The need for agricultural cropland to meet future food demand is a highly debated issue. We took a pragmatic approach to assess whether or not the current agricultural cropland is able to sustain future food demand growth. The premise of our approach was the assumption that, in 2005, food sup­ply equalled food demand; both were indexed at 100%. For this analysis, we did not analyse current or future food distribution patterns that might lead to local food shortages. We only assumed that there is no shortage of food production at the global level for which we would need to set aside additional land and that there is no overuse of cropland at the global level which could be taken out of food production without affecting supply.

We forecast the evolution of food demand and supply to 2050 as fol­lows:

We extrapolated the growth in food demand using the following step­wise approach:

1. We started with current per capita calorie values of ~ 10 MJ caput-1 (~2400 kilocalories caput-1) of plant product [20] and 1.46 MJ ca­put-1 (350 kilocalories caput-1) and 3.97 MJ caput-1 (950 kilocalo­ries caput-1) animal product in non-OECD and OECD regions [21], respectively. Animal product calories were converted into crop equivalents with conversion factors based on the crop feed intake necessary to produce them. The basis for these factors were feed intakes of ~17 kg kg-1, ~2.4 kg kg-1 and ~1.7 kg kg-1 of feed per produced amount of meat, eggs and dairy respectively. For meat, this factor was derived from literature values for feed efficiencies per animal type [2] and current distribution of consumption of meat per animal type [22], which is a mixed diet of bovine, ovine, pig and poultry products. For eggs, literature values from [23] were used. For dairy, literature values from [2], [24] and [25] were used. The feed is assumed to have an energy content of19 MJ kg-1 of dry matter [2].

2. We calculated a “business-as-usual” (BAU) per capita diet in the period 2005-2050 differentiated between OECD and non-OECD countries. This was done based on existing diet projections [22].

3. We then assumed that total animal product consumption worldwide will be constrained to a growth of no more than ~65% between 2005 and 2050, which means that the average animal product con­sumption per capita (in crop equivalents) increases by about 10% over the same timeframe, given population projections. In prac­tice, it could be desirable to divide the global 10% increase across regions in a non-equal manner, e. g. a reduction in animal product consumption in OECD countries and a significant increase in non- OECD countries.

4. We then multiplied the constrained per capita diets with population growth numbers used in [1] to get a total growth in food demand in crop equivalents. This was indexed against 2005.

We extrapolated the growth in food supplied by the current agricultural cropland by using a yield increase of 1% per year. This value is an inter­mediate value in a range of yield increase projections of 0.4-1.5 % found in literature ([7], [8], [22], [26] and [27]). The impact of climate change on yield projections was not explicitly considered in this analysis. However, by choosing the intermediate value of yield increase projections we have tried to be moderate in our assumptions. This yield increase was applied to the indexed value in 2005 of 100%.

The results for the extrapolated food demand and food supply are pre­sented in Fig. 4. For reference, Fig. 4 also contains the indexed yield de­velopment of coarse grains over the last 50 years, which has been higher than the 1% assumed in this work.

From the graph in Fig. 4 it can be observed that, based on our assump­tions the current agricultural cropland is projected to be able to supply the entire food demand in 2050. However, in intermediate years this is not

always the case. We have calculated that the maximum shortage of food from current agricultural cropland occurs in 2035 and amounts to about 4% of current agricultural cropland. This totals 630,000 km2 (63 million hect­ares).

Although the identified 630,000 km2 (63 million hectares) is the largest amount of additional land needed for meeting food demand in any given year to 2050, we choose to exclude it from the potential over the entire pe­riod in our analysis. This reduction is additional to the exclusion of current agricultural cropland based on IIASA data.

