Bioethanol in Ecuador

In 2010, in the province of Guayas, the Ecopaís pilot plan began with the purpose of testing the E5 fuel mixture, comprised of 5% (v/v) of bioethanol and 95% of gasoline, which ended in the year 2014 (^{Paredes, 2015}). In 2016, the proposal was to extend the use of E5 to the entire country and, later, increase the percentage of bioethanol in the mix to 10 and 15%, to replace the demand for extra-type gasoline in 2019 entirely. This type of gasoline represents 79% of the gasoline consumption and around 46% of the demand for liquid fuels in the country by 2014 (^{Ministerio Coordinador de Sectores Estratégicos, 2015}). For this, the production of bioethanol should increase by a figure close to 200% in the period 2017-2019 (figure 1), which shows the magnitude of the challenge to overcome and to which this study aims to contribute by proposing an alternative production route of bioethanol to the one commonly used based on sugarcane cultivation (^{García et al., 2013}).

Source: Elaborated by the authors based on ^{Paredes (2015)}

Figure 1 Current and projected production of bioethanol in Ecuador (Mml) 

Studies in Ecuador on the production of bioethanol have considered different types of biomass: ^{García et al. (2014)} estimated the potential for bioethanol production from agricultural residues of rice, banana, and sugarcane, and were supported by a predictive model and by locating the production plants according to the energy potential of the region. For their part, ^{Prado and Cervantes (2017)} analyzed the main variables that affect the cultivation of sugarcane for the production of bioethanol; these authors concluded that the planted area is the variable with the highest incidence in crop efficiency. ^{Guerrero and Muñoz (2018)} used the life cycle approach to estimate environmental sustainability and demonstrate the ability to reduce greenhouse gases (GHG), with favorable results in both cases. Unproductive species have also been studied, such as the Peruvian feathergrass, paja ichu or paja de páramo (Stipa ichu) as a primary source for the production of bioethanol with promising results (^{Albarracín et al., 2015}).

Likewise, the potential of a specific crop and province has been estimated. In the province of Chimborazo, the production of bioethanol from potatoes has been evaluated. This alternative use has been assessed in response to the overproduction of this crop, which causes a 50% decrease in the commercialization price and even the use of waste or out-of-specification products (^{Pérez et al., 2017}). Finally, in the province of Imbabura, the production of bioethanol from corn waste has been studied (^{Hernández-Rueda et al., 2018}).

Regarding the use of residual cacao biomass for energy purposes, ^{Kuglarz et al. (2018)} evaluated the potential for biogas production by anaerobic digestion for the Balao canton, a region with the highest residual cacao biomass production density. In this canton, biogas is used for electricity generation that could satisfy 88% of its energy demand.

From this documentary review, it can be seen that the study of the use of cacao residues for the production of bioethanol has not been studied much in Ecuador, such as the use of kinetic models to estimate the potential for bioethanol production of a specific lignocellulosic residue. In this context, the aim of the current work was to estimate the theoretical potential of bioethanol in Ecuador from the residues of the cacao husks through acid hydrolysis and fermentation. To this end, a mathematical simulation model was formulated based on official information on national cacao production and the application of Seaman's kinetic model.

The purpose was to contribute to the basic knowledge on an alternative route of bioethanol production in Ecuador, strategically convenient and that also allows the valorization of an agro-industrial waste positioned in fifth place in the country related to the generated volume and energy content (^{Ministerio de Electricidad y Energía Renovable, 2014}). The main result was the identification of the provinces of the country with an attractive bioethanol production potential to carry out more detailed feasibility studies that include environmental and economic dimensions. All these elements constitute the main contribution of the work.

Estimation of bioethanol production potential

The estimation of bioethanol theoretically obtainable from the residual biomass of cacao in Ecuador is carried out in three stages: (i) establish the amount of cacao husk residues generated annually in the provinces of the country, and determine the amount of corresponding cellulose based on the lignocellulosic analysis; (ii) quantify the glucose generated in the hydrolysis of the cacao husks applying the kinetic model of ^{Saeman (1945)}, and (iii) estimate the production of bioethanol by fermentation of the glucose generated in the provinces and regions of Ecuador.

