In open raceway ponds, microalgal biomass concentrations are typically about 0.5 g L-1. The N content of this biomass is about 7 % and the P content 1 %. As a result, the minimal nutrient concentration in the culture medium to achieve a biomass concentration of 0.5 g L-1 should be around 5 mg P L-1 and 35 mg N L-1. In photobioreactors, microalgal biomass concentrations are higher (up to tenfold), and a higher nutrient concentration is needed in the medium to achieve the maximal biomass concentration. If nutrient concentrations in the wastewater are lower, microalgal biomass will be nutrient-limited and the biomass concentration and productivity will be lower than can be achieved under optimal conditions. If the biomass concentration in the medium is too low, this may in turn result in higher harvesting costs.

Concentrations of N and P vary considerably between different types of wastewaters. Domestic wastewater contains about 15-40 mg N L-1 (Rahman et al. 2012; Peccia et al. 2013), which is perhaps just sufficient to achieve the maximal productivity of microalgae in raceway ponds (Olguin 2012), but too low for pho­tobioreactors. If wastewater with a lower concentration of N and P is used as a source of nutrients, the retention time of the microalgae in the system can be increased relative to that of the nutrients. This can be achieved in several ways. One option is to grow microalgae on a fixed support rather than suspended in the culture medium (Hoffmann 1998; Mulbry et al. 2008; Zamalloa et al. 2013; Boelee et al. 2013; Kesaano and Sims 2014). The fixed microalgae can be unicellular or fila­mentous species and can be grown on a variety of supports. Another option, as summarized in Chap. 2, is to immobilize suspended microalgae in alginate beads or alginate mats (e. g., Mallick 2002; Ruiz-Marin et al. 2010; Eroglu et al. 2012). However, it may be difficult to separate the microalgae from the alginate and use the biomass. Also, membrane photobioreactors can be used that retain microalgae in the photobioreactors but allow a high throughput of wastewater (Bilad et al. 2014). Wastewater derived from animal manure or industrial effluents are often high- strength wastewaters and can contain up to several grams of N L-1. When nutrient concentrations are higher than the requirements for microalgal production, the microalgae will be light-limited due to self-shading before all nutrients are con­sumed (Huisman et al. 2002). Wastewater with high “N” and “P” concentration can be diluted with water to match the nutrient supply with the productivity of the microalgae, yet the use of pure water to dilute wastewater is unsustainable (Mar — cilhac et al. 2014). Concentrated wastewaters can be diluted with seawater to produce a growth medium for marine microalgae (e. g., Craggs et al. 1995; Zhang and Hu 2008; Jiang et al. 2011). Alternatively, low nutrient domestic wastewater could be used to dilute concentrated wastewater. If this is not possible, the culture medium may be repeatedly recycled until all nutrients have been consumed by the microalgae. Few studies, however, have attempted this to date.

The ability to make specific changes to DNA, such as changing, inserting or deleting sequences that encode proteins, enables researchers to engineer cells, tis­sues and organisms for practical applications. Clustered regularly interspaced short palindromic repeats (CRISPR), a bacterial adaptive immune system effector, has been shown to facilitate RNA-guided site-specific DNA cleavage in bacteria, suggesting a simple alternative strategy for genome engineering (Sorek et al. 2013). The CRISPRs are a diverse family of DNA repeats that all share a common architecture. Each CRISPR locus consists of a series of short repeat sequences (typically 20-50 bp long) separated by unique spacer sequences of a similar length. The CRISPR/Cas systems are phylogenetically and functionally diverse, but each of these systems relies on three common steps: new sequence integration, CRISPR RNA biogenesis, and crRNA-guided target interference (Fig. 8.2c).

