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Supercritical CO2 extraction of essential oil from orange peel; effect of the height of the bed
Journal of Supercritical Fluids 18 (2000) 227 – 237 www.elsevier.com/locate/supflu
Supercritical CO2 extraction of essential oil from orange peel; effect of the height of the bed A. Berna a,*, A. Ta´rrega b, M. Blasco b, S. Subirats b b
a Department of Chemical Engineering, Uni6ersity of Valencia, 46100 Burjassot, Valencia, Spain AINIA, AgroFood Technological Institute, Apdo. 103, Parc Tecnolo`gic, 46890 Paterna, Valencia, Spain
Accepted 7 July 2000
Abstract The influence of the height of the particle bed on the kinetics of supercritical fluid extraction (SFE) of essential oil from orange peel is analyzed in this article. Peel of dehydrated oranges of the satsuma and naveline cultivars was used. A series of experiments were designed wherein, for the same conditions, particle height varied widely. These experiments were also carried out on different scales with extraction volumes of 0.5 and 5 l. The results of the experiments were interpreted using Sovova´’s extended flow model as has been done in previous studies. The bibliography indicates that a number of phenomena may distort the process. One of these phenomena is the formation of masses of particles, due to their oil content, which increases resistance to mass transfer inside the particle. However, this phenomenon was barely noticeable in our experiments. Also, some reordering of the particles may take place due to the differing densities of the two phases and a certain drag effect exercised on the particles by the fluid. This situation can cause a lack of homogeneity in the fluid, further reducing the effectiveness of the process. In the experiments with the satsuma cultivar, where the bed-height range was broader, a base of diatomaceous earth was added in the extractor in order to reduce the lack of homogeneity in the fluid flow. Very similar behavior was found in all the experiments and we can, therefore, conclude that where there is homogeneous flow the height of the bed has very little effect, at least on the same scale of operation. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Orange essential oil; Supercritical fluid extraction; Modeling; Effect of bed height; Carbon dioxide
1. Introduction Supercritical fluid extraction (SFE) is a technique that makes use of the high solvent ability of supercritical fluids (SF), which combine the solvent capacity of liquids with the mobility of gases. * Corresponding author. Fax: +34-6-1318008. E-mail address: [email protected] (A. Berna).
This is due to the fact that the density and viscosity of these fluids lie midway between those of a gas and those of a liquid. Moreover, the diffusivity of these fluids tends to be much higher than that of liquids, thus allowing increased extraction rates. Their properties also vary widely with operating conditions (pressure and temperature), facilitating the adjustment of the solvent effect. In recent years considerable effort has been
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devoted to researching these processes and increasing the number of applications for them [1 – 7]. Many of these applications were to oil extraction [8–11]. Oranges are one of the main products of the Valencian region. In 1995 production reached over 3400 Mkg. Such production levels tend to saturate the market and a significant proportion of output is, therefore, processed to obtain juices, marmalades and so on. Thus, in 1995, 40% of the region’s output was used by the citrus derivatives industry. The processing of oranges produces a series of by-products. One of these is the peel, from which a variety of products, including essential oil, can be obtained. Orange essential oil is used to add the aroma from the orange to products such as carbonated drinks, ice creams, cakes, air-fresheners, perfumes, etc. [12–14]. Other applications make use of the germicidal properties of some of its components. Small amounts of D-limonene can have an important effect on wastewater as a germicide treatment [15]. Carotenoid pigments, which are also present in orange peel extracts, are important for the health, not only for their nutritional value as vitamin A precursors, but also for their antioxidant and anticarcinogenic properties [16]. These components are also used as food coloring. In spite of their potential significance, there exist few studies dealing with the extraction of essential oils from citrus fruit in general [17] and from orange peel in particular [18]. There are more studies on the deterpenation of these oils available [19–26]. This is probably due to the fact that the traditional procedures are very quick and economical, although they do not allow selective extraction. In principle, supercritical extraction can give rise to the fractionation of the essential oils, reducing or eliminating the terpene fraction responsible for the deterioration of these oils. We studied the application of SFE techniques to the extraction of essential oils from orange peel. Our studies analyzed the effect of operating conditions on the solubility of orange essential oil [27], and the effect of particle size and solvent flow on the extraction rate [28]. One of the most salient aspects of the latter study was that it showed the effect of particle size on the composition of the extract.
