Traditionally, yeasts have been used in the food and beverage industry, so the major­ity of yeasts have been adapted to meet these procedures. The ability to accumu­late lipids above 20 % of its weight is achieved by only 5 % of the known yeasts (Beopoulos et al. 2011). Lipid accumulation in oleaginous yeast occurs under excess of carbon sources, being scarce the nitrogen source, so the carbon excess is channeled into triglycerides (Ageitos et al. 2011). Similar to other microorganisms, yeast is able to consume different sources of carbon and nitrogen, from waste to laboratory-pure sources. However, to take advantage of this technology, the use of widely available waste is a key parameter. According to this, the main by-products of the rapeseed oil-based biodiesel industry, glycerol (carbon source) and rape — seed meal (nitrogen source), were used as culture medium for the oleaginous yeast Rhodosporidium toruloides Y4 and the accumulation of oil was analyzed. Results showed that the accumulation of oil reached up to 19.7 g/L, higher than 16.2 g/L achieved when a medium composed of glycerol and yeast extract as nitrogen source was used. Besides, the oil fatty acid composition comprised a high content of mon­ounsaturated fatty acids, which makes it suitable for biodiesel production (Uckun Kiran et al. 2013). Many authors have proposed the use of glycerol as carbon source to grow different oleaginous yeasts, i. e., Cryptococcus curvatus (Liang et al. 2010), Rhodotorula glutinis (Saenge et al. 2011), Rhodotorula graminis (Galafassi et al. 2012), and R. toruloides (Xu et al. 2012). In all cases, it was considered a suitable carbon source for lipogenesis. Also, the hydrolyzate from lignocellulosic materials has been considered an interesting substrate due to the availability and economic feasibility (Yu et al. 2011; Gong et al. 2012; Uckun Kiran et al. 2012).

The culture conditions, such as C/N ratio (close to 100), substrate, culture mode, microelements, and inorganic salts, are crucial in lipid accumulation (Ageitos et al. 2011). While the ratio C/N plays the most important role in lipid accumulation, the culture mode is also of special interest. For this reason, Zhao et al. (2011) used dif­ferent feeding strategies with yeast R toruloides Y4 and concluded that the fed-batch strategy exhibited the largest oil accumulation potential under large-scale production plant, while keeping the residual glucose concentration to 5 g/L of carbon source and the fed-batch cycles were multiple times repeated. Authors removed the majority of the mature culture at the end of each cycle, keeping 900 ml of the culture in the bioreactor. Then, fresh media were added and a new cultivation cycle was initiated. As a result, the highest amount of lipids reported in the literature, 78.7 g/L, was achieved (Table 7).

The main disadvantage of oleaginous yeast is the extraction of the oil, due to the resistance of the cell walls to different solvents. In most cases, a chloroform methanol stream has been used, although this solution is not environmentally friendly because of the toxicity of reagents. An interesting alternative is provided by an enzyme-assisted method, consisting in a microwave-aided heating pretreat­ment, further enzymatic treatment with the recombinant P-1,3-glucomannanase and plMAN5C, and later oil extraction with ethyl acetate. The percentage of extraction with this method is close to 96.6 % of the total oil (Zeng et al. 2013).

Table 7 shows the fatty acid composition of yeast oil. Although it varies depending on the species and substrate, it is mostly composed of palmitic and oleic acid, the lat­ter being preferred for the biodiesel industry due to its high unsaturation degree (Pinzi et al. 2011). Wahlen et al. (2012) compared biodiesel properties, performance, and emissions in a diesel engine, biodiesel being produced from soybean, algae, bacteria, and yeast oil. Only small differences in terms of exhaust emissions were detected, as biodiesel from yeast oil emitted lower hydrocarbon but higher NOx emissions.

4 Conclusion

Many studies have demonstrated that the use of oleaginous macro — and microor­ganisms has a great interest to the biodiesel industry, as an alternative to first — and second-generation biodiesel. Although each species has its own characteristics that make it suitable to the production of biodiesel, insects posses the ability to recycle organic waste like manure and produce high amount of good-quality oil, while micro­organisms may be fermented on conventional bioreactors, which is a very attractive feature. In the improvement of these technologies, genetic engineering provides a key tool, besides the increase of knowledge about organisms, i. e., culture media and growing conditions. Moreover, the oil composition of oleaginous organisms may be genetically modified to meet the ideal biodiesel requirements, but also it can be modi­fied in pursuit of the best combination of substrate, species, or culture mode. It may be concluded that yeast is the preferred oleaginous microorganism among those ana­lyzed in this chapter, due to its rapid growth, ability to be scaled up, production of lipids, and suitable fatty acid composition to be transesterified into biodiesel.

Acknowledgments This research was supported by the Spanish Ministry of Education and Science (ENE2010-15159) and the Andalusian Economy, Innovation and Enterprise Council, Spain (TEP-4994).

1.2 EU Biofuel Policy Scenario

In the European context, two political decisions have had a fundamental role in the biofuels expansion: the Directive 2003/30/EC and Directive 2009/28/EC (RED). The objectives of RED policy in 2009 included the following: increasing farm income, improving environmental quality, and increasing national energy security.