The CRISPR/Cas system allows targeted cleavage of genomic DNA guided by a customizable small noncoding RNA, resulting in gene modifications by both non­homologous end joining (NHEJ) and homology-directed repair (HDR) mechanisms. CRISPRs are unevenly distributed between Bacteria and Archaea. Currently, CRISPR loci have been identified in 90 % of the archaeal genomes and 50 % of the bacterial genomes (Sorek et al. 2013). CRISPR-Cas systems have emerged as potent new tools for targeted gene knockout in bacteria, yeast, fruit fly, zebrafish, human cells and plants (Belhaj et al. 2013; Gaj et al. 2013). In August 2012, Jinek et al. (2012) showed that a synthetic RNA chimera (single guide RNA, or sgRNA) created by fusing crRNA with tracrRNA is functional to a similar level as the crRNA and tracrRNA complex. As a result, the number of components in the CRISPR/Cas system was brought down to two, Cas9 and sgRNA (Jinek et al. 2012). For appli­cations in eukaryotic organisms, codon optimized versions of Cas9, which is orig­inally from the bacterium Streptococcus pyogenes, have been used. Four of the studies on the application of the CRISPR/Cas technology in plants used a plant codon-optimized version of Cas9, as using the previously described human codon — optimized version was not highly effective (Belhaj et al. 2013; Jiang et al. 2013).

All tested versions of Cas9 appear to work in plants with very high rates. Transgenic plants, generated using the CRISPR/Cas system, have been reported (up to 89 % for Arabidopsis and up to 92 % for rice) with bi-allelic mutation being recovered in the case of both plant species (Jiang et al. 2013). The discussed studies indicate the possibility of introducing functional CRISPR/Cas system in algae to target any sequence of choice, thus offering new opportunity for implementation in algal biotechnology for biomass production.

Together, these technologies promise to expand our ability to explore and alter any genome and constitute a new and promising paradigm to develop new synthetic biology tools for algal biofuels optimization.

11.3.1 Strategies for GM Microalgae Relevant to Biocrude Production

The potential benefits of GM in microalgae mass cultivation systems for the pro­duction of biocrude can be broadly divided into seven strategies:

1. To increase the net photosynthetic productivity of mass cultures

2. To increase nutrient assimilation capacity

3. To modify bulk energy and carbon flows (e. g. rerouting energy flows into lipids)

4. To enhance the alga’s capacity to remain dominant in contaminated cultures (e. g. resistance to predators, pathogens)

5. To enhance the harvestability and processability of the algae biomass (biology of flocculation)

6. To improve economic viability through the manufacture of high-value products and services (HVP&S—e. g. recombinant vaccines or industrially useful prop­erties such as the ability to digest cellulose)

7. To develop enabling technologies for biotechnology (e. g. export systems for proteins, lipids, or other products; internal signalling or reporter systems and switchable effectors, for example to stop and start growth, trigger programmed cell death or dissemble the cell wall upon demand).

Flotation is a method where air bubbles and algal particles are attracted to each other and the air bubble buoyancy moves the algae to the surface where it can be collected. Flotation methods can capture particles that are less than 550 qm, making these methods particularly suitable for unicellular microalgae. There are a number of different methods applied for harvesting by flotation: DAF, dispersed flotation, electrolytic flotation, and ozone flotation.

14.2.4.1 Dissolved Air Flotation (DAF)

DAF depends on the addition of coagulants or flocculants, but the harvesting is sped up by using fine bubbles moving up from the bottom of the DAF unit to capture small aggregates and bring them to the surface of the tank. At the tank surface, froth containing the cells is skimmed off and collected in a much more concentrated solution—100-fold increase in solids (Milledge and Heaven 2013). DAF is a well-developed method and has already been scaled to volumes that would be used for commercial algal biofuel production. However, DAF suffers from the need to add chemicals to the process that need to be dealt with in downstream processing and thus adds OpEx to the overall operation (Chen et al.

2011) .

A comparison of DAF coupled with filtration to direct filtration (with or without ozonation) for removal of algae in wastewater showed that the DAF/filtration system allowed more rapid flow through and longer runs than were possible using direct filtration (Ferguson et al. 1995).

14.2.4.2 Dispersed Flotation

In dispersed flotation, 700- to 1500-pm bubbles are formed by high-speed mechanical agitator with air injection system. Additions of surfactants such as the cationic N-cetyl-N-N-N-trimethylammonium bromide (CTAB) have been used to remove Scenedesmus quadricauda, while non-ionic Triton X-100 and anionic SDS did not work (Chen et al. 2011).

A cursory examination of literature or commercial websites related to biofuel production from microalgae makes it clear that there are almost as many different ways of growing and processing microalgae for the purpose of producing fuel as there are species of microalgae. Figure 17.1 provides a block flow diagram of the typical process for converting microalgae into biofuel.

