The economic sustainability of any biofuel is dependent on the existence of a mar­ket, which is largely determined by the cost of production relative to alternative approaches. Such calculations are fraught with uncertainties regarding future costs of scarce resources and without proper assignment of various “hidden” costs, or costs not explicitly associated with or assigned to a particular fuel. To be fully com­parable, such costs should include societal costs such as the military and political costs associated with the import of foreign oil and the opportunity costs associated with diverting agricultural resources to the production of fuel. Additionally, at this early stage of development the final configuration of a biofuels production facility based on a nonphotosynthetic autotrophic organism is unclear. Still, it is possible to consider at least the factors of production that will drive costs and to make at least estimates regarding limits to costs of production.

The sustainable synthesis of any liquid fuel requires inorganic carbon, hydrogen, and energy from a renewable source. In the approaches under development through the Electrofuels program a renewable source of energy is converted to either hydro­gen or electricity, which in turn serves as the energy input for carbon fixation and fuel synthesis. The energy density of liquid fuels is extraordinary-gasoline con­tains roughly 13 kWh/kg or 34 MJ/L-and the entire electricity generating capacity of the USA represents roughly half of US oil consumption, assuming a conversion efficiency of 65% (Supp Calc 7). Given these levels, dedicated on-site electricity generation will almost certainly be the most cost efficient design. A cost comparison of chemolithoautotrophic approaches to corn-based fuels thus turns primarily to a comparison of feedstock costs: electricity vs. corn (Fig. 3).

In recent years, a variety of factors, including a rising demand for carbon-neutral biofuels, has driven sugar costs significantly above historical levels. At the same time, advances in renewable energy production have driven down the cost of renew­able electricity, especially from wind, but also from solar and other resources. Electricity costs are very low for on-site generation (Fig. 4), especially for fully depreciated installations; arbitrage opportunities may further diminish effective electricity costs by balancing electricity sales vs. fuel production. West Texas, for example, possesses a significant wind resource that is largely under-utilized at night, when electricity demand is low. This lack of demand leads to significant wind cur­tailment—3.9 TWh in 2009 and 2.1 TWh in 2010 of essentially “free” electricity

[66] —that would have supported production of1.5MBOE and 0.8MBOE in 2009 and 2010 respectively. This combination of effects leads to periods in which elec­tricity is a significantly cheaper feedstock than sugar for the domestic production of biofuels, a trend that could amplify in the future (Figs. 3 and 4).

To project the cost of a mature Electrofuels technology, we consider an Electrofuels facility operating at the production level of a typical corn-to-ethanol facility, producing roughly 35 million GGE annually. Feedstock costs include the cost of electricity, CO2, and water, with oxygen production considered as a coprod­uct when using an electricity feedstock and assuming a 65% overall energy conver­sion efficiency (Supp Calc 6). Wind electricity costs in the US Midwest currently range from $30 to $70/MWh [66], although these costs will diminish in the future as capital is fully depreciated. Time-of-day pricing is also especially significant for wind resources: during the cheapest 6 h of the day prices seldom rise above $20/ MWh, and wind curtailment produces sustained periods of negatively priced elec­tricity [16]. The cost of the CO2 feedstock could approach zero where concentra­tion and/or purification from waste streams is not necessary. Operating costs include maintenance and taxes, labor and overhead, materials and waste. The cost of capital is for the nth plant cost and based on capital costs for a typical corn-to — ethanol plant, using standard interest rates, construction periods, and depreciation schedules. Additional assumptions are described as footnotes to the calculations (Supp Calc 8).

Not surprisingly, the price of fuel from an Electrofuels approach is extremely sensitive to the price of the energy feedstock, and both conversion efficiencies and the choice of carbon fixation platforms are crucial. Based on realistic assumptions and a cost of electricity of even $40/MWh, the projected cost of fuel is close to $3/ GGE (Table 3); at $20/MWh—the current cost of electricity in the cheapest 6 h of the day—costs drop to $2/GGE. Significant efficiency losses included our calcula­tions include 18% from projected voltage overpotential and 14% for electricity con­version to hydrocarbon fuels. It is important to note, however, that these estimates still largely lack experimental underpinning, and more accurate estimates await additional data.

