Total lipid was determined as described by Jones et al. [24] in order to as­sess the oil available for biodiesel synthesis for both algal species. Briefly, dried algal pellets (approximately 30 mg) were extracted with 20 mL of 2-EE for 30 min at 60 °C with continuous stirring. The solution was then filtered through 0.47 pm PTFE membrane (Millipore) and the residual biomass was extracted with a second 20 mL portion of 2-EE. After filtra­tion, the two filtrates were combined, dried under vacuum, and weighed.

The lipid content of microalgae varies among different species and strains (Table 2 [19,20]). The lipid content of microalgae is usually in the range of 20% to 50% (dry base), and can be as high as 80% under certain cir­cumstances. Selecting high lipid content and fast growing microalgae is an important step in the overall success of biodiesel production from mi­croalgae. Traditional methods of screening microalgae for high lipid con­tent rely on time-consuming and laborious lipid extraction process which involves cell wall disruption and solvent extraction of a reasonably large amount of microalgae cells. Recently, high-throughput screening tech­niques employing lipophilic fluorescent dye staining (such as Nile Red [21], BODIPY 505 [22]) and fluorescence microscopy or flow cytometry are being developed [23]. With these new techniques, the amount of sam­ple and preparation time are greatly reduced because the lipid content of algal cells is measured in situ without the need for extraction. Lipid con­tent and lipid productivity are two different concepts. The former refers to lipid concentration within the microalgae cells without consideration of the overall biomass production. However the latter takes into account both the lipid concentration within cells and the biomass produced by these cells. Therefore lipid productivity is a more reasonable indicator of a strain’s performance in terms of lipid production.

In many industrial processes there is often a source of effluent as well as flue gases. Wastewater treatment plants, farms with AD plants, breweries, distilleries and oil refineries all have the potential to offer both materials. The basic requirements of a system to cultivate algae are an area for in­frastructure, a source of nutrients (most importantly N and P), a source of concentrated carbon dioxide, freshwater and a consumer for the products obtained. Table 10 displays a number of areas where algal cultivation may be appropriate and the advantages and disadvantages of such a system. Table 10 shows a variety of potential industries where cultivation of algae could be possible. The majority of these industries provide a wastewater stream with sufficient nutrient loading for the growth of algae. Oil refinery wastewater may have a nutrient concentration too low for optimal growth nevertheless if necessary additional fertiliser could be supplemented. The flue gases found in each of the industries are likely to contain a CO2 con­centration of up to 15% and this value is considered to be near the maxi­mum level that will allow algal growth before it becomes toxic [49]. Each of the flue gases mentioned is likely to boost algal growth whilst seques­tering carbon simultaneously.

Depending upon the industry, there are likely to be many problems to overcome. High nutrient loadings (farm effluent, distillery effluent)

would lead to poor treatment or toxicity and therefore require dilution with freshwater. To dilute such high concentrations would require significant sources of freshwater possibly needing expensive transportation costs and environmental issues if located in a water stressed area. Wastewaters, par­ticularly those from chemical industries such as oil refining and bioethanol production, could potentially contain toxic contaminants. Similarly flue gases may contain toxins that could affect the growth of the algal biomass. It is evident that there are many different opportunities for the implemen­tation of algal cultivation in industry. Nevertheless it is not possible to have one fixed solution. Every scenario will have different wastewater characteristics, available water and land, varying flue gas characteristics, energy needs and problems related to implementation. Every approach to implementation may be different but the concept allows flexibility.

The photosynthetic efficiency can be calculated as the energy content of the glucose produced during photosynthesis divided by the incident ra­diation. This value is different than the overall energy efficiency of growth, which includes the cost of living (i. e., respiration to enable cell functions), conversion of glucose to biomass, and required energy inputs (e. g., mix­ing, nutrient supply, etc.) [29]. The energy content of the glucose produced (per liter processed) can be calculated as:

ЁСН20 = (/ ■ PAR ■ PTE ■ PUE ■ a)

where tc is the volumetric irradiance (in joules per liter of processed volume), PAR is the photosynthetically active radiation fraction (0.46), PTE is the photon transmission efficiency, and PUE is the photon utiliza­tion efficiency [30]. The volumetric irradiance can be converted to an areal irradiance, I, according to:

where tc is the cultivation time (123 days for the Experimental Case and 12.5 days for the Highly Productive Case) and d is the pond depth (0.2 m for both cases). In Equation 3, the variable a characterizes the effi­ciency by which photons used for photosynthesis are converted to glucose through Z-scheme photosynthesis. With a quantum requirement of 8 mol photons per mol of glucose (the energy content of glucose is 467.5 kJ/mol) and an average photon energy content of 225 kJ/mol [30], a = (467.5/8 •