RYAN W. HUNT, ANDREY ZAVALIN, ASHISH BHATNAGAR, SENTHIL CHINNASAMY, and KESHAV C. DAS

6.1 INTRODUCTION

Electromagnetic fields are capable of eliciting in vivo and in vitro effects in many biological systems [1]. Increasing attention is being directed to­wards bioelectromagnetic stimulation of living cultures for biotechnology and bioenergy applications using the low frequency electromagnetic fields (EMF). A number of bioprocesses could be successfully integrated with electromagnetic or electrochemical stimulation if the cultivation condi­tions are properly engineered using specialized reactors viz. electrolytic bioreactors, electro-bioreactors and bioelectro-reactors [2]. Most recently, a strong initiative in bioenergy research has been taken up to investigate methods for enhancing productivity and metabolic processes for biomass production and biorefining of biomass for production of biofuels, energy and other added value products. Currently, microalgae are considered to be the most promising candidates for biomass production because of their ability to grow fast, produce large quantities of lipids, carbohydrates and proteins, thrive in poor quality waters, sequester and recycle carbon di­oxide from industrial flue gases and remove pollutants from industrial, agricultural and municipal wastewaters. Microalgae are novel feedstocks

for renewable biomass production that is capable of meeting the global de­mand for transportation fuels because the oil productivity of many strains of microalgae greatly exceeds that of the most productive oil crops such as oil palms and soybean [3]. Although biomass production may be most effectively performed by large-scale algae cultivation, yeast and bacteria are the most common groups of organisms used in bioprocessing and con­version technologies like fermentation, composting, anaerobic digestion and bioremediation. Considering the current importance of waste manage­ment and recycling in conserving natural resources, bioenergetic stimula­tion technologies may be used as a potential tool for bioremediation by stimulating the uptake rates of various polluting components found in the waste streams by microbes.

Extensive studies have been conducted over both eukaryotic (algae, yeasts and molds) and prokaryotic microorganisms using various elec­tromagnetic regimes. The biological effects have been found to depend on field strength, frequency, pulse shape, type of modulation, magnetic intensity, and length of exposure [4]. Some results have been difficult to replicate due to various hidden parameters typically not monitored, such as local intensity and orientation of Earth’s geomagnetic field, cosmic ra­diations, solar winds and sunspot events.

Electromagnetism may affect organisms in both negative and positive manner which includes acceleration of growth and metabolism. This paper however focuses on the facilitative effects of electromagnetism on various microorganisms. The research attempts in this area can be divided into several groups based on implemented EMF parameters. Simplest initial classification can be based on time behavior of EMF and relative represen­tation of the electric and magnetic components of the field. As it follows from the recent research results, a spatial configuration and topology of the EMF may also have significant impact on processes in living cultures. This paper also summarizes our own data regarding the effects of mul­tipolar electromagnetic influences on biological systems and the future potential biostimulation techniques for improving microalgae biomass and lipid productivity for producing biofuels.

The results from Figure 1 showed that the sulfuric acid/methanol trans­esterification reagent could be reused multiple times for eluting algae from resin. We next tested whether recycling the sulfuric acid/methanol reagent led to a progressive decrease in FAME synthesis in comparison to fresh sulfuric acid/methanol [Figure 3(a)]. For the recycled sulfuric acid/ methanol solution, each eluate was extracted with hexane and analyzed for FAME content before it was reused. The results showed that both fresh and recycled sulfuric acid/methanol solutions gave comparable amounts of FAME during four successive cycles of algal loading and elution.

Reuse of the sulfuric acid/methanol solution would minimize chemical costs, and removal of the FAME with each cycle should promote product formation. Hexane extraction of FAME is a relatively cumbersome and time consuming process leading us to explore a simple hydrophobic resin-based method to collect the FAME generated during each cycle. For comparison, the sulfuric acid/methanol eluate was either directly extracted with hexane or passed over a hydrophobic ethylene glycol dimethacylate:hexyl meth­acrylate (EGDMA:HMA) resin [Figure 3(b)] which was then eluted with hexane in a separate recovery step. The results show that FAME recovery from the resin (11.0% of DCW) was comparable to that obtained by direct hexane extraction [11.8% of DCW; Figure 3(c)]. While the hydrophobic column was effective at collecting FAME on the lab bench scale, we sus­pect that other methods, such as a hollow fiber membrane extractor [28] would be more useful commercially.

A simpler method of energy recovery may be facilitated by anaerobic di­gestion of algal biomass providing a promising source of bio-energy in the form of biogas. The process was considered a potential source of useful energy recovery from algal cultivation near the start of modern research [2]. Anaerobic digestion is a process that has been used for hundreds of years to provide a source of energy from low value organic matter with minor energetic inputs. In the case of algal biomass, all the carbohydrates, proteins and fats can be converted into methane and carbon dioxide, al­though some components provide greater methane yields than others. It follows therefore that there is slightly less necessity to cultivate particular strains of algae for increased yields.