The numerous process variations arise from different technologies applied at each of the unit operations listed below:

1. Growth

2. Harvesting

3. Dewatering

4. Extraction

5. Conversion

In some cases, harvesting and dewatering are combined as one step or extraction and conversion can occur simultaneously. An overview of the various technologies proposed for this is provided in Table 17.1.

Biosensor research often focuses on the application of enzyme sensors for the detection of toxic chemicals (Dennison and Turner 1995; Shul’ga et al. 1994). Due to the drawbacks of this technology, such as enzyme stability, cost of the process, and difficulty to prepare multienzymatic biosensors, immobilized cells have been proposed as an alternative biosensor technology. Using the entire cells has the advantage of involving various enzymes at the same time, which allows estab­lishing information about the toxicological effects of different pollutants directly on the selected organisms. Immobilized cells had more stable metabolic activities than free cells during the long testing periods (Lukavsky et al. 1986) and also higher resistivity to turbid/colored effluents (Bozeman et al. 1989).

The generation or consumption of charged chemicals during bioreactions results in a significant change in the ionic composition of the test sample that can be detected by conductometric biosensors. For this reason, Chouteau et al. (2004) investigated the development of conductometric biosensors using immobilized C. vulgaris cells for alkaline phosphatase analysis and cadmium ion detection. C. vulgaris cells were immobilized inside bovine serum albumin membranes that were cross-linked with glutaraldehyde vapors.

Frense et al. (1998) used immobilized Scenesdesmus subspicatus algal cells as optical biosensors for the determination of the herbicide content in wastewater samples. The algal cells were initially immobilized on a filter paper, which was then covered by alginate and then cross-linked with CaCl2 solution. They used a fiber optics-based electronic device for measuring the chlorophyll fluorescence of algal cells as a response to the presence or absence of the toxic substances in the liquid sample.

C. vulgaris cells immobilized in a membrane of oxygen electrode has been used as a biosensor for the detection of perchloroethylene aerosols by monitoring the pho­tosynthetic activity of the microalgae through oxygen production (Naessens and Tran-Minh 1999). Shitanda et al. (2005) also immobilized alginate-entrapped C. vulgaris cells on the surface of an indium tin oxide electrode, for the monitoring toxic compounds such as atrazine, toluene, benzene, and 3-(3,4-dichlorophenyl)-1, 1-diethylurea (DCMU).

Immobilized algal cells of S. capricornutum in alginate beads were used for the toxicity testing of various chemicals, such as cadmium ions, copper ions, penta- chlorophenol, sodium dodecyl sulfate, and herbicides (glyphosate, hydrothol, paraquat) (Bozeman et al. 1989). In subsequent studies, alginate-immobilized S. capricornutum cells were also successively used for the toxicity testing of various pesticides, herbicides, and fungicide (Abdel-Hamid 1996; Van Donk et al. 1992). The immobilization process reduced the toxic effect of these tested chemicals on the algal cells compared to their free-cell equivalents.

Key parameters determining the economic feasibility of algae biofuels include biomass productivity, lipid content, and lipid productivity. Microalgae produce a variety of lipids, tri — and diglycerides, phospholipids, glycolipids, alkenes, and pigments such as the carotenoids. Reports of total lipid content for specific strains (i. e., compounds soluble in organic solvents per dry weight, as originally described by Bligh and Dyer 1959) vary in the literature (Griffiths and Harrison 2009). This is due, in part, to variations in the sequence and polarity of solvent systems used for extraction (Guckert et al. 1988). Because of the complexity of lipid compounds in algae and that the fractions of each class can vary with environmental conditions, lipid quantification, which is essential to the development of production models for algae biofuels, needs refinement. The biodiesel industry is currently based on transesterification of plant triglycerides forming alkyl esters of the fatty acid moiety. The fate of other cellular lipid compounds in the tranesterification process, potentially a large fraction of lipoidal extracts, will require more attention.