225) = 0.26 [29]. The photosynthetic efficiency, PE, is the ratio of EDCH2) to І, which becomes:

(5)

The amount of energy contained in the growth volume (as algal bio­mass), EDgv, can be calculated from:

where HHVGM is the higher heating value of the grown algal biomass. The amount of energy contained in the growth volume can also be calcu­lated from:

tDGV = / ■ PAR ■ PTE ■ PUE ■ a ■ (1 — CoL) ■ т

where CoL is the cost of living, which is defined as the fraction of glu­cose consumed for cellular operations [30]. The energy conversion of glu­cose to biomass energy can be grossly simplified as a single-step process, represented by t. Assuming algae have the Redfield stoichiometry defined by Clarens et al. [15] ( C106H181O45N15P ), the conversion of glucose to algal biomass can be approximated as:

106CH2O + 15NaNO3 + 0.5P2O5 + C106H181O45N15P + 8H2O + 42.75O2 + 15NaOH

2 3 2 5 106 181 45 15 2 2

(8)

The higher heating value (HHVGM) for algae can be estimated as stated by Clarens et al.:

HHVnh, = 35160 • x + 116225 — 11090 • x„ + 6280 • x [kJ/kg]

GM c H 0 n

where x is the mass fraction of each element (carbon, hydrogen, oxygen, and nitrogen) [15]. The HHVGM for the algae considered here is 24.49 MJ/kg (59.12 MJ/mol). The energy conversion of glucose (106 mol with a HHV of 467.5 kJ/mol) to biomass energy is represented by т = 1.19. Com­bining several of these relations, the PE can be calculated as:

5.2.5 ENERGY RETURN ON INVESTMENT FORMULAE

The second-order energy return on investment, 2nd O EROI is calcu­lated as:

„nd ЁОоШ ЁОво + ЁОвмр (11)

Eg + Ёр + Ёк Ёс + Ёр + Ёк

As a second-order analysis, direct and indirect energy inputs are in­cluded, while a first-order analysis would include only direct energy inputs [5]. An apostrophe accent is used to denote units that are reported with respect to the growth volume processed, such as the energy inputs in units of J per L processed (J/Lp).

To account for differences in energy quality among the inputs and out­puts, the quality-adjusted second-order energy return on investment (QA 2nd EROI) was calculated by multiplying each input and output by priced — based quality factors. The quality factors (QF) were calculated for energy flows based on the energy price (EP), which is the price of each energy source per joule, and correlates the relative value of each fuel [31]. U s­ing coal as the arbitrary standard with a quality factor equal to 1 ($1.5/ MMBtu, $1.4/GJ), the quality factors used in this study were: electricity

19.5 ($27.8/GJ, 010/kWh), petroleum 14.5 ($20.6/GJ, $0.66/L), and natu­ral gas 2.7 ($3.8/GJ, $4/MMBtu) [32]. The bio-oil was assigned the QF of petroleum and methane was assigned the QF of natural gas. For materials, the quality-factor was determined as:

where MP is the price (in $/kg), EE is the energy equivalent (in MJ/kg), and EPcoal is the energy price for coal ($1.4/GJ).

Progress to understand the intercellular interactions of microorganisms has been linked to the investigation of prokaryotic signaling molecules; however, there is increasing evidence of physically mediated communica­tion for some events, including cell division, adaptation and stress conditions [96]. The hypothesis that electromagnetic forces have a fund mental role in organization and transport of entities is supported by indirect and direct measurements of the electromagnetic fields around living cells.

3.4.2.7 ELECTROMAGNETIC CELL FUNCTIONS

The electromagnetic fields serve as mediators for the interconnection of the organism with the environment as well as between organisms. Electric dipole and multipole moments are common to every biological structure and macromolecule. Oscillating multipole EMF may be generated as a result of interaction of these dipoles and multipoles with electromagnetic emitters and transceivers [97]. Thus the fields produced by the organisms play an important role in the coordination and communication of physi­ological systems and informational interactions in addition to energetic interactions which play a significant role [98]. The endogenous physio­logical EM rhythms control and determine the growth and differentiation of cells and are essential for spatiotemporal organization at the subcellu­lar, cellular and organism level [70]. With the recent development of the “nanosized voltmeter” using a voltagedependent fluorescent nanosensor (E-PEBBLE), the first complete three-dimensional profiling throughout the entire volume of living cells was accomplished. The results indicated that the endogenous electric fields generated penetrate much deeper into the cytosol and non-membrane regions than previously estimated. These measurements support the picture of an electrically complex environment inside the cell [87].