Various authors have also studied the influence of pretreatments on the kinetics of extraction. More specifically, the effect of the moisture of the raw material (orange peel) has been considered by Mira [29]. A similar study, although involving a different type of oil, was carried out by Snyder et al. [30]. The extraction curves were modeled using Lack’s extended plug flow model as adapted by Sovova´ [31,32]. This model takes into account the solubility of the extract (yr) in the solvent and the mass transfer coefficients both in the flowing phase (Z= Z[kf]) and in the solid phase (W= W[ks]). It also considers that the solute is evenly distributed throughout the matrix that contains it. In spite of this uniformity, two fractions of the same solute are considered; an easy-access fraction, which is the most superficial one, and a difficult-access fraction, which is in the nucleus of the particle. The mass transfer parameters Z and W can vary with particle size, but only Z will vary with solvent flow. By analyzing the data from the experiments we can identify the parameters of the model: yr, xo, xk, Z and W. yr represents the apparent solubility of the solute, xo and xk represent total initial solute content and initial difficult-access solute, respectively. The first parameter depends mainly on operating conditions (P and T). The second and third parameters will depend on the raw material and the selected particle size. The parameter for mass transfer inside the particle (W) can vary with particle size and the parameter for mass transfer in the fluid (Z) will depend on solvent flow, particle size, the properties of the fluid and the bed height. Parameters yr, xk, Z and W are of great interest when scaling up the process, since they contribute useful information for equipment design and for the selection of optimum operating conditions. The selected model presents the difficulty of requiring a large number of parameters that have to be adjusted based on information from the experiments. Nevertheless, some of these parameters could be established using information from independent experiments. We refer to solubility and the initial composition of the raw material. The advantage of this model is related to the
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inclusion of possible internal and external resistances to mass transfer, as well as the distribution of the solute inside vegetable matrices. Nevertheless, this model may fail to represent some phenomena, such as the possible adsorption of the product by the matrix [3]. The objective of the laboratory scale research is to facilitate the design of an industrial plant, which would involve determining the optimum operating conditions taking into account the quality of the product, and the yield and economy of the process. Such research can be carried out on laboratory or pilot scales, although it should not be assumed that scale-up will be a simple process since phenomena that are so insignificant as to be imperceptible at a reduced scale may become significant at production scale. In the bibliography there are a number of texts dealing with scale-ups in chemical industry processes [33], and some approaches for supercritical fluid extraction [34 – 37]. The proposed model has demonstrated its usefulness for representing different situations with different raw materials, provided they fit the basic ideas of the model, particularly with regard to the distribution of the solute in the matrix. The effect of the height of the particle bed is not specifically contemplated in this model and it has been little studied. It may be apparent in the amount of raw material and the mass transfer coefficient of the fluid phase. The estimation of mass transfer coefficients in systems with packing is dealt with in general mass transfer books. The effect of bed height is considered only in relation to certain procedures. For example Coulson et al. [38] and Perry et al. [39] reported some studies that take it into account. These studies show the effect of bed height on HEPT (height equivalent to a theoretical plate). Some of the proposed correlations show that HEPT is proportional to z 1/3 or z 1/2, where z is the height of the bed; that is to say, the mass transfer coefficient must decrease in the same way. This effect is not considered in other correlations. It seems interesting to approach our study as preparatory work for scale-up. Sovova´ et al. [32] studied the effect described above using two series of experiments on a small scale: an extractor of 12
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ml and feed between 1 and 4 g, and an extractor of 150 ml with feed between 2 and 17 g. In these experiments there occurs a decrease in the effectiveness of the process when the amount of feed is reduced. This was evident in the case of the experiments with smaller supplies of raw material, but its effect was smaller in the rest. The interpretation of these results suggested the existence of a certain channeling of the fluid, which the authors represented by dividing the bed into n equal parallel sections. The modeling of the channeling phenomenon can be approached by representing the flows circulating via these sections as non-homogeneous. If we call the amount (kg) of solid feed free of solute M, in each section one will have M/n kg of solid free of solute. The flow rate of fluid (kg/s) that circulates for each section will be Qj, a fraction (aj) of the total flow rate Q. The following must be true: n
% Qj = Q
Qj = ajQ
j=1
n
% aj = 1
(1)
j=1
The specific flow rate of the fluid in each section (qj) will be related to the total (q): q; j = nQj/M=najq;
(2)
and the dimensionless amount of solvent passed through the jth section in the time t is: q; j = q; jt= najq;
(3)
The dimensionless amount of extract obtained from the jth section of the bed can be calculated with the equations of the model (Eqs. (1)–(8), in Mira et al. [27]) substituting qj for q. The overall dimensionless amount of extract obtained will be: n
e(q; = q; t)= % ej (t)/n
(4)
j=1
The lack of homogeneity of the fluid flow in the bed is represented by s.