Perhaps a more important consideration of reported variations in lipid content, even within a specific species, is the physiological responses in lipid metabolism due to culture conditions including temperature, salinity, growth phase, nutrient deprivation, and the diurnal light cycle, all of which have a strong influence on lipid content (Roessler 1988, 1990). Unfortunately, biomass productivity is often inversely correlated with overall lipid productivity. High lipid and carotenoid content is usually produced under stress conditions, especially nutrient limitation which prevents cell growth and division resulting in excess photosynthate shunted toward triglyceride accumulation (Griffiths and Harrison 2009; Illman et al. 2000; Jakobsen et al. 2008; Lv et al. 2010; Rodolfi et al. 2009).

Lipid productivity is the product of lipid content and productivity. A survey of the literature on growth rates and lipid content under nutrient-replete and nutrient — deficient conditions showed a stronger correlation between biomass and lipid productivity rather than simply lipid content (Griffiths and Harrison 2009). In continuous ponding operations, selection of fast-growing strains increases yield and decreases the cost of harvesting and extraction (Borowitzka 1997) and reduces competition by invading strains. High productivity is also advantageous in a two — stage process, as described above, with the first stage designed to optimize biomass production and nutrient removal from wastewater followed by a second phase to induce hyper-lipid production.

In order to increase productivity of biomass or a desired product, target genes have been selected and manipulated with success using transgenic approaches. These genes may comprise the metabolic pathways under consideration or be part of unrelated pathways that indirectly contribute to higher productivity. Highlighted below are some notable examples of target genes used for genetic manipulation along with examples of potential targets yet to be explored.

Much work has been done to genetically manipulate plants to produce more biomass or more of a specific tissue or compound. The Viridiplantae (green plants) include land plants and two lineages of algae, the chlorophytes and the charophytes (Finet et al. 2010). We therefore can look at gene targets in plants for possible research avenues when considering algae. A number of gene targets have already been picked and utilized with great success from previous knowledge of metabolic pathways. Fruit yield was increased in tomato (Solanum lycopersicum L.) when RNAi was used to decrease ascorbate oxidase activity (Garchery et al. 2013). Basically, the stress response to water or environment was down-regulated thus allowing more energy to be allocated for fruit production even in unfavorable conditions. Likewise, stress response genes in algae, such as those involved in oxidative stress (Perez-Martin et al. 2014) and light-related stress (Kukuczka et al.

2014) , might be down-regulated to allow for more energy to be allocated to biomass production. One strategy to increase biomass is to manipulate photosynthetic light capture. Internal shading is a limiting factor in biomass production in algae, so reducing the size of the light-harvesting antennae may increase biomass production. However, pigment mutants of Cyclotella sp., a diatom, failed to outperform their wild-type counterparts in biomass productivity (Huesemann et al. 2009). The authors note that the mutagenesis procedures (chemical and UV) may have affected other metabolic processes that contributed to the Cyclotella sp.’s unremarkable growth and found no difference in growth of wild and mutated strains of this alga when grown parallel in raceway ponds. Green algae (e. g., C. reinhardtii) have evolved genetic strategies to assemble large light-harvesting antenna complexes (LHC) to maximize light capture under low-light conditions, with the downside that under high solar irradiance, most of the absorbed photons are wasted as fluores­cence and heat generated by photoprotective mechanisms.

An insertional mutant was obtained with a disrupted gene for the antennae protein TLA1 (Polle et al. 2003). Biochemical analyses showed the TLA1 strain to be chlorophyll deficient, with a functional chlorophyll antenna size of photosystem I and II being about 50 and 65 % of that of the wild type, respectively. The TLA1 strain showed greater solar conversion efficiencies and a higher photosynthetic productivity than the wild type under mass culture conditions (Polle et al. 2003). Other researchers have used RNAi to knock down the entire family of LHCs (Mussgnug et al. 2007). The resultant mutant, Stm3LR3, exhibited reduced levels of fluorescence, a higher photosynthetic quantum yield and a reduced sensitivity to photoinhibition. Cultures with these mutants have higher light penetrance, which may lead to more efficient biomass production. Another strategy to increase bio­mass production is to focus on increasing the rate at which the alga assimilates CO2 from the atmosphere or through supplied gas, or to increase the efficiency of the carbon capture mechanism (CCM) (Stephenson et al. 2011). Genes that are involved in the CCM and are possible targets for genetic manipulation include an ABC transporter (Hla3/Mrp1 Cre02.g097800), two low-CO2-inducible chloroplast envelope proteins (Ccp1 Cre04.g223300), an anion transporter (LciA/Nar1.2 Cre06.g309000), and ten different carbonic anhydrases (Winck et al. 2013). When the desired outcome is increased production of a specific product, increased bio­mass yield may or may not be desirable. For example, in engineering algal cells to increase lipid yield, biomass productivity is only important so far as it increases total lipid yield. A variety of genes have been manipulated with this aim with varying degrees of success (Stephenson et al. 2011). One of the most remarkable achievements in lipid production from Chlamydomonas occurred when researchers showed that Chlamydomonas deprived of a nitrogen source accumulates a high degree of lipids (Wang et al. 2009b). This effect is much more pronounced in mutants lacking the small subunit of a heterotetrameric ADP-glucose pyrophos — phorylase (Zabawinski et al. 2001). The normal response of Chlamydomonas under nitrogen deprivation is to accumulate starch; however, the mutants, unable to accumulate starch, instead store energy as lipids (Wang et al. 2009b).