Both electricity and hydrogen feedstocks are clearly compatible with modern industrial infrastructure and both can supply the energy needed for an Electrofuels process (Fig. 5a). While hydrogen can be produced via electrolysis or perhaps from catalytic water oxidation in the future, it might also be produced from natural gas or biomass reforming, offering gas-to-liquids or biomass-to-liquids (GTL/BTL) pos­sibilities (Fig. 5b). For example, steam reforming of industrial tail gases or low value hydrocarbons can produce hydrogen at less than $1.00/kg [32] with concomi­tant production of free, clean, concentrated inorganic carbon. These values would reduce feedstock costs to $1.34/GGE and overall costs to $2.25/GGE, even consid­ering a likely increase in capital costs (Supp Calc 9).

Cost components and base values are tabulated to determine the individual cost of specific compo­nents as well as the overall cost of fuel production through electrofuels. With each cost item, a sensitivity analysis is provided in the Tornado chart on the right to illustrate how the variation in a single parameter influences the overall cost. The top of the table/chart itemizes standard engineer­ing parameters, whereas the bottom of the table/chart itemizes biological constraints, the latter which each of the Electrofuels projects address

Electrofuels

Fig.5 (a) Paths to Electrofuels using either direct current or dihydrogen as the energy source. (b) Proposed Electrofuels pathway as a gas-to-liquids technology where methane first passes through a steam methane reformer (SMR reactor) and then through a water-gas shift reaction, before the effluent is cooled and fed to an Electrofuels reactor

The physical methods include comminution (ball milling, hammer milling), irradia­tion (electron beam, microwave), steam exploration (high pressure steam) and hydrothermolysis (liquid hot water). These methods have been successfully used to pre-treat other biomass for bioethanol production [58]. Physical methods of bio­mass pre-treatment mostly result in decreasing biomass particle size and degree of depolymerisation of hemicellulose and cellulose, as well as in reducing cellulose crystallinity [29]. However, physical methods are energy intensive, and the rate of hydrolysis is slow.

6.1.1 Chemical Method

The chemicals involved in the pre-treatment of biomass can be divided into two types; acidic (sulphuric, hydrochloric, phosphoric) and alkaline (lime, sodium hydroxide ammonium sulfite). Nguyen et al. [47] reported that acid pre-treatment of

Chlamydomonas reinhardtii biomass yielded around 58% (w/w) of glucose and resulted in an ethanol yield of 29.2% (w/w) at the end of the fermentation process. Aside the promising results obtained for microalgae, the efficiency of this method has been widely verified for other feedstocks [4, 9]. The chemical methods are, by far, the most prevalent biomass pre-treatment method. This is due to the low cost of the process, and its effectiveness in hydrolysing the hemicelluloses and celluloses to sugars. They are often used in conjunction with an initial degree of physical pre­treatment to reduce the biomass particle size. Also, the chemical methods are preferred due to their low operating costs when compared to the energy-intensive physical methods [29]. Since microalgal biomass does not contain lignin, the method is efficient in converting complex carbohydrates to fermentable sugars. However, the utilization of hazardous chemicals in the process can cause severe corrosion to the fermentation vessel and the resulting irrecoverable salts may form part of the biomass, thus changing the fine and specific biomass structure and its biochemical composition.

6.1.2 Biological Method

This method involves the utilization of microorganisms such as fungi to reduce the cellulose and hemicellulose crystallinity of the biomass. It is an environmentally and energetically efficient process because the pre-treatment occurs under mild con­ditions (low temperature and pH around 6-7). However, the rate of hydrolysis using this method is too slow for industrial application, and some fermentable materials are consumed in the process. Whilst this method is unlikely to be used as a sole treatment of microalgal biomass, it could serve as the first step of a multi-step pre­treatment method [24] .

A natural evolution in process development is the replacement of the homogeneous catalysis with a solid base catalyst, change that simplifies extensively the post­processing process. In particular, it makes it easier to operate in continuous mode, eases the catalyst separation and recycling after reaction, avoids the saponification problem, and yields a cleaner biodiesel product, a purer glycerol that can be more easily marketed.