A large variety of biofuel support policies are in place in EU member states, rang­ing from command and control instruments such as standards and shares, economic and fiscal measures, such as tax exemptions, to information diffusion. This implies that market demand is created by policies, as the production costs of biofuels lie above those of fossil fuels. This can be done through basically two instruments: sub­sidization or prescription of a mandatory production. Under the first scheme, biofuels are subsidized in order to reduce the price level to that of fossil fuels (or below). The second approach consists of prescribing a specific quantity of biofuels to be supplied by fuel suppliers on an obligatory basis (blending or use target mandates).[9]

The first option is implemented by the following: (a) tax reduction scheme, which has proven successful although it has caused important revenue losses for the government and (b) support to the cultivation of agricultural feedstock production by the Common Agricultural Policy (CAP). Unfortunately, in 2011, both of measure budgetary support were deleted. The second option (use target mandates) provides that fuel suppliers are obliged to achieve a certain biofuel share in their total sales. Currently, the latter measure is working.

The European Union climate and energy package from 2008 nullifies or updates much of the previous legislation. Its implementation will have a profound impact on how biofuels are used and the level of market penetration achieved in the future. The package aimed achieving the 20-20-20’s objectives: 20 % reduction in emissions, 20 % renewable energies, and 20 % improvement in energy efficiency by 2020.

Within the package, the Renewables Directive (RED) has arguably the high­est significance with regard to biofuels. The Directive deals with biofuels in sev­eral ways, of which the most noteworthy is the mandatory target which states that 10 % of final energy consumption in transport should be met by renewable energy by 2020. Another important aspect of the Directive is the mandatory sus­tainability criteria to which all biofuels are subject. This aspect, in particular, has received high publicity, and its detailing in the Directive has left serious questions open regarding indirect land-use change and potential clashes with trading laws (Amezaga et al. 2010; European Federation for Transport and Environment 2009).

Regarding the sustainability criteria, the RED ensures that the production of raw materials for biofuels does not lead to losses of high carbon stock land such as wetland, forested areas, and peatland; and high land biodiversity such as primary forest and other protected areas including grassland. EU production shall, in addi­tion, comply with certain agricultural and environmental requirements. In particu­lar, biofuels are required to ensure a saving of greenhouse gas emission of at least 35 % when compared to the replaced fossil fuel. This minimum saving would be increased by 50 % in 2017 and by 60 % in 2018 for new installations. The emis­sions shall be calculated over the entire life cycle of the biofuels and include, if any, carbon losses from conversion of land for biofuel crop production.

Currently, similar sustainability requirements were set in the Fuel Quality Directive 2009/30/EC on the specification of petrol, diesel, and gas oil, which pro­vided also a 6 % reduction in greenhouse gas (GHG) emissions from road trans­portation fuels by the blending with biofuels.

Only sustainable biofuels, domestically produced or imported, will be eligible to be counted against the target and for any other public support.

In June 2010, the European Commission announced a set of guidelines explain­ing how the Renewable Energy Directive Verification, on compliance with the sustainability criteria for biofuels and bioliquids, should be implemented (COM (2010)160/01; COM (2010) 160/02; and Decision 2010/335).

In addition, the European Commission was asked to come forward with propos­als by the end of 2010 to limit indirect land-use change. The RED criteria, in fact, exclude some important GHG emissions such as the indirect effects, for example, on land use. For this reason, on October 17, 2012, the Commission published a proposal of directive issued as COM (2012) 595 aiming at limiting global land conversion for biofuel production (include indirect land-use change, ILUC) and to raise the climate benefits of biofuels used in the EU.

The proposal (named ILUC proposal) should amend both the Renewable Energy Directive (2009/28/EC) and the Fuel Quality Directive (98/70/EC). With these new measures, the Commission would limit the use of food-based biofuels and include ILUC2 emissions when assessing the greenhouse gas effect of biofu­els. The use of first generation of biofuels to meet the 10 % renewable energy tar­get of the Renewable Energy Directive will be limited to 5 %. The intention of the proposal is to introduce three ILUC emission factors (for cereals 12 g CO2 eq/MJ, sugars 13 g, and oil crops 55 g). The high ILUC factor especially for oil crops could disqualify most biodiesel made from rapeseed, soybeans, as well as palm oil (first-generation biofuels).

The sustainability criteria proposed by the EU, which aim to combat the envi­ronmental problem, have been subject to widespread criticism and extensive dis­cussion. Social criteria and indirect land-use change are hot topics, both of which are not dealt with in the Directive and face similar difficulties (Amezaga et al. 2010). Both are recognized struggles but how to quantify their effects and incorpo­rate them into policy remains a serious issue. For this reason, the proposal ILUC, nowadays, is largely called into question by European stakeholders.

This article conducted qualitative descriptive research, using the case study research method. The case under analysis in this study is the agricultural link of the biodiesel production chain in Brazil, with a focus on oil palm family farmers. Thus, the study can be classified as multi-cases with personal and in-depth interviews.

The primary data collected included interviews with 27 professionals, con­ducted from February 2010 to February 2011. Of these key players, six respond­ents were from public agencies, two were bank professionals, three represented the opinions of the biodiesel companies, five were companies producing oil palm and other derivatives, two were representatives of family farmers’ associations, and nine respondents belonged to the agricultural production chain.

