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.

First-generation biofuels are relatively cheaper to produce than advanced biofuels (second-generation biofuels and beyond), but they still cost more than equivalent fossil fuels, and are also problematic from a sustainability perspective, as discussed in chapter “Environmental Issues in the Liquid Biofuels Industry”. Although advanced biofuels could address the latter issue, commercial production is yet to commence because of the higher start-up and operational costs associated with these production processes. This section will provide a comparison of the produc­tion costs of biofuels vis-a-vis fossil fuels.

The feedstock for first-generation biofuels, i. e. edible crops, accounts for nearly 55-70 % of the total production cost (IEA 2008). As a result, first-generation bio­fuels, in general, are unable to compete effectively with fossil fuels (UN 2008), particularly when government subsidies and other incentives are removed from the equation. Only sugarcane-based bioethanol produced in Brazil, which costs USD 0.25-0.35 per litre of gasoline equivalent[2] (lge), is competitive with gasoline at USD 0.34-0.42 per litre (i. e. USD 40-50 per barrel) (IEA 2007).[3] By way of con­trast, the cost of corn-based ethanol in the United States and sugar beet-based etha­nol in the EU vary between USD 0.60-0.80/lge (IEA 2007)—much higher than the then price of gasoline. Likewise, the cost of producing biodiesel from animal fat, vegetable oil, tallow fat and palm oil varies between USD 0.40-0.50, 0.60-0.80, 0.60-0.85 and 0.82-0.86/lde,[4] respectively (IEA 2007; RFA 2007), all higher than production costs of petroleum-based diesel. For some feedstocks, such as cooking oil, commercializable by-products could lower its effective cost (Demirbas 2009).

Second-generation biofuels are produced from the cellulosic content of inedible plants. While the cost of such feedstock is comparatively lower, it still represents around 36 % of the net production cost of the biofuel (USDA 2010). Processing — related expenses, including chemicals such as enzymes, are substantial. Although technological advances have significantly lowered the cost of cellulosic ethanol (Wyman 2008), the processing technique employed continues to be most signifi­cant determinant of the fuel’s net production costs. The IEA (2007) estimated the cost of second-generation bioethanol and biodiesel at approximately USD 1.00/lge (assuming feedstock price of USD 3.6/GJ) and USD 0.90/lde (assuming feedstock price of USD 3.6/GJ), with a potential reduction to USD 0.50/lge and 0.70-0.80, respectively, by 2017. Furthermore, the cost of setting up a second-generation biofuel refinery is potentially up to ten times that of establishing an equivalent first-generation production unit (Eisentraut 2010). While this additional outlay partially negates the advantage of using lower-cost feedstocks, larger plants may be able to capture economies of scale and achieve some cost savings (UN 2008). Nevertheless, high capital investments are a major concern, particularly for those plants being proposed in less developed countries (Eisentraut 2010).

Eisentraut (2010) theoretically deduced the cost of second-generation biofuels pro­duced in different countries by assuming capital costs to be 50 % of the total produc­tion costs, feedstock 35 %, operation and maintenance, energy supply for the plant, and other expenses between 1 and 4 % each. Table 3 summarizes these estimates.

Eisentraut (2010) also compared the probable production cost of second-generation biofuels if an oil price of USD 120/bbl is assumed. He concluded that bioethanol and biodiesel would cost USD 1.09 and 1.07, respectively, in the short term. In the long term, prices are projected to fall to USD 0.72 and 0.73, respectively, which would be lower than gasoline and rapeseed biodiesel, and also competitive with first-generation bioethanol. The above figures should be considered in tandem with the then price of fossil fuels. This, however, does not greatly change the cost efficiency of biofuels as the cost of biofuels continues to increase with the rise in price of feedstock and other inputs (OECD 2011). In addition, these costs are purely economic and do not include the various environmental costs typically included in life-cycle analyses (LCAs), as explored in chapter “A Comparison Between Ethanol and Biodiesel Production: The Brazilian and European Experiences”. Other costs associated with production, and that of first-generation biofuels in particular, relate to storage, especially given the seasonal nature of biofuel production (Moreira and Goldemberg 1999; Karp and Richter 2011).