Various types of heterogeneous catalysts are being considered and studied for biodiesel production, including titanium silicates, ion-exchange resins, and zeolite metal-supported catalysts, among others. Extensive reviews of the current status on the use of solid base catalysts can be found in Liu et al. [63] and Di Serio et al. [33]. Peng et al. [75] prepared, characterized, and studied a solid acid catalyst for its activity in the production of biodiesel from several feedstocks with a high FFA content, showing that heterogeneous catalysis is a worthy option to process those types of raw materials.

Heterogeneous catalysts such as zeolites and metals may also allow for the use of feedstocks with a high FFA content [16, 31, 54]. However, some scientific and technical barriers persist relatively to their application at industrial-scale. For instance, Albuquerque et al. [2] concluded that the catalyst activity strongly depends on the metal composition of the oxides used, and new materials with well-defined structures, high surface area, and adequate basic or acid properties have yet to be developed. Although many of the solid catalysts proposed in literature for biodiesel production have good catalytic performances, they require high temperatures and pressure to work properly. Also, it is necessary to address the questions of deactiva­tion, reusability, and regeneration of the catalysts in practical conditions to assess their real potential for using in commercial applications. As heterogeneous cata­lyzed processes have advantages over homogeneous catalyzed and are easier to operate, more commercial applications will certainly be introduced in the near future with important impact on the biodiesel production.

There are many different forms of filtration. These include dead-end filtration, microfiltration, pressure filtration, vacuum filtration and TFF. Filtration involves running the algal culture through filters with defined pore characteristics on which the algal cells accumulate, allowing the medium to pass through. The culture runs through the filters until the filter accumulates a thick algae paste [8]. It has been recognised that the use of fil ter presses under pressure or vacuum are effective methods to concentrate microalgal species that are considered to be large in hydro­dynamic size such as Spirulina plantensis. The recovery of small dimensioned algae species such as Dunaliella and Chlorella with size similar to that of bacteria is difficult to perform with pressure or vacuum filtration methods. Recent studies show that TFF and pressure fil tration can be considered as energy-efficient dewatering methods, as they consume optimum amounts of energy when considering the output and initial concentrations of the feedstock [8]. Simple filtration methods such as dead-end filtration are not effective dewatering methods on their own due to issues with back mixing. However, simple filters can be used in conjunction with centrifu­gation to create better separation [15].

In ascertaining whether the microalgal biodiesel production process is carbon neu­tral or carbon negative (absorbs carbon dioxide) or carbon positive (releases carbon dioxide) a life cycle assessment (LCA) is carried out. The LCA is based on ISO 14,040 standards [11].

1.7.3 Life Cycle Assessment: Goal and Scope

The LCA is based on a solid understanding of the GHG neutrality of the process. The LCA will be conducted on the entire process, from the cultivation stage to the final processing stage (gate-to-gate assessment).

1.7.4 Life Cycle Assessment: System Boundary

The LCA system boundary is based on the physical boundary of the entire plant. Basically, a cordon is placed around the entire plant and an audit is performed on the inflow and outflow of GHGs and any energy input and output. However, as the process is developed stage-wise, the boundary is enclosed around the individual stages to simplify the audit. By including all possible factors which may affect the carbon neutrality of the process, the goal is to ensure the carbon audit is a true rep­resentation of the actual emissions from the process. Conducting such an extensive and in-depth audit allows an accurate analysis of whether such a process is feasible in reducing the GHG emissions.

Light intensity and duration of irradiation determine the growth rate and production yield, which is limited by the enzymatic mechanisms of the microorganism. This limit, referred to as light saturation point, is between 5 and 10 klux (60-120 pmol photons m-2 s-1) according to Balloni et al. [4].

Vonshak et al. [110] showed that the light/dark cycle, to which cells in the ponds are exposed during the day, is an important factor that influences the growth rate and photosynthetic efficiency and it can be completed in seconds. The light regimes to which the cultures are submitted are considered to be an important factor in the productivity and yield of photosynthetic reactions [94, 105]. Several studies have been carried out focusing on the effect of different photosynthetic photon flux den­sities (PPFDs) incident on photobioreactors, but there are few reports focusing on the effects of the duration of the day and night cycles [66, 78].