Amount of residual cacao husks in the provinces and regions of Ecuador

The Bioenergetic Atlas of Ecuador is the primary source of information on the amount of residues from cacao cultivation, estimated at 2,015,353 t/year for 2014 (^{Ministerio de Electricidad y Energía Renovable, 2014}). Its geographical distribution (figure 2) shows that the provinces of the coastal region are the ones with the highest contribution, with approximately 87% of the total waste.

Source: ^{Ministerio de Electricidad y Energía Renovable (2014)}

Figure 2 Geographic distribution of the cacao cultivation residues in Ecuador 

The residues corresponding to cacao husks represent 14.32% (by weight) of the total residues of this crop (^{Sánchez, 2013}), equivalent to 288,580 t/year. In figure 3 are shown the regions and provinces with a significant contribution to generate energy. The eastern region has been divided into two subregions: Oriente Norte [West North], comprised of the provinces of Napo, Orellana, and Sucumbíos; and Oriente Centro-Sur [West Center-South], formed by the provinces of Pastaza, Morona, and Zamora.

Source: Elaborated by the authors

Figure 3 Residues of cacao husks (t/year) in the main provinces and producing regions 

The cellulose fraction present in the cacao husks, in dry weight, is the basis for calculating the amount of cellulose and is taken as the average of the values reported in various studies (table 1).

Table 1 Percentage of cellulose in cacao husks 

Source: Elaborated by the authors

The amount of hydrolyzable cellulose generated in the provinces and regions of Ecuador is obtained from equation 1 and is shown in table 2.

Equation 1

Table 2 Cellulose in cacao residues in selected provinces and regions 

Source: Elaborated by the authors

Kinetic modeling of cellulose hydrolysis

The reaction of cellulosic materials with acids is complex: on the one hand, the different series and parallel chemical reactions that take place, and, on the other hand, the presence of two phases in them. Therefore, the global reaction mechanism has not been entirely established due to the practical difficulties of measuring the reaction rate of individual reactions (^{Carrasco & Roy, 1992}). In this situation, an approach to understand and predict the behavior of the acid hydrolysis reaction in the crystalline fraction of cellulose is to consider it as a first-order pseudo-homogeneous reaction, with apparent rate constants.

The pioneering development of this approach is carried out by ^{Saeman (1945)}, supported by experiments on the degradation of wood at moderate temperatures with diluted sulfuric acid. Its model has been used for various types of residual biomass and operating conditions (^{Carrasco & Roy, 1992}; ^{Thompson & Grethlein, 1979}) and has also been applied to the hydrolysis of the hemicellulose fraction (^{Lu et al., 2008}; ^{Téllez et al., 2002}).

This model is used to establish the amount of glucose obtained from the cellulose present in the residues of the cacao husks and considers that glucose is the sugar with the highest interest in lignocellulosic hydrolyzates, and from whose fermentation bioethanol is obtained (^{Paredes, 2015}).

Reaction rate

The simplified schematic representation of the hydrolysis of cellulose is as follows:

The solution of this reaction system, for zero initial conditions, is C_A = C_B = 0, and is represented like this:

Equation 2

Equation 3

Equation 4

Where k₁ is the rate constant in glucose production (s^-1); k₂ is the rate constant in the breakdown of glucose (s^-1); C_A is the cellulose concentration (%); C_B is the glucose concentration (%), and C_A0 is the initial cellulose concentration (%).

By mathematically manipulating equations 2 and 3, the expressions for the maximum glucose concentration (C_Bmax) and the time it takes to occur (t_max) are obtained. These are useful for calculating the maximum efficiency of the conversion of cellulose to glucose and the amount of bioethanol generated through fermentation.