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.

The environmental impacts of biofuel crops vary considerably. Among the first — generation feedstocks (e. g. sugar cane, sugar beet, maize, cassava, wheat, oil palm, rapeseed and soya bean), some absorb more CO2 than they release. But the wider environmental costs may still be greater than the benefits. For example, rapeseed offers relatively little benefit in terms of CO2 emissions and energy dependency when its impact on land and soil is taken into account (Russi 2008). Doubts have also been raised about staple food crops. Maize, in particular, has been regarded as not producing a worthwhile amount of energy when all the inputs are taken into con­sideration (IEA 2007). That said, it is one of the more efficient (others are wheat, sugar cane and sugar beet) biofuel crops in terms of reducing in CO2 emissions. On the contrary, the production of soya bean-based biodiesel releases substantial CO2, but has been pushed in the USA in recent years when other forms of oil-rich biomass are regarded as more environment friendly for biodiesel production (Pahl 2005).

Second-generation biofuel crops such as switchgrass, alfalfa, reed canary grass, Napier grass and Bermuda grass, which are mostly perennial, have fewer environmental impacts than first-generation crops. This is because the lower fertilizer input and less-intensive farming practices that these crops require help with respect to achieving greater reductions in GHG emissions (Karp and Richter 2011). In comparison with annual crops, perennial crops can have a positive effect on environmental quality and biodiversity (Sanderson and Adler 2008). In addition, as new technologies and processes for biomass production continue to mature and lead to the commercialization of second-generation biofuels, these biocrops are likely to revolutionize the biofuel industry (Ragauskas et al. 2006). Nevertheless, the environmental costs of biofuel feedstock are mostly viewed by biofuel proponents as either insignificant because of the limited economic and ecological value of existing vegetation and land uses, or worth bearing on account of the expected future benefits (MAPA 2006).

Lauro A. Ribeiro, Patricia Dias, Luis Felipe Nascimento and Patricia Pereira da Silva

Abstract Despite the challenges, depending on the local conditions and practices, renewable energy sources are already a significant contribution to the energy mix. Although this is true for electricity generation, the same does not apply for the trans­portation sector, where the available renewable sources are limited and still have a modest impact in the overall consumption. In this context, advanced biofuels such as microalgae are worldwide believed to be a better choice for achieving the goals of incorporating non-food-based biofuels into the biofuel market and overcoming land — use issues. Compared to other biofuel technologies, the most favorable factors for the cultivation of microalgae for the production of biofuels are they can be grown in brackish water and on non-fertile land, and the oil yield production is far supe­rior. Main challenges are currently the feasibility of large-scale commercialization, since the majority of economic and financial analyses rely on pilot-scale projects. Environmental issues are most likely to diverge opinions from experts. This chapter presents a review of microalgae cultivation (species, usage, processes, and culture) and biofuel production, highlighting advantages and challenges of algae biofuel.

L. A. Ribeiro (*)

School of Sciences and Technology, University of Coimbra and INESCC, R. Antero de Quental, 199, 3030-030 Coimbra, Portugal e-mail: lribeiro@inescc. pt

P. Dias • L. F. Nascimento

Management School, Federal University of Rio Grande do Sul, Av. Washington Luiz, 855, 90010-460 Porto Alegre, Brazil e-mail: patricia. dias@ufrgs. br

L. F. Nascimento

e-mail: nascimentolf@gmail. com

P. P. da Silva

School of Economics, University of Coimbra and INESCC, R. Antero de Quental, 199, 3030-030 Coimbra, Portugal e-mail: patsilva@fe. uc. pt

A. Domingos Padula et al. (eds.), Liquid Biofuels: Emergence, Development and Prospects, Lecture Notes in Energy 27, DOI: 10.1007/978-1-4471-6482-1_12, © Springer-Verlag London 2014

1 Introduction

Innovative technologies and sources of energy must be developed to replace fossil fuels and contribute to the reductions of emissions of greenhouse gases associated with their use. Biofuels are particularly important as an option by means of trans­portation that lack of other fuel options (especially trucks, ships, and aircrafts). However, alternative sources of biofuel derived from terrestrial crops such as sugarcane, soybeans, maize, and rapeseed impose pressure on food markets, con­tribute to water scarcity, and precipitate forest devastation. In this way, the sustain­ability of biofuels will depend on the development of viable, sustainable, advanced technologies that do not appear to be yet commercially viable.

