zone and can exist under equilibrium or stable conditions. A fourth class (Class 4) pertains specifically to oceanic accumulations, and involves disperse, low-saturation hydrate (SH < 10%) deposits that lack confining geologic strata [140].

Another fundamental knowledge challenge is to establish a verified transient model of multiphase flow, which is experimentally validated. Currently two-phase flow systems are fairly well established. However, a rigorous three — or four-phase tran­sient model with experimental verification in flow loops is beyond the current state of the art. The accurate modeling and experimental validation of such phenomena in systems with coexistent of three or four of the gas, oil, water, ice, and hydrate phases will be vital to hydrate control in both energy production and flow assurance.

The nation’s reliance on fossil-based fuels creates problems for the environment and our national security. The production of a renewable source of motor fuels is required. We have designed a production pathway for synthesizing IBT biofuel from CO2, H2, and O2 using the genetically tractable and metabolically versatile bacte­rium, R. eutropha. The majority of the genes required for this pathway are already present in R. eutropha. Metabolic engineering strategies are being implemented to establish a semisynthetic pathway to produce IBT from CO2, H2, and O2. This IBT production pathway has the potential to affect two high-priority environmental con­cerns, capture of CO2 and production of an alternative nonfossil-based fuel.

Acknowledgments We thank John W. Quimby for critical review of this manuscript. D. S. is supported by the following foundations: Nijmeegs Universiteitsfonds (SNUF), Fundatie van de Vrijvrouwe van Renswoude te’s-Gravenhage, and Dr. Hendrik Muller’s Vaderlandsch Fonds. Other authors are supported, fully or in part, by the Advanced Research Projects Agency-Energy (ARPA-E) Electrofuels project. We wish to thank the ARPA-E directors and staff for their support.

Nowadays, algae industry is mainly focused on high value specialty products related to nutritional industry, sold from $10,000 to $100,000 per tonne; however, com­modity products, as fuels, are usually sold for less than $1,000 per tonne. This means that, in order to obtain algae commodity products, the production costs of the current technologies have to be reduced of almost one order of magnitude. In particu­lar, operating open ponds and processes as the harvest and the dewatering of algal biomass have a large impact on overall costs and energy balance. Thus, the develop­ment of a method in which algal metabolites, as hydrocarbons, can be directly extracted from the algal culture without energy costly steps can make the process more beneficial, economical, and sustainable.

The extraction of B. braunii hydrocarbons through a “liquid/liquid” method has been already accomplished by using n-hexane [45]; in our work, the SPS DBU/octanol was used analogously (Fig. 8), by exploiting the fact that octanol is a water-immiscible alcohol and that DBU, in spite of its water solubility, can be shifted into the organic phase through an adjustment of the pH to alkaline conditions (Fig. 9) [25].

Analogously to the obstacle represented by the presence of free fatty acids which could react with DBU hindering the switch of the non-ionic form of the SPS into the ionic one, also residual water in the system can be a problem. Spectroscopic data for the reaction between DBU and CO2 in presence of water are in fact consistent with the formation of the salt DBU bicarbonate ([DBUH+][HCO3-]) [40].

In our liquid/liquid extraction system after the adjusting of the pH of the aqueous phase with KOH, the water content in the upper organic phase (DBU/octanol) was 7% [25]. However, the residual water could be easily removed from DBU/octanol by bubbling N2 in the system for 30 min at room temperature; after this time, the residual water was less than 0.1%, without any significant loss of the organic com­ponents (Fig. 10).

The extractions of B. braunii cultures were performed at room temperature, cen­trifuging the samples at different speeds and simulating a high (3,000 rpm) and a low energy (300 rpm) liquid/liquid extraction process from the growth medium (Table 4). Centrifuging was chosen as the best procedure to obtain a clearer separa­tion (useful for small samples operation) of the aqueous and organic phases. This method allows to avoid vigorous stirring that should end up into an untreatable foaming, still maintaining a good extraction efficiency.

Fig. 9 Liquid/liquid

extraction system of B. braunii culture with the SPS DBU/ octanol

Although the extraction process is somewhat sluggish, the SPS DBU/octanol after 24 h at 300 rpm gives 8.2% hydrocarbon yield, almost an half of the yield achieved with DBU/octanol on freeze-dried samples (16%). Moreover, at higher rate (3,000 rpm) the extraction results faster, obtaining in 4 h approximately the same yields obtained at 300 rpm in 24 h. This can be explained by the fact that by raising the centrifuge rate, less dense algae (with higher hydrocarbon content) move quickly to the top of the water phase and release the hydrocarbons in the upper organic layer by contact.

The cultivation process relies on photosynthesis. One of the major products from photosynthesis is oxygen; thus as the algae consumes carbon dioxide and photosyn — thesise, the culture experiences a significant increase in dissolved oxygen concen­tration. As mentioned above, excess dissolved oxygen within the culture can inhibit photosynthesis and cause photo-oxidative damage to cells. Molina Grima et al. [22] found that the maximum dissolved oxygen concentration within the culture should not exceed the standard air saturation of the culture by more than 400%. This param­eter constraint is one key issue involved with the scale-up of photobioreactors. Dissolved oxygen cannot be removed within the solar receiver, thus limiting the length of the tubular receiver.