Table 6, taken from a study by Sialve et al. [85], displays the methane potential of each biomass component. Research has been conducted inves­tigating the potential of various strains of algal biomass and Sialve et al. [85] used the methane potential to calculate yields for a number of strains. Their results can be viewed in Table 7 which compares theoretical results with experimental results from literature. Table 7 suggests that the values of methane yield can vary between species due to compositional make-up and that the yield depends very much upon the growth conditions as this can have a great impact upon the composition of the biomass. Comparing the actual yields with the theoretical yields shows a realistic conversion efficiency loss of about 50% in the majority of cases.

It is important therefore that in further studies investigating potential yields, exaggerated or over-optimistic yields are not used as these may not reflect real performance.

As opposed to direct conversion, anaerobic digestion can alternatively be used to recover energy from the waste biomass following extraction of the more valuable components from the biomass cells. In their life-cycle assessment, Lardon et al. [77] calculated that the only feasible way of pro­ducing a positive energy balance of algal biodiesel was to recover further energy using anaerobic digestion of the residual waste. In fact, in normal culture conditions, they found that the energy produced from anaerobic digestion would be greater than that from extracted biodiesel. In their in­vestigation of biogas from algae, Sialve et al. [85] suggest that at lipid contents below 40% it is unlikely to be worth recovering the lipids using current methods and the biomass should simply be digested to recover the maximum energy yield. In their LCA study of algae digestion Collet et al. [86] found the environmental impacts of biogas from algae to be poor in comparison to algal biodiesel using results from the study conducted previously by Lardon et al. [77]. The study compared the results for 1MJ of energy produced in a combustion engine. The difference in impacts was mainly due to electricity consumption and assuming anaerobic di­gestion is also applied following the biodiesel extraction in the biodiesel scenario. The figures used in the mentioned study provided high values of energy consumption which contrast with those used in other studies [87], the impacts may therefore not be as adverse as suggested. Collet et al. [86] concluded that the impacts can be improved with reduced energy consumption and a combined process of lipid extraction and anaerobic digestion may provide the optimal solution.

The biogas produced through anaerobic digestion differs from bio­diesel and bio-ethanol in that it is not a fuel that can be used directly for combustion in vehicle engines. There are two options for biogas, one is combustion within a co-generator to produce electricity with possible heat recovery. The alternative is to refine the biogas removing the CO2 and the methane can then be used as a fuel within a gas engine [90]. Fur­ther energy is required to upgrade the gas to a useable transport fuel and this is often ignored in studies with the energetic content of the gas is only considered. Further research is necessary to investigate the impact of downstream processing if comparison to the alternative biofuel types as a transport fuel is desired.

Anaerobic digestion is one of the methods of recovering energy that seems to provide a positive net energy balance due to the low inputs re­quired [77]. The results may however be optimistic as real yields are much

TABLE 7: Theoretical and actual methane from different algal species. Algae Species Proteins (%) Lipids (%) Carbohydrates(%) CH, (L/g VS) (Theoretical) [85] CH4 (L/g VS) (Experimental) Refs. Euglena gracilis 39-61 14-20 14-18 0.52-0.8 — [85] Chlamydomonas reinhardtii 48 21 17 0.69 0.59 [88] C Morelia pyrenoidosa 57 2 26 0.8 0.17-0.32 (CMorella — Scenedesmus) [2] CMorella vulgaris 51-58 14-22 12-17 0.63-0.79 0.24 [89] Dunaliella salina 57 6 32 0.68-0.74 0.44-0.45 (.Dunaliella) [85] Spirulina maxima 60-71 6-7 13-16 0.63-0.74 0.31-0.32 (jSpirulina) [85] Spirulina platensis 46-63 4-9 8-14 0.47-0.69 0.31-0.32 (jSpirulina) [85] Scenedesmus obliquus 50-56 12-14 10-17 0.59-0.69 0.17-0.32 (CMorella — Scenedesmus) [2]

lower than theoretical calculated yields. Additionally the biogas may re­quire further processing to be useful as a fuel and this will affect the en­ergy consumption and environmental impacts. Nevertheless the process is capable of recovering energy from all strains of algae regardless of the composition and therefore can be very useful as part of a flexible approach.