In this perspective, algal biofuels are generating substantial awareness in many countries. In the United States, they may contribute to achieve the biofuel produc­tion targets set by the Energy Independence and Security Act of 2007. Likewise, in the European Union (EU), they may assist to the achievement of goals established in the recent Renewables Directive. In order to address the technical-economic barriers to the further development of this type of bioenergy, it is thus necessary to contribute with a study that incorporates biomass feedstock availability assess­ment, production, management, and harvesting in support of the upscaling of this promising technology.

Biodiesel and bioethanol are the two liquid biofuel options currently looked upon with more attention and under more vigorous development, since they can be used in today automobiles with little or no modifications of engines, for replac­ing diesel and gasoline, respectively. The Directive 2009/28/CE also targets the transportation sector fuels; in particular, each member state should reach a mini­mum 10 % share of renewable energy by 2020. Complementary, the Directive also states that this must be possible by using electricity and sustainable biofuels (i. e., based on a sustainable production). It also mentions that correct sustainability cri­teria should be adopted for biofuels, so that the rising world demand for biofuels does not destroy or damage land biodiversity and establish many others’ recom­mendations to ensure total sustainability of biofuels. An interesting point of this Directive is that, it recommends member states to incentive and support the use of biofuels that add supplementary diversifying benefits, such second — and third-gen­eration biofuels (e. g., biodiesel from microalgae or bioethanol from lignocellulosic materials). Some changes were recently proposed to the Directive 2009/28/CE (EC 2012), in particular dealing with the calculation of the carbon footprint, namely how to account for the ILUC (indirect land-use changes), and setting new goals deemed more adequate to promote the growing European biofuels industry.

In this context, the overall purpose of this literature review is to provide an inte­grated assessment of the potential of microalgae as a source to produce biofuels, while confronting it with competing emerging biofuel technologies. It is intended to provide a comprehensive state of the art technology summary for producing fuels and coproducts from algal feedstocks and to draw some insights into the fea­sibility and techno-economic challenges associated with scaling up of processes.

In Europe, most of the biofuel used in transportation is essentially sourced from biodiesel, which accounts for 78.2 % of the total energy content (10.9 mil­lion tons in 2011), as opposed to 21 % for bioethanol (2.9 million tons in 2011) (EurObserv’ER 2012).

Compared to USA and Brazil, and also to the European biodiesel sector, the EU fuel alcohol sector is rather small. Nowadays, the monthly production in USA is higher than the EU production per year. In 2008, a record in terms of imports in EU was registered. Total imports of bioethanol (fuel and non-fuel) are estimated to have reached 1.9 billion liters (increasing by 400 million compared to 2007), most of which (between 1.4 and 1.5 billion liters) came from Brazil (ePURE) (Shikida 2002; Ferreira Filho and Horridge 2009).

The EU is the world major player in biodiesel production with a share of 57 % of total world production in 2009. In the same year, biodiesel represented about 73 % of total biofuels produced in Europe (Biofuels-platform 2012).The European 2 Indirect land-use change (ILUC) can occur when land currently cropped for non-energy pro­duction is diverted for biofuel feedstock cultivation. The diverted crops must then be compen­sated for by converting other natural land, usually native systems (Ravindranath et al. 2009). Direct land-use change (dLUC) occurs when additional cropland is made available through the conversion of native ecosystems such as peatlands, forests, and grasslands, as well as by return­ing fallow or abandoned croplands into production. Particularly, when virgin land, such as rain­forest or peatland, is converted to agricultural land, the initial induced carbon losses can only be compensated after many decades of biofuels production (Ravindranath et al. 2009).

biodiesel industry consolidates its position at an international level despite a lower increase in its growth rate of production in 2010 when compared to previous years. For example, with a 9.5 million tons of biodiesel produced in 2010, EU bio­diesel production registered an increase of 5.5 % on the basis of the previous year. However, that stands below the increase in production of 17 % registered in 2009 and in the previous years (35 % in 2008). In 2011, the production decreased by 10 % when compared to 2010 (Fig. 5).