Electricity consumption and raw materials usage were the major running costs resulting from biomass production. Electricity consumption was of particular importance in this analysis as this contributes directly to carbon emissions. All car­bon dioxide consumed by the system was assumed to be supplied free of charge through flue gas from the nearby power station. The analysis of electricity con­sumption centred on the pumping and mixing of fluids in each of the production stages, and the electricity consumed by the centrifuge or filtration equipment in dewatering the culture.

In the cultivation stage, the electricity consumed in pumping carbon dioxide and water throughout the system was estimated using electricity consumption data from

Sazdanoff [30]. Sazdanoff’s consumption data were scaled-up volumetrically to meet the requirements outlined in Table 1. Also considered in the cultivation section was the electricity consumed in mixing the algal culture: by airlift pump in the reactor-style systems or paddle wheel in the raceway ponds. Electricity consumed by the airlift pumps and the paddle wheels was estimated using data from previous studies by Acien Fernandez [1] and Sazdanoff [30], respectively. The only major raw material considered in the cultivation section was the cost of culture medium, where unit costs were based on Molina Grima et al. [21] and the quantity required was developed using information provided in Danquah et al. [8].

All pumping to the dewatering unit operation were assumed to be associated with the cultivation section, thus the only running costs involved in a single-stage dewatering process was the operation of the different dewatering systems. The energy consumption of the single-stage dewatering options was estimated primarily using data provided in Molina Grima et al. [21] . For the dual-stage process, other running costs such as the flocculant and the mixing of algal broth in the flocculation tanks were also considered. Chitosan was the preferred flocculant, with costs esti­mated at US $11/kg [9]. The electricity consumption in the mixing during flocculation was determined using the data provided in Sinnott [32] .

A number of materials and solvents were required to extract saponifiable lipids from the dewatered biomass including ethanol, hexane and water. The quantities of the raw materials required were based on work by Ramirez Fajardo et al. ] 27], whereas costs were based on Molina Grima et al. [21].

Human health metrics are often overlooked in the analysis of alternative energy sources. Part of the reason for this is that, of the three classes of inputs surveyed here, these tend to have the highest embedded uncertainty. The exposure to hazard­ous substances varies significantly, and this can greatly impact the results of an analysis. Further, since limited toxicological data is available for many compounds, developing reliable causal relationships is a challenge. When impacts can be quantified in a life cycle context, they are often reported in terms of disability — adjusted life years.

Ignoring the contribution that human-health indicators may have on algae-to — energy life cycle studies could be an important oversight for several reasons. The most dangerous substances on the United States Environmental Protection Agency list of carcinogenic chemicals reveals that many are agricultural chemicals. If algae are deployed as an alternative to terrestrial agriculture, which is heavily reliant on harmful herbicides, fungicides, and pesticides, there could be a net advantage to adopting aquatic species for biomass generation. Of course, the algae cultivation sector is too young to know whether it will require significant flows of agricultural chemicals to cope with pests or other problems. Similarly, the water quality implica­tions of large-scale algae cultivation could have mixed impacts. On the one hand, algae could remove contaminants from water sources, serving effectively like a large ecosystem-level “liver” for toxin removal. On the other hand, algae could excrete low levels of toxic chemicals as exemplified by coastal red tides. In short, any large-scale production of algae is likely to have some human health conse­quence and even though it is difficult to predict how those will manifest at this early stage, it is not difficult to anticipate that better tools will be needed to understand these relationships as the technology matures and becomes deployed.

Chlorophyll content (a and b) was determined spectrophotometrically at the maxi­mum absorption wavelengths for each chlorophyll. DR 5000 UV-vis spectropho­tometer from Hach, USA, was used for all analyses. The wavelength maxima, A, for chlorophyll a and chlorophyll b are, respectively, 664 and 647 nm in 90% ace­tone and 665 and 652 nm in 90% methanol. One milligram of either chlorophyll a or chlorophyll b standard was dissolved in either a mixture of acetone (45 mL) and water (5 mL) or a mixture of methanol (45 mL) and water (5 mL) to form stock solutions. All of the stock solutions were then diluted with their respective solvent mixtures (either 90% acetone or 90% methanol) to form standard solutions with five different concentrations (0.004, 0.008,0.0012, 0.0016, and 0.02 mg/mL). Calibration curves of each chlorophyll type in a particular solvent mixture were created by plot­ting the absorbance of its standard solutions (at the maxima of both chlorophyll a and chlorophyll b) against concentration. In accordance to Lambert-Beer law, specific absorbance coefficient, a (in mL/mg/cm), is the gradient of the linear por­tion of the calibration curve [26]. Table 5 summarizes the wavelength maximas,

Amax, and the specific absorbance coefficents, a, of chlorophyll a and chlorophyll b in 90% acetone and 90% methanol. Concentrations of chlorophyll a and chlorophyll b in a pigment extract containing both chlorophylls can be simultaneously deter­mined using an extension of Lambert-Beer law which takes into account the contri­bution of chlorophyll b absorbance to the absorbance of chlorophyll a at chlorophyll a maxima and vice versa. Principles of this extended theorem and the derivation of its formulae can viewed elsewhere [26]. Based on the a values obtained in Table 5, concentration of chlorophyll a, Ca (mg/mL), and concentration of chlrorophyll b, Cb (mg/mL), in the diluted extract sample are calculated as follows:

For extracts in 90% acetone and 10% water,

Ca = 0.00964A664 — 0.00175Аб47 (1)

Cb = 0.01487A647 — 0.00410A664 (2)

where A664 and A647 are the absorbances of the diluted extract sample at 664 and 647 nm respectively.