The dark/light regime in the cells is influenced by the agitation, turbulence, and cell density in the ponds [82]. When light intensity is very low, cell growth is limited or there is no cell growth [4] . On the other hand, high light intensity results in increasing cell growth up to a light intensity at which it stops with increasing light intensity. The light intensity at which cell growth begins is known as the light limit­ing region, while the light intensity at which no further increase in growth takes place with increasing light intensity is known as the light saturation point. Further increase in light intensity neither increases the specific growth rate, nor hinders growth. The point at which increased light intensity decreases the specific growth rate is the point where photoinhibition begins [53]. A high-intensity light can induce photo-oxidative stress, resulting in photo-inhibition of photosynthesis, destruction of photosynthetic pigments and cell death [64] .

Photo-inhibition is a reduction of the photosynthetic activities caused by the exposure to high PPFDs [119]. When the flux of photons absorbed by chloroplasts is too high, the concentration of high-energy electrons inside the cell is excessive, and they cannot be consumed through the Calvin cycle. These excessive electrons lead to the formation of H2O2 , which can damage cell structures [20]. Even in densely populated outdoor cultures of Spirulina spp., photo-inhibition can be observed when light intensity is 60-70% of full sunlight [111].

Light intensity has a strong influence on cell growth, nitrogen-to-cell conversion factor and cell productivity, as well as biomass composition. According to Rangel — Yagui et al. [80], the best S. platensis growth carried out in 5-L open tanks was observed with 500 mg L-1 urea, added for 14 days by a exponentially feeding pro­tocol, at a light intensity of 5,600 lux (67.2 mmol photons m-2 s-1), whereas the highest concentration of chlorophyll in the biomass was observed at a light intensity of 1,400 lux (16.8 mmol photons m-2 s-1). The best chlorophyll productivity was observed with 500 mg L-1 urea at a light intensity of 3,500 lux (42 mmol photons m-2 s-1), providing the optimal balance between cell growth and biomass chloro­phyll content. Under the best conditions for cell growth, maximum cell concentra­tion using urea as a nitrogen source was higher than that obtained with the use of KNO3 [ irrespective to the cultivation process (batch or fed-batch) used for cell growth with the latter nitrogen source. As expected, these findings highlight that the fed-batch process conducted properly is not hampered by light intensity. Using a different strategy, Danesi et al. [34[ investigated the influence of light intensity reduction on S. platensis cultivation, using urea and KNO[ as nitrogen sources applying fed-batch and batch processes, respectively, reducing the light intensity from 5 to 2 klux (60-24 mmol photons m-2 s-1) on the 9th and the 13th day of culti­vation. Increases of up to 29% in total chlorophyll production were observed for the cultivations with light intensity reduction, in comparison with the cultivations car­ried out at fixed light intensities. Irrespective of the time for light reduction, the use of urea as nitrogen source by fed-batch process led to higher cell growth, obtaining maximum cell concentration of about 1,800 mg L-1.

Soletto et al. [96] showed that the photosynthetic efficiency of S. platensis in a bench-scale helical photobioreactor reached its maximum value (PE = 9.4%) at a PPFD of 125 mmol photons m“2 s-1 . The photo-inhibition threshold appeared to strongly depend on the CO2 feeding rate: at high PPFD, an increase in the amount of fed CO2 delayed the inhibitory effect on biomass growth, whereas at low PPFD, excessive CO2 addition caused the photosynthetic microorganism to stop growing.

In general terms, the bioactivity of algal and microalgal extracts can be tested using two big groups of techniques: chemical and biological methods. Since no universal method to test bioactivity exists, marine extracts are commonly evaluated by using several methods.

As will be seen in Sect. 4, most of the bioactive compounds that can be found in algae and microalgae have been described to possess antioxidant activity; thus, most of the chemical methods that will be explained in this section are directed to measure different parameters related to the antioxidant activity.