n
s = % (naj − 1)2/n j=1
n
0.5
(5)
which is a measurement of this phenomenon. This information can be used to quantify the lack of homogeneity, but not to make predictions about the process.
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The objective here is to approach the study of the effect of the height of particles on the rate of the process with a different raw material (dehydrated orange peel) and larger equipment than that used in the above-mentioned study. In this way, we intend to test whether the model can be applied to systems in which the amount of solids used for extraction is very different. Moreover, we wish to determine if it is possible to approach the scale-up with the mentioned model or whether, on the other hand, it needs to be supplemented with other information on the phenomena associated with the amount of raw material.
2. Materials and methods The oranges used in this study were Citrus sinensis (L.) of the naveline and satsuma cultivars. In both cases the fruit was ripe. The naveline variety was selected because it is produced in volume and the satsuma because it is so frequently used for processing. Samples of the satsuma variety were obtained from a citrus co-operative (Agriconsa, Valencia, Spain) and oranges of the naveline cultivar were obtained from a local producer in Gandı´a (Valencia, Spain). Oranges of the naveline cultivar were peeled by means of an industrial procedure that separates the external part (flavedo), leaving 20% of the weight of the fresh product. Oranges of the satsuma cultivar were peeled manually by the co-operative supplier. The drying procedure and the characterization of these materials were described in a previous report [27]. The final moisture of the samples was 0.084 and 0.150 (kg H2O/kg m.s.) in the satsuma and in the naveline peel, respectively. The solvent used was dry CO2, supplied by Abello´-Linde (Valencia, Spain). It was over 99% pure. The operating conditions were 313 K and 200 bar (20 MPa). The selected solvent flow was 1 kg/h in the pilot scale experiments and 20 kg/h in the production scale experiments. The amount of orange peel used in each experiment varied between 0.045 and 0.145 kg in the pilot scale experiments and between 0.920 and 2.200 kg at production scale. Some of these experiments were also designed to study the scale-up of the process.
In this case, a scale relationship of 20 was applied for the amount of raw material and for the flow rate. Results of previous studies [27,28] were used as a guide in selecting operating conditions. Pressure was set at 20 MPa in order to allow extraction of a significant fraction and at the same time to facilitate the extraction of oxygenated compounds. The selected temperature is relatively low to avoid the deterioration of the extract and also to facilitate control of the process. The experiments were carried out on two different sets of equipment, one for the pilot-scale and another for the production-scale experiments. The pilot unit with an effective capacity of 0.36 l (SFE-500, SEPAREX) is described in a previous study [27]. We also used a set of equipment of our own design, with an extractor of approximately 5 l that also has two separation units, a cyclone and a decanter. This equipment is considered to represent production scale for the purpose of comparison. The amounts of the satsuma and naveline cultivars to be used were established as follows: in the pilot-scale experiments with the naveline cultivar two amounts corresponding to 50 and 70% of total capacity, respectively, were used. In the pilot-scale experiments with the satsuma cultivar a wider range of total capacity was studied (from 30 to 95%). The production-scale experiments were an adaptation of the pilot-scale experiments. Some relationships (q; and q) were kept constant and a scale factor was introduced. This procedure was proposed by Clavier et al. [35]. As has been pointed out previously, q; and q are the specific flow rate of the fluid (kg CO2 kg − 1 solute-free feed s − 1) and the dimensionless relationship between the amounts of solvent and raw material used in each experiment (kg CO2 kg − 1 solute-free feed), respectively. Twenty was selected as the scale factor for the amount of raw material. The conditions under which the experiments corresponding to the different scales and cultivars were conducted are shown in Table 1. The productionscale experiments that were adaptations of the pilot-scale ones are indicated with the same letter in capitals in Table 1.