Equation 5

Equation 6

The mathematical expressions of the constants of the reaction rates and the numerical values of the parameters present in them must be established to complete the kinetic model. In the first case, compliance with Arrhenius's law has been corroborated in several experimental studies. Furthermore, considering Saeman’s model, in the pre-exponential factor, a term that quantifies the effect of the diluted acid concentration is incorporated (^{Aguilar & Canizales, 2004}; ^{Suárez et al., 1985}; ^{Thompson & Grethlein, 1979}). Its generic mathematical expression is shown below:

Equation 7

Where C_s is the concentration of diluted sulfuric acid (%).

In the second case, to specify the values of the parameters k₀, n, and E (equation 7), associated with the hydrolysis of the cacao husk residues, a documentary search was carried out without favorable results. However, considering the purpose of this study, the quantification of bioethanol that would be obtained theoretically from the processing of the cacao husks available in Ecuador, the values of these parameters reported in ^{Carrasco and Roy (1992)} were taken for the hydrolysis of wheat straw. This selection was made under the following considerations: (i) the similarity in the cellulose content of both species, 38.7% and 37.2% for cacao and wheat straw, respectively, and (ii) equality under operation conditions, such as temperature and concentration ranges of diluted sulfuric acid. Therefore, these are the expressions for the rate constants:

Equation 8

Equation 9

^{Carrasco and Roy (1992)} recommended empirical models to simulate the hydrolysis mechanisms of lignocellulose materials. From this, ^{Aguilar and Canizales (2004)} established the k₁ and k₂ values based on experimental data obtained from acid hydrolysis, where k₀ and E were statistically determined using least squares regression.

With the previous equations, the kinetic model is completed and will serve as a mechanism for calculating the glucose produced from the residual cacao biomass and, later, in the bioethanol obtained.

Glucose production

The procedure for calculating glucose production is based on determining the operating conditions that allow obtaining the maximum conversion of crystalline cellulose to glucose and its minimum conversion to third products or degradation products, is comprised of the following steps:

Bioethanol estimation

Equation 10 is used to calculate the bioethanol resulting from the fermentation of glucose with a theoretical yield (Rtp) of 0.49 g ethanol/g glucose, i.e., an average value used in other studies (^{Albarracín et al., 2015}; ^{Ballesteros et al., 2004}).

Equation 10

where VE is the ethanol volume, l/year; 𝜌, bioethanol density, 790g/l; 1E⁶, the conversion factor from grams to tons, and C_p is cellulose by province, t/year.

It should be mentioned that the estimation of ethanol production is carried out for ideal conditions or theoretical yields for the fermentation stage in the global ethanol production process. Therefore, it is expected that the actual production that will be obtained will be less when considering the yields and efficiencies in the handling, adaptation, and conversion processes involved in the overall process. From the literature review, no values have been found on the efficiency of the global process for obtaining bioethanol for the residual biomass studied. Only the values of the global yield of bioethanol production from other biomasses, such as rapeseed straw of 12.2% (^{Kuglarz et al., 2018}) and olive oil residues of 11.8%, can be referenced (^{Solarte et al., 2019b}). Both percentages were calculated in terms of the ratio of the bioethanol weight respect to the initial raw material weight. In this scenario, the need to carry out experimental cutting studies is appreciated allowing to obtain specific and conclusive information on this bioethanol production route, which considers the yields and efficiencies of the global process from the suitability of the raw material to the purification of bioethanol in vehicle fuel grade.

Kinetic model

The dynamics of the change of reactants and products for T = 190 °C and Cs = 1% (figure 4) shows behavior following the kinetic theory for irreversible reactions in series with k₁ >> k₂, and also with the results of several similar studies for other types of residual biomass (^{Suárez et al., 1985}; ^{Thompson & Grethlein, 1979}). Also, in figure 4, the maximum operating point (t_max, C_Bmax) can be located. The continuous growth of degradation products and the existence of a maximum value of the glucose concentration indicate the need to ensure that the process operates around this operating point.

Source: Elaborated by the authors

Figure 4 Dynamics of the cellulose hydrolysis reaction 

Table 3 presents the results of the procedure followed to establish the maximum conversion to glucose for the specified initial conditions. The high sensitivity of the optimum point value is appreciated (t_max, C_Bmax) with temperature.