On the other hand, marine compounds have been associated with a high number of bioactivities (mainly pharmacological activities) that can be tested by biological or biochemical methods. In this sense, several reviews covering both general and specific subject areas of marine pharmacology have been published. This kind of review arti­cles has been grouped by Mayer et al. [105] as: (a) general marine pharmacology;

(b) antimicrobial marine pharmacology; (c) cardiovascular pharmacology; (d) antituberculosis, antimalarial, and antifungal marine pharmacology; (e) antiviral marine pharmacology; (f) anti-inflammatory marine pharmacology; (g) nervous system marine pharmacology; and (h) miscellaneous molecular targets.

The oxidation-reduction potential (ORP) generally is a measurement of a sub­stance’s affinity to either gain or lose electrons. In AD it reflects the availability of oxidants, such as oxygen or nitrate ions or of reductants such as hydrogen. A high ORP (>50 mV) indicates the presence of free oxygen in the anaerobic environment. An ORP between 50 to -50 mV is characteristic of an anoxic environment with nitrates and nitrites, the most favorable electron acceptors. At ORP lower than -50 mV, the environment in the digester is strongly reducing. If sulfate ions are present and the ORP is in the range from -50 to -100 mV, sulfate reducing micro­organisms can outperform methanogens for hydrogen and acetate since sulfate is a more thermodynamically favorable electron acceptor. The most favorable ORP for fermentation and acid production is from -100 to -300 mV, which indicates that the strongest oxidant available is found in different organic compounds that can be reduced to a mix of acids and alcohols. Methanogenesis requires the ORP <-300 mV when carbon dioxide is used as an electron acceptor and methane is formed [76].

Methane yield, VS reduction, OLR, and HRT are important operating parameters for the ADP. Generally, the ratios of actual to theoretically calculated methane yield and VS reduction are relatively low (typically from 0.4 to 0.6). Biodegradability is often limited by the ability of anaerobic bacteria to hydrolyze complex organic compounds as well as by the slow rate of acetogenesis and methanogenesis stages of AD. A variety of methods, including process parameters and reactor design, feedstock pretreatment and conditioning, and source and modification of anaerobic microorganisms are used to increase the AD efficiency. The general principles of digestion with non-algal feedstock can be applied to the AD of algae. Environmental parameters have a significant impact on AD performance. Optimal process design and control allow enhancing methane yield, increasing OLR and decreasing HRT.

Reactor Design

The main goal of optimal reactor design is achievement of the maximum methane yield at high OLR and low HRT in order to reduce reactor volume and capital costs. Several high-rate digester configurations were developed over the past several decades for digestion of biosolid wastes and residues. Their characteristics and

advantages and disadvantages are described elsewhere [68, 70, 371-373]. One major strategy is decoupling HRT from SRT by anaerobic sludge immobilization [374-379], granulation, and floc formation [380-387], biomass recycling [388], or membrane retention [389-391] . The methane yield and methane production in a nonmixed vertical flow reactor (NMVFR) digester were larger and more stable at higher OLR compared to CSTR (Fig. 14) [79]. Another promising approach applied for biosolids digestion is separation of the hydrolysis and acetogenesis steps from methanogenesis, a process called a two-stage system [392-394]. A two-stage anaer­obic reactor system achieved stable methane production from M. pyrifera and

D. antarctica with an HRT of one day for each stage [395].

A special case of the two-stage system is preliminary treatment of macroalgae in percolation reactors with natural hydrolysis and acidogenesis processes. In percola­tion reactors, algae are stored in a tank yielding a drained liquid product containing VFAs and ethanol as good substrates for methanogenesis [246, 248] . Legros and colleagues compared maximum OLRs for three systems: one-step CSTR, two-step CSTR, and percolator followed by upflow and fed batch digesters for liquid and solid phases, respectively. The reported maximum volumetric loads were 2.5 g VS/L-day for one-step, 4 g VS/L-day for two-step systems, 5.3 g VS/L-day for upflow reactor, and 6.3 g VS/L-day for fed batch digester (assuming COD/VS equal 1.25). A comparison of methane yield and production rate from Ulva and Ulva juices is presented in Fig. 11.