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237
where N is the number of experimental points. This OF is on an absolute value basis, and has been used in a comparative way.
Extraction kinetics were recorded through periodic measurement of the weight loss of the orange peel. The procedure was described in a previous work [27]. A base of diatomaceous earth was used in the experiments with the satsuma variety. This base was added in order to achieve homogeneous fluid flow. A procedure of least square has been used with the Solver function of the Excel-97 spreadsheet to identify the parameters of the proposed model. The objective function that had to be minimized was:
3. Results and discussion The results of the four series of experiments are shown in Figs. 1–4. They were carried out with the satsuma and naveline cultivars, and the only difference among the experiments in each series is the height of the bed of particles. These results are, partly, similar to those of the above mentioned authors [31,32]. The rate of the process increases slightly with the amount of the raw material.
N
OF= % (eexp −ecalc)2n/N
231
(6)
n=1
Table 1 Equipment and raw materials used for the study of the effect of the height of the beda a) Equipment Scale
Pilot
Volume (l) Diameter (cm) Height (cm)
Production
0.36 5.50 15.0
5.18 13.0 39.0
b) Culti6ars b1) Na6eline culti6ar Series Flow rate (kg/h) Time (h) Scale
1N 1 7 Pilot
2N 20 7
Experiment
a
Production b
A
Feed (g) Height of bed (cm) q; (kg/kg h) q (kg/kg)
109 10.4 10.2 72.5
80.4 7.7 14.0 97.9
b2) Satsuma culti6ar Series Flow rate (kg/h) Time (h) Scale Experiment
1S 1 2.5 Pilot c
2S 20 2.5
Feed (g) Height of bed (cm) q; (kg/kg h) q (kg/kg)
148 14.1 7.1 17.9
a
Operation conditions (40°C and 20 MPa).
d 100 9.5 10.6 26.4
B
2199 37.7 10.3 72.4
e
1630 28.0 13.9 97.6
Production E
f 69 6.6 15.4 38.6
46 4.3 23.1 57.9
1380 23.7 15.2 38.0
F 919 15.7 22.8 56.9
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Fig. 1. Kinetics of the extraction of essential oils from orange peel (naveline cultivar). Experiments carried out at 40°C and 20 MPa, pilot scale and different amounts of raw material, 109 g (1Na); ×80 g (1Nb); — model.
Fig. 2. Kinetics of the extraction of essential oils from orange peel (satsuma cultivar). Experiments carried out at 40°C and 20 MPa, pilot scale and different amounts of raw material, 148 g (1Sc); × 100 g (1Sd); 69 g (1Se); + 45 g (1Sf); — model.
The results of the experiments were interpreted using the proposed model. Initially, all the data for each series of pilot experiments on both cultivars were adjusted simultaneously. This allows us to test the capacity of the model to incorporate the effect of the height of the bed. The results of the adjustment are shown in Table 2 and in Figs. 1 and 2. As can be seen, the model represents the results of the experiments appropriately. However, it shows a series of differences and possible incoherences with the physical implications of the parameters. Thus, the solubility figure changes from one series of experiments to another. The mass transfer coefficients for the two phases also vary. One can explain the differences between the solubilities (yr) of the essential oil obtained from
Fig. 4. Kinetics of the extraction of essential oils from orange peel (satsuma cultivar). Experiments carried out at 40°C and 20 MPa, production scale and different amounts of raw material, 1380 g (2SE); ×919 g (2SF); — model. Table 2 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/pilot
Fig. 3. Kinetics of the extraction of essential oils from orange peel (naveline cultivar). Experiments carried out at 40°C and 20 MPa, production scale and different amounts of raw material, 2199 g (2NA); ×1630 g (2NB); — model.
Naveline/pilot
yr 102 xo 102 xk 102 Wq; 104 Zq; 102
1.32 5.80 4.47 4.33 517
1.93 12.6 6.44 2.11 5.12
OF 106
8.6
16.2
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model.