Ions are the transducers of information in the regulation of cell struc­ture. Modification in the interfacial structure of cell membrane alters its ionic composition and constitutes electrochemical information transfer. This alters biochemical and mechanical transport properties of the mem­brane that is interpreted by the cell as requiring a change in its function which could trigger specific enzyme activity [62,73]. Thousands of chemi­cal reactions are carried out simultaneously and successively in different cellular compartments and are closely coordinated and linked together. The importance of vibrational coherence in the form of electrical and me­chanical oscillations has been proven through the experiments [99]. It has been shown for instance that endogenous electric fields exhibiting coher­ent behavior can have a dominant effect on directed transport of molecules and electrons such that the probability to reach the target is enhanced in comparison with random thermal motion alone [97].

The algal cells can be gathered into a corporation or fixed to the carrier by immobilization technology. Immobilized algae have numerous benefits as follows: high cell density, excellent ability to resist poison, high re­moval efficiency, good stability, easy product separation, etc. At present, immobilization carriers include mainly natural macromolecular materials (such as agar, sodium alginate, etc.) and synthetic polymeric gels (such as polyvinyl alcohol, polyacrylamide, etc.). The natural polymers have no toxicity and good mass transfer property, but their intensity is low. How­ever, the synthetic organic polymer gels have high strength, but poor mass transfer property. Therefore, new immobilization carriers are expected to facilitate the development of algae immobilization technology.

High rate algal pond (HRAP) can achieve efficient removal of organic matter, heavy metals, nitrogen, phosphorus and other nutrients in waste­water by algae-bacteria symbiosis system. In the system, the microalgae provide oxygen and nutrition for bacteria; meanwhile bacteria provide use­ful growth-promoting substances for microalgae. Our team has developed a new type of microalgae immobilization carrier using the fungi [72]. The key of the technology is that fungi mediate pelletization of microalgae. After adding a certain number of fungal spores to the microalgae culture, algae-fungi symbiotic spheres formed accompanied by spore germination. The immobilized microalgae allow efficient recycling of livestock waste­water for algae cultivation and are easy to be harvested. In addition, the fungi can be converted to animal feed.

The German Advisory Council on Global Change (WBGU) performed a study on the conservation of the biosphere [17]. One of the conclusions of this work was that between 10 and 20 % of the world land mass should be protected to preserve the different functions of the biosphere, such as climate regulation, and its biodiversity.

Recent statistics provided by the World Database on Protected Areas state that 14% of the land mass is currently protected [18].

Therefore, to be at the upper limit of the range put forward by the WBGU, an additional 6% of the global land mass should be protected. Although it is not known where this 6% is located, we assume in our cal­culations that meeting this requirement will also reduce the land potential for rain-fed cultivation of energy crops by 6%. The reduction then totals

540,0 km2 (54 million hectares). This reduction is additional to the ex­clusion of currently protected land based on the IIASA study.

Based on the results of this study, targets can be set for producing algal bio­fuel that will enable a 2nd O EROI and PFROI equal to 1 (i. e., break-even) without exceeding water availability constraints or drastically increasing national fertilizer consumption. Since these targets are devised only with consideration of operating inputs, productivity would need to be increased and/or expenses would need to be decreased significantly to achieve an overall EROI and overall FROI (including capital costs) greater than 1 for the delivered energy carriers (a requirement for fuels to make a net ener­getic contribution), or greater than 3 (for practical purposes). The guiding targets for research stakeholders for comparison to the Experimental Case and the Highly Productive Case are:

1. Algal concentration of 3 g/L with a lipid fraction of 0.3, which would yield approximately 25 kJ of bio-oil and 25 kJ of methane per liter of processed volume (which is about 800 L BO/MLp and 450 kg methane/MLp, estimated to be roughly $600 of revenue per million liters of growth volume (assuming $0.66/L BO ($2.50/gal BO) and $3.8/GJ ($4/MMBtu) of methane));

2. In conjunction with item 1, an energy input for growth, processing, and refining that is less than 50 kJ per liter of processed volume enables a 2nd O EROI > 1 and requires using discounted inputs;

3. The FROI is dependent upon market prices, and therefore can vary substantially depending on market conditions (e. g., oil price). However, based on the price assumptions used in this study, if the targets listed above can be achieved, the PFROI would be greater than 1 if the cost of growth, processing, and refining is less than $600 per million liters of growth volume processed (which is equivalent to $0.20/kg of grown mass). Achieving a total cost less than $600 per million liters of growth volume processed would yield an overall FROI greater than 1 for this scenario (assuming no subsidy revenue);