The AD of hydrolysis juices is more economically efficient compared to diges­tion of whole macroalgae due to lower reactor size, energy for substrate heating, grinding, and pumping [246-248]. For example, the volume of digester with fixed bacteria for digestion of hydrolysis juices is 25 times smaller compared to a CSTR digester required for whole algae [245] .

Mixing

Mixing is essential for optimal distribution of substrate, intermediate products, nutrients, and microorganisms throughout the anaerobic digester, but excessive mixing can be unfavorable for methanogenic bacteria [396-399]. Furthermore, proper mixing diminishes temperature and concentration fluctuations.

Temperature Conditions: Psychrophilic vs. Mesophilic vs. Thermophilic

Psychrophilic conditions were found to be nonfavorable for methane production from algae even when natural inoculum adapted to low temperature is used to start the AD process [77, 111, 400]. The influence of temperature on digestion of Enteromorpha Iinza, Enteromorpha intestinalis, Enteromorpha prohfera, and P percursa in the range from 10 to 35°C is presented in Fig. 15 [77]. Insignificant methane was detected at temperatures under 25°C. The final methane yields were identical at 30 and 35°C, but the initial methane production rate was significantly higher at 35°C.

Generally, the degradation rate of biosolids is usually higher under thermophilic conditions, reducing the volume of the anaerobic digester. Furthermore, raising the temperature increases the lipid solubility in water and its availability for enzymatic attack. For example, during the digestion of a mixture of Scenedesmus spp. and Chlorella spp., a 27% higher methane yield was observed at 50°C compared to 35°C [110]. Mesophilic conditions can favor algal survival in the anaerobic digester and make them more resistant to biodegradation. This is evidenced by the low meth­ane yield from the digestion of cyanobacteria at 22.3°C [401 ]. The intact Scenedesmus cells were detected in a digester after 6 months of incubation [157].

But, operating under mesophilic conditions is generally more stable due to lower sensitivity of mesophilic organisms to temperature and substrate variations. Moreover, toxicity from ammonia and salts increases as the temperature increases. The observed methane yield from M. pyrifera at thermophilic conditions was approximately two times smaller than under mesophilic conditions [402]. A. max­ima gave 40-80% larger methane yield at mesophilic conditions compared to thermophilic regimes (Fig. 16b) [158]. The methane production from A. maxima was completely inhibited at 15 and 52°C (Fig. 16a) [160]. Keenan reported a similar methane yield for mesophilic and thermophilic regimes (0.312 and 0.318 L/gVS) during AD of Anabaena flos-aquae at OLR between 3.2 and 2.8 gVS/L-day [403].

In terms of global distribution, oceanic hydrates constitute about 99% of the total GH resource [178], so that a 1% error in the ocean approximations could encompass the entire permafrost hydrate reserves [178]. Kvenvolden [98] compiled 89 hydrate sites shown in Fig. 1 [178]. At those locations, hydrates were:

1. Recovered as samples (23 locations, of which 3 in the permafrost and 20 in ocean environments).

2. Inferred from (a) Bottom Simulating Reflector (BSR) geophysical signatures (63 locations), (b) decrease in pore water chlorinity (11 locations), well logs (5 loca­tions), and slumps/pockmarks (5 locations).

3. Interpreted from geologic settings (6 locations).

A measure of the dearth of direct knowledge on hydrates compares this mea­ger list, which represents the entirety of the database of natural hydrates, to the huge body of information on conventional and unconventional oil and gas reservoirs [ 209 ] .

Given their relative abundance, marine GH occurrences will likely be the pri­mary targets for future R&D activities. However, given the favorable economics of conducting long-term field programs in the Arctic (as opposed to the deep water), it is expected that arctic R&D activities will also continue. Two countries, the United States and Japan, are making considerable R&D investments in the Arctic, under the reasoning that the information gained on the behavior of gas hydrate­bearing sand reservoirs can be readily transferred to the study of marine resources at a later date.

Fig. 1 I (63), recovered (23), and potential (5) hydrate locations in the world [98]