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237 Table 3 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/production
yr 102 xo 102 xk 102 Wq; 104 Zq; 102 OF 106
1.32 5.80 4.47 4.33 0.10 12.2
Naveline/production 1.93 12.6 6.44 2.11 0.12 710
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model. The first four parameters are the parameters of the pilot scale in Table 2.
the two cultivars, because their composition is different. The differences in the parameters relating to overall composition (xo and xk) illustrate this. The different value of the mass transfer coefficient of the solid phase (Wq; ) may be related to the differing oil content of the raw material and its differing distribution. This parameter represents the ease with which the solute is transferred in the solid phase. In this sense it will be related to the xk parameter. When the weight of the fraction of difficult-access solute (xk) increases and the particle size is the same, transfer will be easier, and the mass transfer coefficient will increase, because solute is closer to the surface. The satsuma cultivar, which has lower essential oil content, has an xk value that represents 77% of the total content, while the naveline cultivar, which has higher oil content, has an xk value representing only 51% of the total. As we assume that solute is evenly distributed it would appear that the difficult-access solute is deeper in the naveline cultivar, making it more difficult to extract. This would explain the lower Wq; value in this cultivar. A higher xk value may also be related to the formation of masses of particles. This possibility is small in the case of the satsuma cultivar because of its lower oil content, and seems a little more probable at pilot scale perhaps due to the lower flow rate. The opposite is true in the case of the naveline cultivar due to its higher oil content. The
233
possibility of the formation of masses of particles is greater at production scale where there are more solid particles. The differences in the values of the mass transfer coefficient for the fluid phase (Zq; ) are more difficult to explain because this parameter takes into account the ease with which solute transfer takes place in the fluid phase. It will be influenced by flow rate, height of the particle bed and particle diameter. The differences between the two series of experiments do not justify these different values. They may be the result of compensation among parameters. In order to make the model more meaningful and attempt to extend the results from pilot to production scale, we identified the parameters for the experiment data at production scale. When making this adjustment we assumed as common to each cultivar the first four parameters (yr, xo, xk and Wq; ), and we selected for them the values obtained at pilot scale. In the satsuma variety these parameters represent the behavior of four experiments. We tried to adjust the production scale experiments using Zq; . The results are shown in Table 3. The objective function is worse than in Table 2. The dramatic increase in this function for the naveline variety should be noted. It may be related to the fact that in this case the base of diatomaceous earth was not added to homogenize the fluid flow. This effect may have distorted the process and produced the difference between the scales. The loss of quality of the modeling in the satsuma variety is less pronounced. The adjusted parameter shows a significant decrease in both cases, which is related to the increase in the height of the bed. To increase the quality of the representation a further adjustment of the production-scale data was carried out based on the pilot-scale results. In this case we assumed as common to each cultivar only the first two parameters (yr, xo). It seems more realistic for solubility and composition of the raw material to remain the same for the two scales, and to allow that the other parameters are responsible for the possible effects of lack of homogeneity of flow and agglomeration of particles. The results of this analysis are shown in Table 4 and in Figs. 3 and 4. Both series now
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237
234
show a reduction in the objective function to a similar level to that found in Table 2. The naveline series shows a significant decrease and its OF is better than that of the original series (pilot scale). In the case of the satsuma cultivar, the xk and Wq; values are very similar to those in Table 3. However, there is a more significant change in Zq; . Thus, the interpretation would be the same as above. In the case of the naveline cultivar, the values of the three parameters change; xk increases and Wq; and Zq; decrease. The changes in xk and Wq; suggest the possible formation of masses of particles. The decrease in Zq; may be related to the increase in the height of the bed of particles. In order to improve the representation of the results of the experiments we can include the Table 4 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/production
yr 102 xo 102 xk 102 Wq; 104 Zq; 102 OF 106
1.32 5.80 4.47 2.88 2.51 11.2
Naveline/production 1.93 12.6 7.41 0.44 1.06 6.6
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model. The first two parameters are the parameters of the pilot scale in Table 2.