Starch is a polysaccharide composed of glucose units (monomers). This poly­saccharide requires acidic hydrolysis to release the glucose monosaccharide to be fermented by S. cerevisiae yeast to produce 1G ethanol. The starch chemical structure is presented in Fig. 3. Examples of starch-containing plants include corn, potato, cassava, wheat, and barley (Table 4).

Fig. 4 Lignin structure (left) and its precursors (right): (I) p-coumaryl alcohol, (II) coniferyl alcohol, and (III) sinapyl alcohol. Author Silvio Vaz Jr

As of today, it has been shown that it is scientifically and technically possible to derive the desired energy products from algae in the laboratory. The question lies, however, in whether it is a technology that merits the support and development to overcome existing scalability challenges and make it economically feasible (Mcgraw 2009). Additionally, the basic economic motivation for biofuels is that they are a convenient, low-priced, domestically producible, and a substitute for oil; an energy source that is getting costlier; and it is mostly imported from politically volatile regions (Castanheira and Silva 2010). Economic feasibility is believed to be currently the main hurdle to overcome for this technology. Current costs associ­ated to both the state of the science and technologies are sizeable and represent a main factor hampering development.

High costs often prevent the market diffusion of novel and efficient energy technologies. As microalgae biofuel is not a mature technology, it becomes important to provide a revision of technological innovation and diffusion aspects to enlighten some available options that may help overpass the barriers found by innovative technologies (Ribeiro and Silva 2013).

It is widely recognized that modern economic analysis of technological innova­tion originates fundamentally from the work of Schumpeter (1934), who stressed the existence of three necessary conditions for the successful deployment of a new tech­nology: invention, innovation, and diffusion. His seminal work has been constantly referred (Soderholm and Klaassen 2007), and each of the keywords represents differ­ent aspects; in particular, invention includes the conception of new ideas; innovation involves the development of new ideas into marketable products and processes; and diffusion, in which the new products and processes spread across the potential market.

Emergent technologies are relatively expensive at the point of market intro­duction but eventually become cheaper due to mechanisms such as learning-by­doing, technological innovation and/or optimization, and economies of scale. The combined effects of these mechanisms are commonly referred to as technological learning. Over the last decades, learning theories in combination with evolutionary economics have led to the innovation systems theory that expands the analysis of technological innovation, covering the entire innovation system in which a tech­nology is embedded. In particular, “an innovation system is thereby defined as the network of institutions and actors that directly affect rate and direction of techno­logical change in society” (Junginger et al. 2008).

In the emerging energy technologies field, there is a strong need to influence both the speed and the direction of the innovation and technological change. With that in mind, policy makers are putting their efforts on lowering the costs of renewable energy sources to support the development of renewable technologies, either through direct means such as government-sponsored research and devel­opment (R&D), or by enacting policies that support the production of renewable technologies. It is well documented (Johnstone et al. 2010; Popp 2002) that both higher-energy prices and changes in energy policies increase inventive activity on renewable energy technologies (Popp et al. 2011).

As noted by Popp et al. (2011), the higher costs of renewable energy technologies suggest that policy intervention is necessary to encourage investment. Otherwise, in the lack of public policy favoring the development of renewable energy, production costs remain too high and they do not represent an option in replacing fossil fuels.

Policies to foster innovation should not only focus on the creation and sup­ply of new technologies and innovations, but also on the diffusion and take-up of green innovations in the market place. Such policies need to be well designed to ensure that they support, do not distort the market formation, and should be aligned with competition policies and international commitments (OECD 2011).

With this purpose, several government policies have been introduced in the energy markets worldwide in an effort to reduce costs and accelerate the market penetration of renewables. Although the effectiveness of alternative policies to encourage innovation still needs to be tested empirically, it is expected that these policies will stimulate innovation in renewable energy (US DOE 2010).

In the next section, some of the policies that could enhance the development of microalgae biofuels are, therefore, revised.

Biodiesel, which is also known as fatty acid methyl ester (FAME), is produced from the transesterification of vegetable oils or animal fats with the addition of methanol (Lin et al. 2009). This type of biofuel contains no petroleum products, but it is compatible with conventional diesel engines and can be blended in any propor­tion with fossil-based diesel fuel to create a stable biodiesel blend (Lin et al. 2011).

Commercially, these blends are named B5, B20, or B100 to indicate the per­centage of the biodiesel component in the blend with petrodiesel (these percent­ages are 5, 20, and 100 %, respectively). Some of the main countries in grain production have established various stages of implementing or expanding the man­datory blending of biodiesel in motor fuels. This type of policy is crucial for the establishment of the biodiesel industry (Janaun and Ellis 2010).

Figure 4 presents an estimate of biodiesel production, consumption, exports, and imports for 2013 and 2020.

In 2010, the European Union (EU) was the leading biodiesel market with a pro­duction share of 52.8 %, and it was followed by the Americas with 33.9 % and Asia with 3.5 % (Sawhney 2011). Thus, the EU is the world’s largest biodiesel industry and market (Yusuf et al. 2011). Currently, each state has set different targets and regulations, but the average biodiesel blend is estimated at 5.75 % (IEA 2011).