Currently, the production capacity of European biodiesel has reached approximately 22 million tons. The number of existing biodiesel facilities in July 2011 was 254 with a slight increase compared to 2009 due to the start of a few new production units (EBB 2011). This strong industrial basis is the result of considerable investments in biodiesel production planned before 2007. These investments are in reliance to the ambitious objectives for biofuels consumption given by EU authorities (EBB 2010). In 2011, Germany and France remained by far the leading biodiesel producing nations, while Spain confirmed its position of the third European biodiesel producer, ahead of Italy.

Within the EU, the first four largest biodiesel-producing member states that account for two-thirds of total production are Germany (33 % of total European pro­duction), followed by France (18 %), Spain (7 %), and Italy (5.6 %) (EBB 2013). Table 6 shows the biodiesel production and consumption of the countries of EU.

According to the European Biodiesel Board, in the first two-quarters of 2011, for the first time, the entire European production slightly decreased. Increased imports from third countries such as Argentina, Indonesia, and North America are mostly likely to have contributed to lessen European domestic production.

According to the EurObserv’ER (2012), biofuels consumption in transport con­tinued to increase in the UE at a slower pace though. It should stabilize at around 13.9 Mtoe in 2011 compared to 13.6 Mtoe of consumption in 2010. Thus, growth was only 2.7 % between 2010 and 2011, down from 13.9 % between 2009 and 2010, 24.6 % between 2008 and 2009, and 41.7 % between 2007 and 2008.

The biofuel market is very geographically concentrated, with a limited number of member states (Germany, France, Spain, Italy, UK, and Poland) representing over 78 % of EU-27 consumption.

The EU is the world’s largest biodiesel producer, consumer, and importer. The shift from tax incentives to mandates across Europe has been one of the key rea­sons for the growing amount of biodiesel imports. This shift can be attributed to a previous loss in fuel tax revenues for member states, causing a reduction of tax exemptions and compensation via mandates. Without tax exemptions, biodiesel was not price competitive against fossil diesel, even though the price of fossil

diesel increased. Under a mandate, fuel suppliers tend to opt for blending low-cost biofuels causing the increase of biodiesel imports (Ecofys 2011).

Imported biofuels in the EU come from a range of countries, with considerable changes in the list of countries from which the EU imported biofuels year by year, thus reflecting the impact that EU tariff preferences can have on such imports. This is demonstrated in Table 7 that depicts changes in EU biodiesel imports from 2008 to 2010 (European Commission, SEC 130 2011).

Looking at the trade volumes, in 2010, Argentina and Indonesia were the main exporters. The imports from USA and Canada reduced considerably regarding the previous years due to the application of the EU anti-dumping and countervailing duties for biodiesel.

The manner in which the economic stakeholders conduct their activities has increasingly distanced from the neoclassical conception, where the price system coordinates the markets. The new institutional economics (NIE) has for decades strived to demonstrate how the functioning of economics is influenced not only by economic and social institutions, but also by how the economic actors adapt to form governances or coordinate negotiations (Zylbersztajn 2005). In other words, formal and informal institutions strive to understand the processes in order to obtain efficiency in the business markets, including individual actions to coordi­nate business affairs in each market.

In the article “The nature of the firm,” Coase (1937), a researcher at NIE, pre­sents a firm as another area of resource allocation. Several works of Coase evi­dence the constant concern with the negotiations faced by a firm, pointing to specific interest on transaction costs (TCs) as a real barrier to market efficiency. Thus, if the company is a complex transaction unit, it is because the market and the overall business integration are not the only institutions that define economic efficiency, thus having to pay attention to the formal and informal agreements.