Fig. 5. Modeling of the experiments using 148 g (1Sc, ) and 1380 g (2SE, ) of raw material (satsuma cultivar), considering the bed formed by six parallel sections, — model.
variation in the mass transfer coefficient in the fluid phase (Zq; ) with the height of the particle bed (z) or its equivalent variable the amount of raw material used (M). This analysis was done using the pilot-scale satsuma cultivar series, because it includes a greater number of experiments. The relationship proposed is a potential one based on the correlations suggested in the bibliography. The first four parameters were fixed at the values shown in Table 2. The relationship found was: Zq; = 10.0 M − 1.04
(7)
The value of the objective function for this series fell to 1.3 10 − 6. The base of earth described was used in all the experiments with satsuma peel at pilot scale except in the experiment with 148 g of raw material, because in this case the extractor was nearly full. This experiment shows a different pattern from the rest of the series. The deviation of this experiment seems to indicate poor distribution of the fluid flow. One way of taking this effect into account is to suppose that the bed of particles is divided into a series of n similar sections of bed, and that the flow of the fluid is divided among them (not necessarily homogeneously) [32]. This procedure was applied to this experiment using six parallel sections [32]. The parameters of the model are the same as those established for the overall series (Table 2). This is how we calculated the distribution of flow to simulate the experiment. The parameters for distribution of flow (aj) were calculated by means of a least square procedure. The value of s obtained for this experiment is 0.20, which seems to indicate a low level of lack of homogeneity. Results of the adjustment are shown in Fig. 5. A similar analysis with experiment 2SE, which is not reproduced well by the model (Fig. 4) permits to improve lightly its representation, this analysis is also shown in Fig. 5. The value of s obtained for this experiment is 7.6 10 − 3. We can, therefore, conclude that this interpretation explains the phenomena that appeared in the experiments with different amounts of raw material and at different scales. The model is able to represent the behavior of these experiments. The small differences between the experimental and
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237
calculated points may be due to variations in the characteristics of the raw material [40,41]. The experiments shown in Figs. 1 – 4 are also part of a program of experiments to study scaleup of the supercritical fluid process. They are used here to discuss hypotheses on lump formation and lack of homogeneity in fluid. Though differing amounts of raw material were used in these experiments, they always corresponded to ordinary values fitting the capacity of the extractor.
4. Conclusions In this essay we have examined the influence of the height of the bed on the rate of the extraction process. Dehydrated orange peel was used as raw material for the study. We have seen that a variety of phenomena arise during the extraction process and hinder it. The raw material may contain lumps of particles. However, this phenomenon was hardly observed at all, or its effects were barely noticeable. Another phenomenon that can distort the process is imperfect fluid flow as a result of poor distribution of flow (lack of homogeneity). The addition of a bed of particles of sand or diatomaceous earth in the bottom of the extractor can reduce poor distribution of flow. The Sovova´’s extended flow model has been used to interpret the experimental results. This has been able to represent the process including the effect of the height of the bed.
235
OF is the objective function, Eq. (6), q is the dimensionless amount of CO2 consumed (kg CO2 kg−1 solute-free feed), Q is the flow rate of fluid (kg s−1), Qj is the flow rate of fluid circulating by jth section (kg s−1), qj is the dimensionless amount of CO2 consumed by jth section (kg CO2 kg−1 solute-free feed), q; is the specific flow rate of solvent (kg CO2 kg−1 solute-free feed s−1), q; is the specific flow rate of solvent in the jth section (kg CO2 kg−1 solute-free feed s−1), W is the dimensionless mass transfer parameter in the solid phase, xk is the initial difficult access solute fraction (kg difficult access solute kg−1 solute-free feed), xo is the initial solute content (kg total solute kg−1 solute-free feed), represents the solubility of the solute in yr CO2 (kg extract kg−1 of CO2), z is the height of the particle bed (m), Z is the dimensionless mass transfer parameter in the fluid phase, aj is the fraction of the flow rate circulating via the jth section, s is a measurement of the lack of homogeneity in the bed.
Acknowledgements 5. Nomenclature e kf kS M n N
is the fraction of extract (kg extract kg−1 solute-free feed), is the mass transfer coefficient in the supercritical phase (m s−1), is the mass transfer coefficient in the solid phase (m s−1), is the amount of solid feed free of solute (kg), is de number of sections considered in the bed, is the number of points,
This work was funded through grant ALI971227-CO2 from the Comisio´n Interministerial de Ciencia y Tecnologı´a (CICYT). Their contribution is greatly appreciated.