The US production of biodiesel is smaller than the European production and shows important differences. Soybean oil is the most commonly used feedstock in the USA, and it is followed by rapeseed oil and soy oil. A stable consumption of 1 billion gallons per year is estimated from 2013 to 2020, and the production will tend to increase. This pattern will ultimately create export opportunities for the US biodiesel industries.

Argentina is a major exporter of biodiesel, which is produced almost exclu­sively from soybeans. The country has an export-oriented industry that is respon­sible for the estimated increase of biodiesel production and exports from 2013 to 2020. B7 was recently introduced in the domestic market (IEA 2011). However, the country’s exportable surplus is projected to increase 13 % from 2013 to 2020.

In Brazil, most of the biodiesel production is meant to satisfy the domes­tic demand, which is motivated by government policies. Nevertheless, a slight decrease in domestic consumption can be expected by 2020, as shown in Fig. 4. Biodiesel producers expect to gradually increase the demanded biodiesel volume from B7.5 to B10 in 2014 and to B20 by 2020. Currently, the net exports’ projec­tions remain at modest levels and will not exceed 60 million gallons by 2020.

The dominant feedstock is soybean oil, although Brazil is investing in alternative vegetable oils to produce biodiesel.

The source for biodiesel production is chosen according to the appropriate raw materials’ availability in each region or country. In Malaysia and Indonesia, coco­nut oil and palm oils are used for biodiesel production. The combined biodiesel production in Indonesia and Malaysia is expected to increase approximately 20 % by 2020, and both countries are net exporters. Their domestic production growth is limited by small domestic demand, high feedstock prices, and strong competi­tion from the Indonesian availability in the export markets. The Malaysian govern­ment has started to implement a B5 policy (IEA 2011). However, the domestic consumption is expected to remain stable.

A few other countries are considering the introduction of biofuels policies, which could create an additional global demand for vegetable oils and grains. This new demand would potentially influence both the grain and oilseed processes and these commodities’ availability for food, livestock, dairy, and poultry production.

In this context, algae may represent a promising alternative to grain oil, as they can be produced in many locations with enough sunlight. The most significant dis­tinguishing characteristic of algal oil is its conversion into biodiesel: The conver­sion rate is up to 50 % (Demirbas 2007). For traditional biodiesel, key areas for improvement include more efficient catalyst recovery, improved purification of the coproduct glycerin, and enhanced feedstock flexibility (IEA 2011).

The world biodiesel price (Central Europe FOB) and the biodiesel price for this fuel when it is bought directly at a plant show similar trends in Fig. 5.

From 2007, when approximately 3 million gallons of biodiesel were produced, to 2012, an increase of 104 % was observed in the total produced amount. In the same period, the world biodiesel price increased by 49 %. The cost of biodiesel

fuels varies depending on the feedstock, the geographic area, the variability in crop production from season to season, the price of crude petroleum, and other fac­tors (Demirbas 2007). Increasing crude oil prices and the mandates in Argentina, Brazil, the EU, and the USA have led to price increases throughout the period under consideration. In 2011, a high biodiesel price ($5.75) per gallon occurred, and there was a small decline in 2012. Below, we briefly outline the history of the two major producers of biofuels that stand out in the current scenario: Brazil and the USA.

FASOMGHG contains accounting procedures which calculate GHG emissions, sequestration, and bioenergy offsets by the forestry and agricultural sectors includ­ing land use changes. Usage of crop residues and energy crops for the ethanol or electricity production replaces gasoline and coal-related emissions. At the same time, hauling and biomass processing produce emissions, also accounted for in the model. All GHGs are converted to a carbon dioxide equivalent (CO2e) basis using 100-year global warming potential (GWP) values (Beach et al. 2010). Table 1 pro­vides examples of GHG categories.

CO2e pricing (or GHG pricing) is modeled as a market payment for the reduction in net emissions (i. e., a reduction from baseline emissions or an increase in sequestration or bioenergy offsets). It also serves as a tax on net emissions increases such as an increase in hauling emissions associated with bioenergy production. GHG payment variables are created which pay a per ton price to the change in each GHG account relative to the baseline. The GHG payments can be either positive or negative in each account based on the net change in GHG (Beach et al. 2010). Table 2 presents the GHG prices in dollars

Carbon emissions from agricultural use of fossil fuels Carbon sequestered in agricultural soil Carbon sequestered in trees Carbon sequestered in forest products

Carbon emissions from gasoline use offset by conventional ethanol production

Carbon emissions in hauling for conventional ethanol production Carbon emissions in processing of conventional ethanol production Carbon emissions from gasoline use offset by cellulosic ethanol production

Carbon emissions in hauling for cellulosic ethanol production Carbon emissions in processing of cellulosic ethanol production Methane emissions from enteric fermentation by animals Methane emissions from animal manure Nitrous oxide emissions from crop fertilization Nitrous oxide emissions from animal manure

Source Adapted from Beach et al. (2010)

Table 2 GHG prices used in GHG prices used in the model (in $/ton of CO2e) the model (GHG price signal)

$0

$1

$5

$12

$15

$30

$50

$100

per ton of CO2e (in terms of their global warming potential[13]) which are used in the model.