The ideas of Coase (1937) represented a step forward for economic studies, since until then the firm was known as a production function where inputs were transformed into end products. In the neoclassical view, the firm was an optimiz­ing entity, totally indifferent to its internal structure and its determining environ­ment, with the exception of prices.

According to the author, setting up the firm, represented by a set of agreements governing internal transactions, takes place because of the costs the actors to use in the price mechanism to organize production, given that this cost is related to discovering the relevance of the prices.

Thus, selecting the coordination mechanism to be used (firm or market) depends on the costs incurred, that is, the costs of discovering the prices prevailing in the mar­ket (information collection), the negotiation costs, setting up a contract, and the costs necessary to carry out inspections to ensure that the terms of the contract are met. The author designated these costs as TCs, thus explaining the existence of the firms.

The transaction concept is defined by Williamson (1993) as the transformation of an asset transferred across technologically separable interfaces. Zylbersztajn (1995) considers transactions as exchanges of property rights associated with goods or services.

“When people realize that what they want is more valuable than what they have (…)” (Barzel 1982, p. 27), transactions take place at any point of time and in any place.

However, as these transactions can take on a variety of forms, a completely sys­tematized framework is necessary to meet the objectives of such transactions. It is within this context that the institutions’ significance expands in order to enable coordinating the economic transactions, showing the limits of traditional analysis models and driving forward studies on transaction cost economics (TCE), the best known topic of NIE. Transactions, according to these approaches, will always be analyzed in a dual mode, which is the two agents under negotiation, the one that buys and the one that sells.

The theoretical framework of NIES deepens on the general concept of the firm, now as a set of agreements directing the internal transactions, rendering their anal­ysis more complex since it considers that the economic agents interact not only to reduce the production costs, as proclaimed by the orthodox economy, but also the costs related to the transactions.

According to Williamson (1975), TC can be defined as costs related to the mechanisms involved in the economic transaction, which are the negotiation costs, to obtain information, monitor performance along the chain, and ensure compli­ance with the agreements and also with recurring agreements. Thus, by includ­ing TC in the microeconomics analysis of the firm and of the markets, a series of costly procedures are considered before and after the negotiation, rendering a more complex nature to the business in terms of economic decisions. While the orthodox economic theory focuses on the process of determining the optimal allo­cation of resources by businessmen allegedly endowed with full rationality at deci­sion times, the objective of NIE is to identify the entrepreneurs’ best coordination method for their economic transactions in environments of uncertainty and, there­fore, the limiting forces for decision making (limited rationality). Thus, TCs are different from production costs as they depict how relationships are processed and not the technology used in a specific productive process. By breaking away from neoclassical economics, the individual preconized by NIE is not the same individ­ual as that of mainstream economy. “Homo economicus,” typified by a rational person with full information to maximize decision making for neoclassicism, is now defined by limited rationality and opportunism in an environment character­ized by uncertainty.

The concept of limited rationality was introduced as an important element of NIE by Williamson (1975) and preconized by Simon (1978). Richter (2001) and North (1990) refer to the individual’s cognitive limitations, who is not able to always be a maximizer despite wanting to be. Not much more can be added to this aspect since it is an unchallenged human condition. The mental shortcuts routinely used by economic agents for their market decisions are the first arguments for the problem of not achieving maximizing profits.

The theoretical framework of NIE discusses the role of institutions in two dif­ferent analytical levels: macroinstitutional and microinstitutional.

The part of NIE concerned with the relationship between institutions and eco­nomic development was the macroinstitutional type. From a macroanalytical point of view, the relationship of the institutional environment studied is composed of the economic, social, and political interactions and the individuals in a society. Thus, the importance of formal and informal rules and property rights is addressed by its contribution to the efficiency of the system.

As for the microanalytic type, focused on in this chapter, it addresses the under­standing of the rules governing specific transactions. Accordingly, TCE seeks to understand what factors drive up TCs and what mechanisms could be used to reduce them.

TCE enables to intensify the firm, now seen as a set of internal transactions governed by a set of contracts. This renders their analysis more complex, because the agents’ relationship is not only to reduce operating costs—as proclaimed by classical economics—but also to reduce TC—as suggested by NIE (Bonfim 2011).