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[19] A. Vega-Bancel, P. Subra, Adsorption and desorption of some hydrocarbonated and oxygenated terpenes under supercritical conditions, in: I. Kikic, P. Alessi (Eds.), Proceedings of the III Italian Conference on Supercritical Fluids and their Applications, Grignano, Italy, 3 – 6 September 1995, University of Trieste, Trieste, 1995, p. 149. [20] M. Carles, C. Perre, G. Delestre, L. Schrive, Deterpenation d’huiles d’agrumes par CO2 supercritique. Mise au point du procede industriel en colonne garnie, in: P. Pellerin, M. Perrut (Eds.), Proceedings of the 3e`me Colloque sur les Fluides Supercritiques, Grasse, France, 29 – 30 January, INPLAR, Vandoeuvre, 1996, p. 181. [21] E. Reverchon, C. Perre, M. Perrut, Fractionnement des huiles d’agrumes et caracteristiques des produits obtenus, in: P. Pellerin, M. Perrut (Eds.), Proceedings of the 3e`me Colloque sur les Fluides Supercritiques, France, 29 – 30 January, INPLAR, Vandoeuvre, 1996, p. 35. [22] E. Reverchon, M. Poletto, A. Marciano, Multiple column operation in supercritical CO2 fractionation of peel oil key mixtures, in: Proceedings of the 4th Italian Conference on Supercritical Fluids and their Applications, 7 – 10 September, Capry, Italy, 1997, p. 197. [23] G. Brunner, M. Budich, T. Wesse, V. Leibku¨chler, Optimization study for countercurrent gas extraction: the deterpenation of citrus oils with supercritical carbon dioxide, in: Proceedings of the 4th Italian Conference on Supercritical Fluids and their Applications, 7 – 10 September, Capry, Italy, 1997, p. 27. [24] M. Sato, M. Goto, A. Kodama, T. Hirose, Fractionation of citrus peel oil by supercritical pressure swing adsorption, in: Proceedings of the 4th Italian Conference on Supercritical Fluids and their Applications, 7 – 10 September, Capry, Italy, 1997, p. 39. [25] F. Benvenuti, F. Gironi, Terpene separation from lemon oils by supercritical solvent extraction, in: Proceedings of the 4th Italian Conference on Supercritical Fluids and their Applications, 7 – 10 September, Capry, Italy, 1997, p. 65. [26] M. Budich, S. Heilig, T. Wesse, V.Y. Leibkuechler, G. Brunner, Countercurrent deterpenation of citrus oils with supercritical CO2, J. Supercrit. Fluids 14 (1999) 105. [27] B. Mira, M. Blasco, S. Subirats, A. Berna, Supercritical CO2 extraction of essential oils from orange peel, J. Supercrit. Fluids 9 (1996) 238. [28] B. Mira, M. Blasco, A. Berna, S. Subirats, Supercritical CO2 extraction of essential oils from orange peel. Effect of operation conditions on the extract composition, J. Supercrit. Fluids 14 (1999) 95. [29] B. Mira, Personal communication, 1998. [30] J.M. Snyder, J.P. Friedrich, D.D. Christianson, Effect of moisture and particle size on the extractability of oils from seeds with supercritical CO2, J. Am. Oil Chem. Soc. 61 (1984) 851. [31] H. Sovova´, Rate of the vegetable oil extraction with supercritical CO2. I. Modelling of extraction curves, Chem. Eng. Sci. 49 (1994) 409.