GHG payments are designed to internalize the negative externality arising from GHG emissions. Not only do they provide incentives for use of agricultural and bioenergy activities that reduce net GHG emissions, but also they can make emis­sion efficient ethanol production more profitable by adding revenue streams. The magnitude of these GHG payments is determined by the amount of GHG emission offsets provided.

The GHG prices, used in this study, range from $0 per metric ton of CO2e to $100. Currently, carbon trading and CO2e prices are in effect in the European Union, under the European Union Emission Trading Scheme. Between 2005 and 2007, the GHG price peaked at $40 per ton. In 2008-2012, the price fluctuated between $9 and $40 per ton. The lowest carbon price happened in January 2013 at $4 per ton. The USA also had a voluntary trading system called the Chicago Climate Exchange. This exchange operated between October 2003 and July 2010 with a price in the range of $0.05-7.50 which subsequently closed. According to EPA estimates, the carbon price would need to rise from about $20 per ton in 2020 to more than $75 a ton in 2050 for the CO2 level in the atmosphere in 2050 to be 83 % less than it was in 2005 (Feldstein 2009). These higher carbon prices will be transmitted into higher prices of carbon dioxide intensive goods and services. Feldstein (2009) argues that the burden of higher carbon prices would mostly fall on households.

As discussed in the sections above, the biochemical route seems to have better attrib­utes such as low cost and easy operation and can be operated in a smaller scale in the vicinity of feedstock production facilities. However, the major hurdle to the imple­mentation of the biochemical route in commercial scale is the pretreatment of the feedstock to produce sugars. In addition to pretreatment issue, fermentation of the pretreated hydrolyzate also remains a great challenge. The key objective of the lig — nocellulosic fermentation should be to use all of the sugars (C5 and C6) and convert them into biofuels. This could be achieved only by genetically modified microorgan­isms having additional pathways needed to convert C5 and other sugars into biofuels.

A detailed discussion of the technical hurdles w. r.t pretreatment process is pre­sented below.

Data on the effects of reaction temperature on degradation of HDPE into various products using HZSM-5 (80) catalyst are shown in Table 3 while Table 4 presents the yields of degradation products using AlSBA-15 catalyst. It is clear that gen­erally the yield of volatile products increased with increasing reaction tempera­ture. It was well noted that by increasing the temperature, cracking probability was increased to result in higher yield of volatile products. At higher tempera­ture, the reaction was generally accelerated, and the accessibility of the reaction products resulting from interaction with external active sites and the reactant was improved. Thus, cracking reactions to give smaller molecular-sized sub­stances were improved. On other hand, the small internal pores of the HZSM-5 and AlSBA-15 catalysts could create hindrance toward the formation of liquid

Fig. 4 Effects of different catalysts on liquid products yield at 623 K with 10 % catalyst loading

products with relatively larger molecular sizes. The effect was more severe in the case of zeolite catalyst with internal pores in the micropore size range. However, it was also noted that the HZSM-5 (Si/Al = 80) catalyst had better capability to con­vert liquid products into gaseous products especially at high temperatures. Similar observations have been reported in literature (Mastral et al. 2006). For exam­ple, it was found that the liquid yield decreased with increasing temperature and higher temperature evidently caused decreases in boiling points of liquid products (Hernandez et al. 2006).

Findings made in this study were in good agreement with those reported by Mastral et al. (2006). They found that zeolitic materials were suitable to be used in

Fig. 5 Effects of reaction temperature on gas products yield by 10 % loading of HZSM-5(80) catalyst

catalytic degradation of polyethylene due to their acidity and structural suitability. As observed in this study, the highest gas yield was achieved by increasing the experi­mental temperature from 350 to 400 °C. Our results regarding the effects of tempera­ture on AlSBA-15 catalyst were also in good agreement with those of Sinfronio et al. (2006) who used Al-MCM-41 as the mesoporous catalyst. Based on these observa­tions, it could be concluded that the most suitable temperature range for maximum liquid fuel yield using HZSM-5 catalyst was 350 °C while it was 400 °C for AlSBA — 15 catalyst. However, higher coke deposition could sometimes correspond to the increasing reaction temperatures, and formation of waxy compound might prevent the accurate calculation of the yield of liquid and gaseous products.

Data regarding the effect of reaction temperature on the gaseous product yield using HZSM-5(80) catalyst are presented in Fig. 5. It is shown that 500 °C gave the most uniform products distribution with highest composition showed by C3 (34.5 %) and the lowest by C5 (11.2 %). By carrying out the reaction at 400 °C, remarkable reduction on the C1 while at the same time an increase in the propor­tion of carbon chain C5 was observed.