Table 3 Summary of the results of the kinetic model for C_s =1.5 s% 

Source: Elaborated by the authors

One aspect to analyze is having reached the optimal point of glucose yield for the most rigorous (or extreme) operating conditions. Nonetheless, these also favor its decomposition to products that could interfere with the alcoholic fermentation, which means that there is a compromise relationship between opposing effects. Another aspect to consider is the decrease in residence time as operating conditions increase in value until reaching a very short residence time of the reaction mixture, very difficult to implement in practice for a scale larger than that of the pilot. Also, in economic terms, the cost of neutralization increases with increasing acid concentration.

The large increase in the reaction rate of glucose with the acid concentration, which reaches increases of over 100% in C_B, are in correspondence with those obtained in similar studies. Mathematically, these are explained by the strongly non-linear nature of the reaction rate caused by the product of a power-type term with another of an exponential type.

Glucose production

The glucose production for T and C_s ranges are presented in table 4. The effect of both variables on C_Bmax is notorious due to the non-linear nature of the relationship of each variable with C_B, so the effect of T is higher due to its exponential variation, in contrast to the power-type variation of C_s. Clearly, the maximum maximorum corresponds to the highest values of the range of T and C_s, which is T = 120 °C and C_s = 1.50 %, with which a C_Bmax = 11.95 % is obtained. It should also be noted that a more representative indicator of the increase in the conversion of the variable of interest consists of measuring the degree of conversion with respect to its initial value; thus, for the C_Bmax value of 11.95 %, the conversion percentage is 32 %.

Table 4 Maximum glucose for different concentrations of H₂SO₄ and temperature 

Source: Elaborated by the authors

Glucose by province

The glucose produced annually in each province (table 5), corresponds to the highest value of C_Bmax according to the cellulose available in each province (table 2). The provinces of the coastal region (Guayas, Los Ríos, and Manabí) are the ones with the highest contribution, representing 71 % of the national glucose production, which will be repeated in the production of bioethanol.

Table 5 Glucose generated in each province 

Source: Elaborated by the authors

Bioethanol production

It is obtained from equation 10, and its quantities for the country and provinces are presented in table 6. The first value, 8.28 Mml, is equivalent to 10% of the national production of bioethanol for the year 2017 (^{Martínez, 2017}). However, a more appropriate comparison results from comparing production for the same base year (2014). In this case, bioethanol from residual cacao biomass represents about 56% of the bioethanol production from sugarcane processing. However, it should be noted that bioethanol production has experienced an average inter-annual growth of 80 % in the 2014-2017 period (^{Martínez, 2017}).

Although this study represents a theoretical model, the amount of bioethanol generated could vary depending on the lignocellulose substrate that is used, knowing that the yield has been based on a traditional fermentation process.

Table 6 Amount of bioethanol generated from cacao residues by province 

Source: Elaborated by the authors

Production of Ecopaís E5 gasoline

The volume of E5 gasoline that would be obtained using bioethanol is 166 Mml. In comparison, the total production for the year 2017 was around 1,688 Mml (^{Ministerio Coordinador de Sectores Estratégicos, 2015}), which means that the gasoline obtained by mixing bioethanol would contribute with around 10 % of the national production. However, a more pertinent assessment of the contribution of E5C gasoline from cacao bioethanol is to consider 2014 as the basis for comparison, bearing in mind that this is the year where the residual biomass was quantified. In this case, the contribution of E5C gasoline corresponds to 56 % of the national produced for that year.

Another dimension to assess the alternate E5 gasoline production route proposed in this study is the provincial level. Thus, when comparing the values of E5C gasoline with respect to the consumption of the three provinces with the highest contribution: Guayas, Los Ríos and Manabí (table 7), it can be observed that in these provinces the substitution of the super gasoline for the E5C mixture has a significant impact, starting from the volumes of gasoline replaced instead of its corresponding percentage, i.e., 118 Mml, which would make it attractive to undertake more detailed studies that include the economic and environmental dimensions.

Table 7 Substitution percentage of the super gasoline for E5C in the selected provinces 

Source: Elaborated by the authors