TCE assumes that the question of economic organization is first of all a prob­lem of governance. Hence, it seeks to explain the different organizational forms that exist in the market and their contractual arrangements, highlighting the insti­tutional environment and its interaction with the organizations.

Williamson (1985), by proposing the firm as a governance structure of transac­tions, can determine if it will be a specific contract from a perfect market rela­tionship, if it will prefer a mixed form or if it will define the need for vertical integration, from the principles that minimize production costs (covered by neo­classical economics), added to the TC. For analytical purposes, the author pro­poses three basic governance forms, namely: [12]

Williamson (1991a, b) clarifies that hierarchy, market, and the hybrid form resulting from the combination of the former two are generic forms of economic organization. They are differentiated by their coordination and control mecha­nisms and their ability to respond to changes in the environment. Thus, the firm’s choice for governance structure—hierarchy, market, or intermediate form—will depend on the nature of the transactions. Williamson (1985) identifies three key attributes in transactions, determining the variation of TCs, namely frequency, uncertainty, and asset specificity.

Cellulosic biomass is the most abundant potential source for 1G ethanol. Cellulose is a polysaccharide present in the lignocellulosic cell wall structures of plants compris­ing also hemicellulose and lignin (Fig. 4, 5, and 6). Cellulose needs to be extracted from the lignocellulosic structure by chemical digestion, to decrease its recalcitrance

Fig. 5 Chemical structure of cellulose; the glucose units are linked by 1,4-|3-D bond. Author Silvio Vaz Jr

due to the presence of lignin, followed by a hydrolysis to release glucose. The glucose can then be fermented by S. cerevisiae yeast to produce 2G ethanol (Oh et al. 2012).

Examples of lignocellulosic biomass are sugarcane bagasse and wood. Table 5 presents the chemical composition of some different lignocellulosic biomasses.

Eucalyptus, barley straw, and corn cobs are good feedstocks for 2G ethanol production because of their high cellulose content (52.7 %). Nevertheless, euca­lyptus has a high lignin content (31.9 %), which is a barrier for cellulose recovery; this is less of an issue for corn cobs (14.7 %). Other factors that also determine the best feedstock are economic factors, such as distance from the biomass to the industry, feedstock costs, and processing costs. Sugarcane bagasse is one of the most widely used feedstock to produce 2G ethanol, particularly in Brazil, where integration with 1G ethanol production from sugarcane via a biorefinery concept, can increase the profitability of the operation.

2 Analytical Techniques Applied to Biomass Chains

Biomass chains and industry typically require the use of chemical analyses that can process a large number of samples at a low cost. Such assays are not restricted only to manufacturing, but are also required in research and development (R&D). Figure 7 shows the common steps in a bioenergy chain from harvest of the bio­mass to formation of the desired products, chemical analyses may be necessary at all steps within this chain.

The quality of the biomass used determines the product quality. Therefore, reliable information is required about the chemical composition of the biomass to establish the best use (e. g., most suitable conversion process and its condi­tions), which will influence harvest and preparation steps. Conversion processes should be monitored for their yield, integrity, safety, and environmental impact. Effluent or residues should be monitored and analyzed for environmental control. Coproducts need to be monitored to avoid interference with the product yield and product purity; however, coproducts are also a good opportunity to add value to the biomass chain. Finally, products need to be monitored and analyzed to deter­mine their yields and purity and to ensure their quality relative to a recognized quality standard.

The execution of a chemical analysis follows a generic process that consists of (Atkinson 1982): (1) sampling; (2) separation; (3) detection (or measure); and (4) interpretation of results. Thus, before discussing the application of techniques, it is appropriate to consider these operations according to their status or involvement in the analysis. The location of analyte on the matrix (or inner surface) and the physical status of the sample (analyte plus matrix) defines the extraction technique used (partition, ion exchange, affinity, size exclusion filtration, etc.). The amount of sample, its purity, the type of information sought (atomic or molecular level) and its use (quantitative or qualitative) defines the detection technique. The analyte concentration has a direct influence on the techniques of extraction and detection.