2.3 LIMITATIONS

Despite having been researched for over 50 years now, there are still only a few companies that are growing algae for fuel on a large or commercial scale. The economics of producing algae for fuel do not currently justify the intensity of the numerous processing stages and current practicalities. Cultivating algae with high productivity year round is a challenging task unless grown in controlled conditions, however, this itself, is not a vi­able solution. Attempts have been made to cultivate pure strains of algae in environmental conditions but with little success. In most cases local strains of algae come to dominate, out-competing the selected strain. This section reviews the limitations currently facing biofuel production from algal feedstock.

Microalgae are single-cell microscopic organisms which are naturally found in fresh water and marine environment. Their position is at the bot­tom of food chains. Microalgae are considered to be one of the oldest living organisms in our planet. There are more than 300,000 species of micro algae, diversity of which is much greater than plants [3]. They are thallophytes — plants lacking roots, stems, and leaves that have chlorophyll as their primary photosynthetic pigment and lack a sterile covering of cells around the reproductive cells [4]. While the mechanism of photosynthesis in these microorganisms is similar to that of higher plants, microalgae are generally more efficient converters of solar energy thanks to their simple cellular structure. In addition, because the cells grow in aqueous suspen­sion, they have more efficient access to water, CO2, and other nutrients [2, 5]. Generally, microalgae are classified in accordance with their co­lours. The current systems of classification of microalgae are based on a) kinds of pigments, b) chemical nature of storage products, and c) cell wall constituents [2]. Some additional criteria are also taken into consid­eration including cytological and morphological characters: occurrence of flagellate cells, structure of the flagella, scheme and path of nuclear and cell division, presence of an envelope of endoplasmic reticulum around the chloroplast, and possible connection between the endoplasmic reticu­lum and the nuclear membrane [6]. Some major groups of microalgae are shown Table 1.

The oil contents of various microalgae in relation to their dry weight are shown in Table 2. It is clear that several species of microalgae can have oil contents up to 80% of their dry body weight. As mentioned ear­lier, some microalgae can double their biomasses within 24 hours and the shortest doubling time during their growth is around 3.5 hours which makes microalgae an ideal renewable source for biofuel production [7]. The oil content and types of microalgae available at fresh water and ma­rine water are shown separately in Tables 3 & 4.

The advent of quantum theories on the molecular scale has inspired the de­velopment of electromagnetic exposure systems that mimic the complex interactions and symmetry found in nature from endogenous electromag­netic signals and their destructive interference between interdependent cells. The idea of using multiple interdependent electromagnetic emitters has led into a novel investigation of complex configurations using specific geometric orientations of multiple electrodes generating electromagnetic fields with precise phase orientation and relationships, which may lead to even more significant coupling with biological systems.

The interdependent Multipolar (MP) electromagnetic systems were devised and developed by Lensky [63], and Zavalin and his co-workers [13,14]. The MP system may contain a variety of number of poles, i. e., 2, 3, 5, 6, 9, 12, in the symmetrical electrode configuration (Cn, where n = 2, 3, 5, 6, 9, 12 correspondingly, in notation of the crystallographic groups of symmetry) and complex driving system of interdependent multidimen­sional transformers that is of most importance. For research with bios­timulation of microorganisms, preliminary studies by Zavalin have found that six-pole systems are most effective for microorganisms compared to other configurations. The MP system used in their research consisted of six electrodes in a symmetric hexagonal geometric arrangement (group of symmetry C6), driven by a hexapole interdependent transformer system, powered by an amplified function generator. The frequencies of the EMF oscillations are lower than 100 kHz, providing the near-field regime of the MP EMF during the treatment. The MP EMF generated is fine tuned such that the superpositional field, composed of oscillating electric fields from each electrode in the near-field regime undergoes complete destruc­tive interference with a resultant zero-vector electric and magnetic field within a certain area, located near the center of symmetry and called the “compensation zone”. The compensation zone can produce a “breathing” mode where all coils are energized simultaneously to achieve the multi­polar compensation zone. A scheme for the 6-polar EMF treatment for the test tube culture studies is shown in Figure 2. The multiple pole EMF configurations have a substantial effect on growth of microorganisms. Maximum achieved growth or gas production increases up to approxi­mately 200% (see Figure 3) were observed in various bacteria, yeast, and protozoa under a 5 or 6-pole configuration at 1 kHz [13], 60 Hz, 0.35-2.1 kHz [14]. The AC voltages at the electrodes were applied 180 degrees out of phase for each opposing set of electrodes, resulting in rather pulsating than a rotating EMF pattern. Figure 3 shows maximum increase in growth of E. coli cultures in test tubes under treatment at different frequencies of 6-polar AC EMF. In the plot a maximal achieved ratio of concentration of stimulated E. coli culture to concentration of control E. coli culture at the same conditions is shown in the right vertical axis. A corresponding time, required to achieve such a maximal relative stimulated increase is shown in the left vertical axis. It should be noted that a depression in growth was observed in 2 and 4-pole system at the similar parameters of the EMF at each electrode. The stimulatory effect was greatest in the lag and log phases of the growth curve.