4. A fresh water consumption intensity on the order of 2.4 L/km (1 gal/mi), achieved by consuming roughly 25 liters of fresh water per thousand liters of processed volume (which corresponds to no evaporation during growth, minimal processing water use, and greater than 97.5% recycling for fresh water cultivation). This con­sumption corresponds to about 33 liters of fresh water per liter of bio-oil produced (with a methane co-product of about 0.58 kg/L BO). Using saline water or waste water could also enable a low fresh water consumption intensity;

5. A net nutrient consumption that would enable large-scale produc­tion while only marginally increasing the national fertilizer con­sumption. For example, to produce 5 Bgal of fuel per year (19 GL/ yr), the net nitrogen consumption for each liter of fuel produced should be less than about 26 g to prevent a national increase in ni­trogen fertilizer consumption of more than 5% (which is about 6 x 108 kg N/yr [43]). In this scenario, one liter of bio-oil is produced from about 4 kg of algae, and therefore the nitrogen consumption should be less than about 7 g per kg of algae, which is roughly 10% of the minimum possible nitrogen requirement for algae (~70 g of nitrogen per kg of algae). Therefore, nitrogen recycling or utiliza­tion of waste nitrogen of 90% or more is required.

Since algae were eluted off the resin by 5% sulfuric acid in methanol, a reagent that catalyzes the transesterification of esterified fatty acid to FAMEs, tests were carried out to measure conversion of lipids in the elu — ate to FAME. To quantify FAME and other lipids, normal-phase HPLC was used in conjunction with an evaporative light scattering detector and mass spectrometry (HPLC-ELSD/MS;) [24]. The advantage here is that one can rapidly measure the amount of FAME generated, its fatty acid composition, and the amount of residual triacylglycerol starting material present in the reaction product as well as in crude total lipid extracts. In the reaction product, the presence of residual TAG is an indicator that the transesterification reaction did not reach completion. Preliminary tests carried out by extracting the sulfuric acid methanol eluate with hexane to obtain the products at various times after elution showed that 12 h at room temperature was sufficient to consume all the TAG. What remains in the extract are mainly saturated hydrocarbons, which have been characterized in more detail elsewhere [24], and FAME.

As a reference, algal lipids were converted to FAME by a two step pro­cedure that entailed treatment of dry algal pellets with base to hydrolyze fatty acid esters followed by re-esterification of free fatty acids in sulfuric acid and methanol [26]. The results showed 21.7%, 20.9%, and 35.2% of dry weights were recovered as FAME for healthy Neochloris, stressed Neochloris, and KAS 603 respectively [Figure 2(a)]. Acid-catalyzed trans­esterification of resin-bound algae resulted in 13.6%, 6.9%, and 37.6% of dry weight recovered as FAME for healthy Neochloris, stressed Neochloris, and KAS 603 respectively. For comparison, FAME synthesis yields are shown alongside total lipid extract amounts [Figure 2(a)]. Crude lipid ex­tract constituted 31.4% of total dry weight for healthy Neochloris, 35.4% for stressed Neochloris, and 41.3% for KAS 603. HPLC analysis of the crude lipid extract showed that TAG constituted 0.4%, 8.6%, and 11.7% of dry weight for healthy Neochloris, stressed Neochloris, and KAS 603, respectively.

For KAS 603 comparable yields of FAME were obtained using either method and the total FAME was close to the weight of total lipid. For

Neochloris, both methods generated substantially less FAME than total lipid and the resin-bound algae yielded only 60% of the FAME generated from the dried pellet. Clearly, substantially more FAME can be generated by direct transesterification than can be accounted for by TAG alone. For healthy Neochloris, there was hardly any TAG present in the extracts yet 15%-20% of the DCW could be recovered as FAME. For KAS 603, 10% of the DCW was present as TAG but nearly 40% of the DCW was recov­ered as FAME. These data suggest that much of the FAME is derived from polar lipids such as glycolipids and phospholipids.