A recent study showed a 12 % increase in the total lipid content of the micro­algae D. salina by transforming it with a bioengineered plasmid comprising specific parts, genes, and inducible promoters, driving the cellular carbon flux into the fatty acid biosynthesis pathway (Talebi et al. 2014).

In addition to lipid production, hydrogen production is also seen as a possible route to biofuel production in Chlamydomonas (Lehr et al. 2012). Increasing hydrogen production does not necessarily follow an increase in biomass; instead, researchers usually aim to increase photosynthetic efficiency or force the cells to more readily assume an anaerobic state.

RNAi knockdown of light-harvesting proteins was found to increase H2 pro­duction in the high-H2-producing C. reinhardtii mutant Stm6Glc4 (Oey et al. 2013). Oey et al. (2013) also stated that the overall improved photon-to-H2 conversion efficiency is due to (1) reduced loss of absorbed energy by non-photochemical quenching (fluorescence and heat losses) near the photobioreactor surface, (2) improved light distribution in the reactor, (3) reduced photoinhibition, (4) early onset of HYDA expression, and (5) reduction of O2-induced inhibition of HYDA (Oey et al. 2013). Rubisco has also been used as a target for genetic manipulation to increase hydrogen production. The Rubisco mutant Y67A accounted for 10- to 15­fold higher hydrogen production than the wild type under the same conditions (Pinto et al. 2013). In conclusion, a variety of gene targets are available in algae that when manipulated may increase biomass and biofuel productivity.

Polymer flocculants cause flocculation by bridging, or by the electrostatic patch mechanism. For bridging flocculation to occur, the polymers should be sufficiently long to be able to form bridges between individual cells. The length of the polymer chains can be significantly reduced by coiling of the polymer chains. Coiling is more prevalent in high-conductivity medium. Therefore, polymer flocculants are often less effective for harvesting marine microalgae (Bilanovic et al. 1988). Polymer flocculants are attractive because they generally require low flocculant doses and produce large and stable flocs (Granados et al. 2012). In wastewater treatment, synthetic polymers based on polyacrylamide are widely used. Because polyacrylamide contains potentially toxic acrylamide residues, contamination of the harvested biomass is an issue. Therefore, flocculants based on biopolymers are preferred over synthetic polymers. These biopolymers should be positively charged in order to allow interaction with the negatively charged microalgal cell surface. Positively charged biopolymers, however, are relatively rare in nature. Examples of natural positively charged natural flocculants are poly-y-glutamic acid, a polymer produced by Bacillus subtilis (Zheng et al. 2012), and flour from the seeds of the

Moringa oleifera tree (Teixeira et al. 2012). Some studies suggest that uncharged natural polymers such as starch may also be capable of inducing flocculation in microalgae (Rakesh et al. 2013). Uncharged natural biopolymers may be modified with cationic functional groups to improve flocculation efficiency. A well-known example is chitosan, which is prepared from chitin by de-acetylation of the acet — ylamine groups, leaving amine groups that are protonated, and thus positively charged at low pH. Chitosan is an effective flocculant for microalgae but is only effective at low pH (Morales et al. 1985; Lubian 1989; Rashid et al. 2013). Starch that is modified by addition of quaternary ammonium groups is also an effective flocculant and can be used as an alternative for chitosan (Vandamme et al. 2010; Gerde et al. 2014). Moreover, the positive charges of the quaternary ammonium groups of cationic starch are less sensitive to pH, allowing the starch to operate over a broader pH range than chitosan. Other biopolymers that have been cationically modified for microalgae harvesting include guar gum (Baneijee et al. 2013) and cassia gum (Banerjee et al. 2014).