In order to compare the effect of temperature when a mesoporous catalyst was used, similar experimental run was carried out using AlSBA-15 catalyst. Figure 6 presents data that were obtained using the mesoporous catalyst. In this case, 350 °C showed the highest gaseous products yield with the highest composition showed by C4 while for the other two reactions, i. e., 400 and 500 °C, C3 predominated. Generally, temperature does not have dominant effects on the gaseous products dis­tribution. However, the difference in gaseous products distribution was significant when comparing results obtained with microporous HZSM-5 (80) and mesoporous AlSBA-15 catalysts. AlSBA-15 catalyst under same 10 % catalyst loading did not produce detectable C1 gas products. This mesoporous catalyst also led to increases in C5 (11.6 and 12.7 %) as compare to those of HZSM-5 microporous catalyst (4.4 and 7.0 %) for the reaction temperatures of 350 and 400 °C, respectively.

However, degradation of liquid products using HZSM-5 (80) showed a decreas­ing trend for increasing carbon chain from C8 to C25+. As shown in Fig. 7, the highest proportion of liquid products for all four reaction temperatures was in

Fig. 6 Effects of reaction temperature on gas products yield by 10 % loading of AlSBA-15 catalyst

Fig. 7 Effects of reaction temperature on liquid products yield by 10 % loading of HZSM-5 (80) catalyst

the carbon chain range of C8-C12. The lowest proportion of carbon chain range was the heaviest carbon chain, i. e., C25+ for all reaction temperatures studied. Increasing reaction temperature had the tendency to produce higher amount of shorter carbon chain molecules while simultaneously reducing the longer carbon chain molecules in the products mixture.

Figure 8 presents the data obtained using AlSBA-15 catalyst under the effect of varying temperatures. Generally, the results showed similar downward trend as observed in the case of using HZSM-5 (80) catalyst. The highest proportion was recorded by carbon chain range of C8-C12 for all three reaction tempera­tures. The second highest composition was recorded by the carbon chain range of C13-C16. This composition also dropped steadily as the reaction temperature increased. The lowest fraction of carbon chain range for the overall liquid prod­uct was C25+. By comparing the effect of varying reaction temperatures to both microporous HZSM-5 (80) and mesoporous AlSBA-15 catalysts, it was concluded that generally liquid degradation products for AlSBA-15 consisted of shorter

carbon chain range molecules. This could be seen for carbon ranges of C8-C12 and Сіз-Сі6 at 350 °C. AlSBA-15 catalyst produced nearly 78.2 % of overall liquid composition while it was only around 63.5 % for HZSM-5(80) catalyst.

The National Oil Agency carries out, since 2005, biodiesel auctions. At these auctions, the refineries buy biodiesel to mix it up with the oil-based diesel (ANP 2012). According to the source, the initial objective of such auctions was to gener­ate a market and hence stimulate the biodiesel production in a big enough quantity for the refineries and distributors to compose the mixture, according to the law. Based on the results of these auctions, we obtained the biodiesel production in cubic meters, per state, as shown on Table 1.

We can see on Table 1 that the beginning of the biodiesel production took place in 2005 and that only four states were producing (Minas Gerais, Para, Parana, and Piauf), showing a high concentration, despite the small quantity being pro­duced, when compared to 2011 and 2012. In 2012, the biodiesel was produced in 12 of the 25 Brazilian federal units, where the higher production of the states Rio Grande do Sul, Goias, Mato Grosso, and Sao Paulo, stands out, representing 78.50 % of the national production, showing that this market is highly concen­trated in these states.

Table 2 shows that the ethanol production has grown 45.74 % between 2005 and 2012 (from 15.924000 to 23,209000 m3 in 2012). This growth can be partially explained by the increase of demand where, the increase in the internal market has been due to the more favorable price of this fuel, when compared to gas, which forces the consumption of alcohol in biofuel cars (gas and ethanol), which have had more and more representativeness in the national freight of small urban vehi­cles, since, as shown on Fig. 4, in 2005, 7 % of the cars (1.4 million) were using biofuel, and are now 57 % of the national freight. Besides, the mixture level of ethanol in gas in the last decade has varied from 20 to 25 % (according to the gov­ernment decision), thus implying more pressure on ethanol’s demand.

Table 3 shows us that the production of ethanol has increased the concentration in the four most important states (Goias, Mato Grosso do Sul, Minas Gerais, and Sao Paulo) that represented 81 % of the national production of ethanol in 2012. Also, Sao Paulo produced 51 % of the national volume in 2012 (11,830 thousand m3); however, this high concentration has decreased, since in 2005, two-thirds of the national production was centralized in this state.

Table 3 shows that both indexes (HHI and Cr(4)) point to a high concentration of the biodiesel production in Goias, Mato Grosso, Rio Grande do Sul, and Sao Paulo, these four states accounted for 87.22 % of the total biodiesel production in

2008, remaining at a level close to 80 % in the following years. Notably, this result is influenced by the main raw material used: soybeans—Goias, Mato Grosso, and Rio Grande do Sul are the main producers. Sao Paulo, on the other hand, stands out due to the usage of beef fat and soybeans. In order to verify this high concen­tration is present, we initially identified the market participation of the 16 biggest companies producing biodiesel, as shown on Table 4.

We can see on Table 4 that for 2005, none of these companies produced biodiesel, whereas only in 2006 did Granol start its activities. In 2012, the 16 analyzed companies kept 80.19 % of market participation, thus indicating that this industry has characteristics of a Cr(16), because these companies keep at least 70 % of the Brazilian biodiesel production since 2007. Do also note that the majority of these companies are located in the south and central west, cor­roborating Picture 2. In order to confirm the installed capacity concentration, we calculated the HHI for the daily installed capacity per Brazilian region, as per Table 5.