One of the surprising results of this study is the finding that Neochloris accumulates high amounts of TAG when subjected to nitrogen depriva­tion [23], yet with only a modest increase in total lipid. While TAG in­creased nearly ten-fold, total lipid still constituted approximately 20% of dry weight, and FAME yield from dried biomass was comparable between healthy and stressed Neochloris. The most notable difference between FAME generated from healthy and stressed Neochloris was found in the fatty acid composition. This can be seen by analyzing positive mode APCI mass spectra of the various FAME reactions. Mass signatures were deter­mined based on the fragmentation behavior of FAME standards. Fatty acyl groups in FAME were identified and quantified by positive mode APCI — MS. Figures 2(b) and 2(c) indicate a trend towards a higher degree of fatty acid saturation with increased TAG content. For example, healthy Neochlo­ris, having little TAG content, yielded more C18:3 and C21:4 species and less C16:0, C18:0, and C20:0 than the other two algal groups. In contrast, stressed Neochloris and KAS 603, having a higher TAG content, yielded more C16:0, C18:0, and C20:0, and less C18:3 and C21:4 than healthy Neochloris. This shift in TAG fatty acid composition from unsaturated to saturated species with nitrogen starvation has been reported previously [21].

Biodiesel is the most common fuel type researched as a method of recov­ering energy from algae due to the high oil content of many algae strains [11, 13, 14]. The production of biodiesel initially requires the extraction of the lipid content of the algal cells. Most researchers follow a standard protocol written by Bligh and Dyer in 1959 [72] which uses chloroform and methanol as the extraction technique. Prior to lipid extraction the cells must be disrupted to allow access to the oils within the cell. Disruption can be achieved by homogenisation, bead beating, mechanical pressing, microwave treatment, acid/alkali treatment, sonication, lyophilisation and autoclaving among others.

Lee et al. [73] produced a study investigating the various methods of cell disruption and corresponding lipid extraction efficiencies. They found that for each algal strain (Botryococcus spp. Chlorella vulgaris and Scenedesmus spp.) microwave treatment provided the highest lipid yield. In terms of productive strains, Botryococcus spp. provided the highest yield using microwave treatment at 28.6% lipid recovery from the bio­mass. Bead-beating however, almost matched this value. Each of the dis­ruption methods (autoclaving, bead-beating, microwaving, sonication and osmotic shock) produced lipid yields higher than a no-disruption tech­nique.

The next step of the process is the lipid extraction and most studies extract the lipid content of the biomass using a modified version of Bligh and Dyer’s method [72]. This requires the addition of methanol and chlo­roform, typically in proportions of approximately 1:1 methanol to chloro­form mixed with the sample also at a ratio of about 1:1 methanol/chloro- form mixture to sample [73]. Once the reaction is complete the oil can be separated using a centrifuge or funnelling method as the densities of the materials differ. Methanol, chloroform and a catalyst (acid or base) are then mixed with oil to allow trans-esterification to occur. The two products from the reaction are methyl esters (biodiesel) and glycerol. The produces are biphasic and thus can be easily separated.

Research in the area is now looking at the possibility of improving extraction of oils from wet biomass which eliminates the energy consump­tion required for drying of the biomass. It is generally considered that removal of oil from dry biomass is most efficient and practical [74]. John­son and Wen [75] investigated the use of both wet and freeze-dried algal biomass (S. limacinum) for the production of biodiesel. The researchers found that wet biomass produced 20% less fatty acid methyl-esters than the dried biomass, lowering the biodiesel value. Further research has been conducted by Patil et al. [74] who conducted experiments producing fatty acid methyl-esters from wet biomass via a supercritical methanol method. The process required only one step for extraction and trans-esterification with addition of methanol at ratio of1:9, biomass to methanol respectively, a temperature of 255 °C and reaction time of 25 min. The results showed a Fatty Acid Methyl Ester (FAME) recovery of around 88% from Nanno — chloropsis biomass. The research suggests that high recovery is possible without the energy intensive process of drying and separate lipid extrac­tion. Similarly positive results of direct extraction from wet biomass were produced from Wahlen et al. [76] who experimented with direct biodiesel production from various freshwater green algae strains, cyanobacteria and mixed wild algae. More research is required to assess the potential of re­covering biodiesel from wet algae in a single stage process yet the concept appears promising. Energy costs of the process may be higher but this could well be outweighed by the reduced energy cost from drying of the biomass as was calculated by Lardon et al. [77] in their LCA of biodiesel from microalgae. This LCA study compared methods of cultivating and processing algal biomass for maximum energy recovery, they investigated the energy consumption associated with producing 1 kg of biodiesel. In their study they found that drying required 81.8 MJ of heat and 8.52 MJ of electricity per kg of biodiesel with no heating requirement for wet bio­mass. Oil extraction required higher energy consumption for wet biomass than dry but the final energy balance for wet biomass was a high positive value (105 MJ/kg biodiesel) compared to the negative balance for dry bio­mass (-2.6 MJ/kg biodiesel).