These studies show great promise considering the uniform frequency being emitted was chosen arbitrarily and are open for future research on

the optimization of output signal for growth stimulation. The results of studies conducted by Lensky and Zavalin indicate that higher topologi­cal EMF, having specific group of rotational symmetry is biologically ac­tive. This phenomenon has been previously observed using other types of self-cancelling coil windings [64-66] although the groups of symmetry have not been disclosed. Preliminary evidence indicates that these non­classical designs may be more effective at delivering vibrational informa­tion by coupling with interdependent harmonic oscillating cells because these methods produce relatively large biological effects experimentally [13,14,66]. Thus, the multipolar configuration is a strong prospect for ex­hibiting unique and distinct biological effects.

Lipid composition and FAME content were analyzed as previously de­scribed [24], using an HPLC (Surveyor LC Pump and Autosampler Plus, Thermo Finnegan, USA) coupled to both ELSD (Sedere Sedex 75) and quadrupole mass spectrometer (Thermo Finnigan MSQ) using a 10:1 line splitter (Analytical Instruments, USA). Xcalibur software controlled op­eration of the autosampler, pump, and mass spectrometer. ELSD analog data was acquired through an A/D data acquisition box (Agilent Technolo­gies, SS420X) and RS232 PCI data acquisition card (Sea Level Systems, 7406S). Lipid standards and extracts were resolved using a YMC Pack PVA-Sil-NP column (250 mm x 4.6 mm I. D., 5 pm bead size) protected by a Waters Guard PakTM guard column containing Nova-PakTM silica inserts. The solvent program is given in Table 1. ELSD was run at 30 °C at gain setting 8. Mass spectrometer was run in APCI positive mode with probe temperature of 400 °C.

8.2 CONCLUSIONS

Anion exchange resins can be used as a simple and inexpensive support for one-step algal harvest and biodiesel generation. The yields of FAME are greatly improved over methods that first isolate the TAG fraction since polar lipids also contribute to the FAME pool. Both the resin and the trans­esterification reagent can be reused for numerous cycles with the resultant FAME collected during each cycle. Although the basic principles have been demonstrated there is much room for improvement, especially in the design of resins. Although resins bind to algae based on surface charge, there are clearly additional issues that impact binding capacity, fouling and FAME conversion that are specific to different species of algae.

The lipid content of algal cells is closely related to the metabolic pathways that the algae undergo. Photoautotrophic growth is usually characterized by lower rates and lower lipid content compared with heterotrophic growth in which algae use organic matter as carbon and energy source [36,37]. Ef­forts have been made to control metabolic activities during cultivation in order to maximize lipid accumulation. Wu et al. [38] added organic carbon (glucose) to and reduced inorganic nitrogen in the cultivation of Chlorella protothecoides, and found that the induced heterotrophic growth resulted in 55.2% lipid content, which was about four times that in photoautotro­phic growth. Xiong et al. [39] developed a photosynthesis-fermentation model with double CO2 fixation in both photosynthesis and fermenta­tion stages which provided an efficient approach for the production of algal lipid. In this model, cultivation of C. protothecoides could realize 69% higher lipid yield on glucose achieved at the fermentation stage, and 61.5% less CO2 released compared with typical heterotrophic metabolism.