Considering the increase in demand for ethanol, as well as the strategies of mergers and acquisitions among suppliers and distribution channels recently observed in Brazil, much has been discussed about the power of the market that may be taken by those agents who are involved in the product chain. Discussions on a possible cause for the increase of the product prices have risen interest on the existence of the market power by the ethanol producers, and/or by fuel distribution channels (Beiral 2011).

The analysis by companies (distilleries and/or sugar and ethanol plants) reveals a scattered environment, granted the great number of registered units. There are now 432 operational plants in Brazil, and 83 of these plants are located in the north-northeastern region and 349 are in the central-south region (MA 2012). Besides the great number of plants, this industry shows traits of a decentralized market, since in 2012 the five largest economic groups responded for 20 % of all the grinded cane in the country (UNICA 2010).

Despite the traits indicating a low concentration level in the ethanol industry in Brazil, it is impossible to calculate it, since the Instrugao Normativa No 52, of November 12, 2009, on the Diario Oficial da Uniao of November 13, 2009, does not allow the communication of all the necessary information, since according to the Article No. 5 “the information received from the legal entities will be classi­fied, and can only be communicated in an aggregated manner per state, region, or national total” (MA 2009).

Table 4 Market participation of the 16 largest biodiesel companies Company City Region 2005 (%) 2006 (%) 2007 (%) 2008 (%) 2009 (%) 2010 (%) 2011(%) 2012 (%) Adm Rondonopolis Central west 0.00 0.00 0.37 15.54 10.67 10.34 5.78 5.61 Biocamp Campo Verde Central west 0.00 0.00 0.00 1.07 1.73 2.08 2.05 2.49 Bsbios Passo Fundo South 0.00 0.00 3.58 7.91 7.02 5.63 4.82 4.91 Bsbios Marialva South 0.00 0.00 0.00 0.00 0.00 1.97 3.54 3.98 Camera Ijuf South 0.00 0.00 0.00 0.00 0.00 0.25 4.11 6.26 Caramuru Sao Simao Central west 0.00 0.00 11.43 9.80 7.62 6.70 5.46 5.54 Caramuru Ipameri Central west 0.00 0.00 0.00 0.00 0.00 1.96 3.78 4.59 Fiagril Fucas Rio Verde Central west 0.00 0.00 0.00 6.25 5.72 4.76 5.40 4.62 Granol Anapolis Central west 0.00 14.75 18.19 11.95 8.39 7.68 6.76 8.59 Grand Cachoeira do Sul South 0.00 0.00 0.00 7.71 7.54 6.92 7.91 4.72 JBS Colide Central west 0.00 0.00 0.31 6.26 5.43 5.22 3.83 2.44 Oleoplan Veranopolis South 0.00 0.00 2.08 8.66 11.13 8.54 9.15 8.70 Olfar Erechim South 0.00 0.00 0.00 0.00 0.00 2.28 4.59 5.05 Petrobras Candeias Northeast 0.00 0.00 0.00 0.87 2.54 2.86 4.19 5.75 Petrobras Montes Claro Southeast 0.00 0.00 0.00 0.00 2.50 3.06 2.80 2.95 V-Biodiesel Iraquara Northeast 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.98 Total 0.00 14.75 35.97 76.01 70.29 70.24 74.19 80.19 Source ANP (2013a)

The perspectives of the Brazilian and American governments are not the same, since according to the Section 1501 of the Energy Policy Act of 2005, the Federal Trade Commission must analyze the market concentration of the production of etha­nol, using the HHI to determine whether or not there is enough competition among the participants of this industry so as to avoid fixing prices and other anticompetition behaviors. According the US Federal Trade Commission (2012), the American etha­nol industry is not deconcentrated (HHI equals 244 in 2010, and 284 in 2011), thus suggesting that an attempt to exert market power by any agent is unlikely.

On the other hand, part of the ethanol marketing in Brazil is made via market­ing groups, the structure of the ethanol market is much more concentrated (Beiral 2011). Thus, point to a concentration of the ethanol market as a trend. For exam­ple, the purchase of the Esso by Cosan (the largest ethanol producer in Brazil); the purchase of the Ipiranga network by Ultra (the second largest distribution channel after the purchase of Texaco, only after BR Distribuidora), along with Petrobras and Braskem (Beiral 2011).

Considering the possible increase of concentration among the ethanol distributors, we sought to evaluate the market participation of the 18 largest distribution firms for ethanol in the country, from 2005 to 2012, as shown on Table 5. Table 5 shows that in 2012, 18 firms kept 80.57 % of the ethanol distribution market. Also, note that

only three companies (BR Distribuidora, Shell, and Ipiranga) held in 2012 55.66 % of this market, showing a high market concentration, increasing since 2005, since these companies held 35.32 % market share (a 57.58 % increase for this period).