For extracts in 90% methanol and 10% water,

Ca = 0.02215A665 — 0.01252A652 (3)

Cb = 0.01978A652 -0.00894A665 (4)

Where A665 and A652 are the absorbances of the diluted extract sample at 665 and 652 nm respectively.

The concentrations of chlorophyll in the original extract sample were obtained by multiplying the concentrations of chlorophyll in the diluted extract sample with a dilution factor of 24. Chlorophyll a yield (g chlorophyll a/g dried microalgae) was the product of concentration of chlorophyll a in the original extract sample and volume of acetone or methanol used in extraction (100 mL). Chlorophyll b yield was calculated in a similar manner, while chlorophyll yield was the sum of chloro­phyll a and chlorophyll b yields.

The Cyanophyta is a unique group of prokaryotic microorganisms and a member of a large group of photosynthetic organisms [28]. In contrast to purple and green bac­teria, the photosynthetic mechanism of cyanobacteria is oxygenic and similar to the photosynthesis mechanism in plants and algae. Several filamentous blue-green algae are able to form heterocysts, which contain the enzyme nitrogenase and fix atmospheric nitrogen [29]. Cyanobacteria possess chlorophyll a and phycobilipro — teins as part of their light harvesting antennae [30] . But cyanobacteria lack mem­brane-bound cell organelles (nucleus, mitochondria, chloroplast), which are defining characteristics of the Eukaryotic Kingdom [31]. Cyanobacteria are found elsewhere in marine, brackish water, freshwater, and terrestrial habitats with a variety of mor­phological forms: unicellular and colonial non-motile, colonial, and filamentous [32, 33]. The characteristics of Cyanophyta are presented in Table 2.

Table 2 Cyanophyta species major organic matter characteristics

Characteristic Description References

Nutrient reserves Cyanophycean starch (a-1,4-glucan) as carbon and [31, 492-496]

energy; cyanophycin (arginine and asparagine polymer) as nitrogen storage; polyphosphate as phosphorus storage; poly(hydroxyalkanoate)

Cell wall organization Multiple-layered. Envelope consists of cytoplasmic [497-504]

membrane and cell wall. Optional outer membrane, s-layer, sheath, capsule, and slime. Four-layered peptidoglycan (murein) is principal component.

Consists of glycan backbone with peptide cross linkages

Cyanobacteria are used for a variety of purposes including as a food and feed supplement due to their high protein (Table 3) and vitamin content, as a good source of fiber, and for their good digestibility. Other current and prospective applications of cyanobacteria include the production of pharmaceuticals (antiviral, antibacte­rial, antifungal, and anticancer compounds), enzymes, wastewater treatment, and use as a biofertilizer [34, 35]. Cyanobacterial species are characterized by high productivity (Table 4).

The enzymatic hydrolysis of algal cell walls and other biopolymers is a promising alternative to energy-consuming mechanical pretreatment and chemical catalytic hydrolysis at high temperature. It has large potential to increase the digestion rate and methane yield. Treatment of WAS by carbohydrases increased the biogas yield by 13% [ 195] . Pretreatment with pancreatic lipases (250 units/mg protein, dose

0. 25 g/L at 25°C for 5.5 h) of slaughterhouse wastewater with pork fat particles resulted in 35% hydrolysis of the neutral fat, but did not significantly increase the fat hydrolysis rate in the anaerobic reactor (sequencing batch type, 25°C) and did not influence the methane yield [244]. The authors suggested that at relatively low temperature (25°C), anaerobic oxidation of LCFA is the rate-limiting step.

Natural hydrolysis pretreatment of green macroalgae in percolators has been extensively studied [175, 245-249]. This method can be viewed as a type of two — step ADP and is discussed in the subsequent reactor design subsection.

The endo-b-1,4-glucanase from Cellulomonas sp. YJ5 hydrolyzed Chlorella sorokiniana cell wall and caused cells lysis after 60-180 min of treatment [250]. Immobilized cellulases hydrolyzed Chlorella cells (reduced sugars yield 62%) and gave a twofold increase in lipids extraction efficiency [251]. Other advantages of enzymatic hydrolysis include an absence of inhibiting by-products and achievement of high selectivity [252]. While this method has a large potential, it is necessary to solve several technological blocks before it can be applied in the biofuel industry.

The major roadblocks are higher cost of enzymes production and their handling, high enzymes to substrate specificity, enormous diversity of algal cell envelope composition and structure.