David Parlevliet and Navid R. Moheimani

Abstract Chemical energy can be produced from solar energy via photosynthesis. Solar energy can also be converted into electricity via photovoltaic devices. These two mechanisms would seem to compete for the same resources. However, due to differences in the spectral requirements, there is an opportunity to coproduce both electricity and chemical energy from a single facility. We propose to introduce an active filter or solar panel above a microalgae pond to generate both electricity and chemical energy. There are several advantages to such technology including reduced heating (saving freshwater) and an independent electricity supply. Additionally, by channeling targeted illumination back into the microalgae ponds, we can double the amount of light absorbed by the microalgae. This can result in increased biomass productivity.

15.1 Introduction

There is no doubt that available fossil fuel resources are depleting. Despite new reserves of some fossil fuels, the current reserves of oil, coal, and gas will last 40, 200, and 70 years, respectively (Shafiee and Topal 2009). There is also the issue of human-induced climate change. These situations have resulted in increasing worldwide interest in the renewable energy sector. Apart from fuel, there is also an urgent need for sustainable food production for the ever growing human population.

One of these alternative and renewable energy supplies is that of photovoltaic modules (solar panels). These are solid-state devices that directly convert solar

D. Parlevliet (H)

School of Engineering and Information Technology, Murdoch University, Murdoch, WA 6150, Australia e-mail: d. parlevliet@murdoch. edu. au

N. R. Moheimani

Algae R&D Centre School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA 6150, Australia

© Springer International Publishing Switzerland 2015

N. R. Moheimani et al. (eds.), Biomass and Biofuels from Microalgae,

Biofuel and Biorefinery Technologies 2, DOI 10.1007/978-3-319-16640-7_15 energy into electricity. Photovoltaics have been used widely for many decades to convert sunlight to electricity (Wenham et al. 1994) and are a well-established technology despite faults that appear in some modules (Djordjevic et al. 2014). Photovoltaic devices take incident illumination and through the use of a charge separating junction can supply electrons to an external circuit. Although in their initial uses they were for specialized projects such as the space program and for remote area power supplies, there is an increasing demand for terrestrial and domestic systems. Solar panels are becoming a common sight on rooftops in suburban areas.

Biofuel (biodiesel and bioethanol) has been used widely as an alternative source of chemical energy (de Boer et al. 2012). It is projected that the global annual production of bioethanol and biodiesel will increase from 113 x 109 and 28 x 109 L in 2012 to 167 x 109 and 40 x 109 L in 2022, respectively (OECD/FAO 2012). There is no doubt that renewable transport fuel production using crops such as oilseeds or sugarcane has economic as well as ethical problems. This is mainly due to the competition for limited resources (freshwater and nutrients) with food crops. Therefore, there is a need for an alternative source of raw material for biofuel production.

These two energy production methods, one for chemical and the other for electrical, seem to compete for the same resource. They both require illumination from the sun to drive their different processes. However, photosynthesis and the production of biomass are largely reliant on the blue and red end of the solar spectrum, whereas photovoltaics are highly efficient in the green part of the spec­trum. These differences in spectral requirements are discussed later in this chapter and can be seen in Figs. 15.2 and 15.3. This suggests that if there was a mechanism for splitting the solar spectrum between these applications, it would be possible to convert the entire solar spectrum to electricity and chemical energy.

We have previously described the scenario of placing an active filter or solar panel above an microalgae pond (Moheimani and Parlevliet 2013; Parlevliet and Moheimani 2014). We produced a conceptual framework and model that described the total amount of power provided to a microalgae culture and the subsequent electrical generation from the solar cells. In this work, we have further developed the model to examine the amount of power absorbed by the microalgae, this taking into account the varying absorption spectra of different microalgae. This work provides a more detailed description of the model and the expected increases in illumination that can be provided to the microalgae.