On Table 6, we can see the higher installed capacity in central west region, with 42 % of all authorized capacity in Brazil, having 31 of those 64 companies authorized to produce biodiesel. When analyzing the usage of the authorized capacity of plants installed in each one of those five regions in Brazil, and considering a 365 day year, we can see that the south region has 62 % of usage, and that if we consider 264 work­ing days in a year, the south region holds 62 % of usage and that if we consider 264 working days in a year (22 days in a month and 12 months in a year), the south region points to the limit of its capacity, with 85 % usage of its capacity in 2011. On the other hand, the northeast region only has 32 % usage of its capacity, whereas the total num­ber of companies has used 63 % of its authorized capacity for producing biodiesel.

Table 7 shows that the largest capacity installed for cane grinding and sugar and ethanol production is in the southeast, with 89, 65, and 90 % of all the Brazilian productive capacity, respectively. By analyzing the use of the average installed capacity of plants, for each of the five Brazilian regions, we can see that the main productive constraint is grinding, where the central west, northeast, and southeast regions show an over 70 % usage. Note that the usage of the installed capacity of grinding in the southeastern region is 75 %, a concerning fact since two-thirds of the installed national capacity is in this region.

On Table 8, we can see that the industrial concentration level has significantly decreased since the National Biodiesel Production Program was implemented, where in the first years of this program (2005-2006), the market showed to be highly concentrated, significantly decreasing the companies power in the market, since in 2012, the four main companies (Granol in Anapolis; Oleoplan in Veranopolis; Petrobras in Candeias and Camera in Ijuf) represented around 30 % of the volume produced in the last three years (2010, 2011, and 2012). In order to verify the impact of this low industrial concentration, we analyzed the weighted average cost of the 16 main companies and compared it to the other companies in the same sector.

As it is commented, the negotiation process for biodiesel is performed accord­ing to auctions. In order to verify whether or not this low industrial concentration

Table 7 Daily installed capacity, usage of installed capacity per Brazilian region of Brazilian cane grinding, sugar and ethanol industry Daily installed capacity % in Brazil Annual plant usage (Considering 365 days) Region Cane grinding (thousand of tons) Sugar (thousand of tons) Ethanol (thousand of tons) Cane grinding Sugar Ethanol Cane grinding (%) Sugar (%) Ethanol (%) Central west 356.78 26.83 44,070,00 15 11 18 72 60 62 Northeast 205.50 40.90 22,511,00 9 16 9 79 49 46 North 26.84 1.18 6,559,00 1 0 3 44 38 28 Southeast 1,543.64 165.43 152,490,00 66 65 63 75 52 52 South 189.42 20.00 17,760,00 8 8 7 63 38 39 Source Conab (2013)

would interfere in the pricing at these auctions, we calculated the average cost per liter of the 16 main biodiesel producing companies in Brazil. The choice of these companies was due to the fact that they represent around 80 % of the national production. As a result, we observed that in 2011 (Auctions, 22, 23, and 24) these companies used a lower price than the other companies; however, in 2012, (Auctions, 25, 26, and 27) the situation was inverse: in two out the three auctions, these companies used a price lower than the others.

In order to verify whether or not the weighted average costs of these two cat­egories are statistically significant, we calculated the average difference t test (Table 9), where we accepted the null hypothesis of equal averages, thus indicating that such companies, despite the fluctuations, do not price in a differentiated man­ner in the long term. This result can be explained by the hypothesis that companies would not have significant gains, considering the sector’s low concentration that makes a significant price reduction impossible at auctions, thus indicating some homogeneity of prices practiced in the biodiesel industry in Brazil.

On the other hand, it is not possible to calculate the concentration level of the ethanol production in Brazil, considering the Instrugao Normativa Number 52 of the Ministry of Agriculture, prohibiting the communication of ethanol production per productive unit, only allowing its communication in an aggregated manner, per state, region, or national total. However, there is another type of strength in this system: the distribution channels. Thus, we sought to evaluate the evolution of industrial concentration of the ethanol distribution in Brazil, in the last 8 years, where we calculated the HHI and the Cr(4), as per Table 10.

Table 10 shows that the industrial concentration level has grown significantly, according to Bain and Qualls (1968) and Usdoj (1997), pointing to a situation where this market moved from a weak-concentration oligopoly, to a moderate concentration, especially after 2009. In order to verify the impact of this increase of industrial concentration on this industry’s profitability, we simulated the

contribution margin for the ethanol distribution channels, as suggested by Beiral (2011). Results are shown on Fig. 5.

Figure 5 shows that in 2005 and 2006, the ethanol distribution channels showed, for several months, a negative contribution margin, and it became positive as of January 2007. Note that as of now, the concentration level of the distribution industry has grown, showing a positive correlation among variables. In order to confirm this supposition, we calculated the Pearson’s product-moment correlation coefficient between these two variables, as shown on Table 11.

As it is shown on Table 11, the Pearson’s product-moment correlation coefficient between the distributors contribution margin, and the HHI, for this industry, was 0.433 (sig equals 0.320) pointing to a positive correlation, although it is relatively weak, between the variables, i. e., as one of the variables increases (industrial concentration level), the other one increases too (distribu­tors contribution margin), noting that this increase of concentration has made it easier for pricing, thus implying a profitability increase for this industry, in det­riment of society.