1.4.1 CULTURE CONDITIONS

Lipid synthesis may also be induced under other stress culture conditions, such as extreme light [40], temperature [41], salinity [42], pH [43], and CO2 conditions [44]. Therefore, during cultivation, process conditions must be closely monitored and/or appropriately adjusted for optimal lipid productivity.

1.4 PROCESSING OF MICROALGAE LIPID

Harvesting of the algal biomass is one of the greatest energy consumers in the process chain for algal biofuel production. Many options exist for extracting the algae with each having their own advantages and disadvan­tages. Low energy harvesting is favoured but options are limited by cell sizes. If the algae being harvested are of a large 70 pm [61] the algae can be filtered. Ideally, if the conditions allow, gravity filtration is possible and this requires very little energy input. This would be the optimal solu­tion economically and environmentally due to low energy requirements. Alternatively, should cell size allow, the biomass can be pressure filtered requiring slightly more energy but providing a higher removal efficiency. In most cases it is likely that flocculation would be required to allow the biomass to settle or float more readily. Conventional flocculants appear favourable in terms of harvesting yield yet may cause issues downstream due to contamination. Ideally if flocculation is necessary, bio-flocculation could be carried out using bacteria or other algae strains to obtain flocs, but further research is required to fully understand in which conditions this is possible. Alternatively organic flocculants such as chitosan could provide a more sustainable option but, again, efficiency of biomass re­moval using chitosan requires further study. It is likely that if flocculation is necessary, a combination of flocculants would be required for the most sustainable solution. Following flocculation, sedimentation or flotation of the biomass should be a successful method of harvesting without signifi­cant energy input.

Centrifugation of algal biomass could be necessary if biomass of high solids content is required. Due to the energy requirement, centrifugation should, where possible, be avoided but due to the high and rapid recovery it could provide a necessary step. The least energy-intense processes for harvesting algae are sedimentation/flotation and gravity filtration as there is little energetic input. Ideally biomass would be filtered or settled using sedimentation due to low inputs however with the majority of strains this may not be practical without prior treatment. Flocculation with the least intensive and damaging flocculants should be used if necessary and cen­trifugation a last option for dewatering.

The average algal concentration of the growth volume in the Experi­mental Case was 0.26 g/L, the neutral lipid fraction was estimated to be

0. 02, and cultivation required 123 days. The neutral lipid content was determined by HPLC and the lipid composition included hydrocarbons, triglycerides, diglycerides, and monoglycerides. On average, 2 mg of bio­crude and 165 mg of post-extraction biomass were recovered per liter of processed volume. These are not high productivity values as the research focus was on processing rather than growth. It was assumed that the bio­oil refining efficiency was 1 and the biomass fuel refining efficiency (con­verting post-extraction biomass to methane) was 0.25 [14,35].

The grown mass productivity (PGM), estimated bio-oil productivity (PBO), and estimated methane productivity (PBMF) were calculated by com­bining these values, yielding 2.1 g of bio-oil per thousand liters of pro­cessed growth volume (0.0026 L/kLp, 0.00069 gal/kLp where Lp is the liters of processed growth volume) and 41.6 g of methane per kLp (cf. Table 2).

For the Highly Productive Case, the algal concentration was modeled to be 1 g/L (a factor of four improvement over the Experimental Case), requiring 12.5 days of cultivation with a grown mass productivity of 0.08 g/L-d. The neutral lipid fraction was assumed to be 0.3 and the production

efficiencies were specfied as: 9harv = °.9, 9Cellsys = °.95, 9sepBC = 09, 9refBO

= 0.9, 9sepBS = 1, 9refBMF = 0.25 [14]. The grown mass productivity (Pgm), bio-oil productivity (PBO), and methane productivity (PBMF) were calcu­lated from these values and are listed in Table 1. As listed, 210 g (0.26 L,

0. 069 gal) of bio-oil and 150 g of methane are produced for each kLp. The Highly Productive Case yields an energy output that is 7 times greater than that for the Experimental Case, and the energy inputs are described below.