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237 [32] H. Sovova´, J. Kucera, J. Jez, Rate of the vegetable oil extraction with supercritical CO2. II. Extraction of grape oil, Chem. Eng. Sci. 49 (1994) 415. [33] A. Bisio, R.L. Kabel, Scaleup of Chemical Processes, John Wiley & Sons, New York, 1985. [34] P.J. Carmelo, P.J. Pereira, P.C. Simoes, M. Nunes da Ponte, Scale-up of a supercritical extraction unit for the deacidification of olive oil, in: P. Von Rohr, C. Trepp (Eds.), High Pressure Chemical Engineering, Elsevier, Amsterdam, 1996, p. 487. [35] J.Y. Clavier, W. Majewski, M. Perrut, Extrapolation from pilot plant to industrial scale SFE: a case study, in: P. Von Rohr, C. Trepp (Eds.), High Pressure Chemical Engineering, Elsevier, Amsterdam, 1996, p. 639. [36] R. Eggers, U. Sievers, Current state of extraction of natural materials with supercritical fluids and developmental trends, in: K.P. Johnston, J.M.L. Penninger (Eds.), Super-
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Supercritical CO2 extraction of essential oil from orange peel; effect of the height of the bed A. Berna a,*, A. Ta´rrega b, M. Blasco b, S. Subirats b b
a Department of Chemical Engineering, Uni6ersity of Valencia, 46100 Burjassot, Valencia, Spain AINIA, AgroFood Technological Institute, Apdo. 103, Parc Tecnolo`gic, 46890 Paterna, Valencia, Spain
Accepted 7 July 2000
Abstract The influence of the height of the particle bed on the kinetics of supercritical fluid extraction (SFE) of essential oil from orange peel is analyzed in this article. Peel of dehydrated oranges of the satsuma and naveline cultivars was used. A series of experiments were designed wherein, for the same conditions, particle height varied widely. These experiments were also carried out on different scales with extraction volumes of 0.5 and 5 l. The results of the experiments were interpreted using Sovova´’s extended flow model as has been done in previous studies. The bibliography indicates that a number of phenomena may distort the process. One of these phenomena is the formation of masses of particles, due to their oil content, which increases resistance to mass transfer inside the particle. However, this phenomenon was barely noticeable in our experiments. Also, some reordering of the particles may take place due to the differing densities of the two phases and a certain drag effect exercised on the particles by the fluid. This situation can cause a lack of homogeneity in the fluid, further reducing the effectiveness of the process. In the experiments with the satsuma cultivar, where the bed-height range was broader, a base of diatomaceous earth was added in the extractor in order to reduce the lack of homogeneity in the fluid flow. Very similar behavior was found in all the experiments and we can, therefore, conclude that where there is homogeneous flow the height of the bed has very little effect, at least on the same scale of operation. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Orange essential oil; Supercritical fluid extraction; Modeling; Effect of bed height; Carbon dioxide
1. Introduction Supercritical fluid extraction (SFE) is a technique that makes use of the high solvent ability of supercritical fluids (SF), which combine the solvent capacity of liquids with the mobility of gases. * Corresponding author. Fax: +34-6-1318008. E-mail address: [email protected] (A. Berna).
This is due to the fact that the density and viscosity of these fluids lie midway between those of a gas and those of a liquid. Moreover, the diffusivity of these fluids tends to be much higher than that of liquids, thus allowing increased extraction rates. Their properties also vary widely with operating conditions (pressure and temperature), facilitating the adjustment of the solvent effect. In recent years considerable effort has been
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devoted to researching these processes and increasing the number of applications for them [1 – 7]. Many of these applications were to oil extraction [8–11]. Oranges are one of the main products of the Valencian region. In 1995 production reached over 3400 Mkg. Such production levels tend to saturate the market and a significant proportion of output is, therefore, processed to obtain juices, marmalades and so on. Thus, in 1995, 40% of the region’s output was used by the citrus derivatives industry. The processing of oranges produces a series of by-products. One of these is the peel, from which a variety of products, including essential oil, can be obtained. Orange essential oil is used to add the aroma from the orange to products such as carbonated drinks, ice creams, cakes, air-fresheners, perfumes, etc. [12–14]. Other applications make use of the germicidal properties of some of its components. Small amounts of D-limonene can have an important effect on wastewater as a germicide treatment [15]. Carotenoid pigments, which are also present in orange peel extracts, are important for the health, not only for their nutritional value as vitamin A precursors, but also for their antioxidant and anticarcinogenic properties [16]. These components are also used as food coloring. In spite of their potential significance, there exist few studies dealing with the extraction of essential oils from citrus fruit in general [17] and from orange peel in particular [18]. There are more studies on the deterpenation of these oils available [19–26]. This is probably due to the fact that the traditional procedures are very quick and economical, although they do not allow selective extraction. In principle, supercritical extraction can give rise to the fractionation of the essential oils, reducing or eliminating the terpene fraction responsible for the deterioration of these oils. We studied the application of SFE techniques to the extraction of essential oils from orange peel. Our studies analyzed the effect of operating conditions on the solubility of orange essential oil [27], and the effect of particle size and solvent flow on the extraction rate [28]. One of the most salient aspects of the latter study was that it showed the effect of particle size on the composition of the extract.
Various authors have also studied the influence of pretreatments on the kinetics of extraction. More specifically, the effect of the moisture of the raw material (orange peel) has been considered by Mira [29]. A similar study, although involving a different type of oil, was carried out by Snyder et al. [30]. The extraction curves were modeled using Lack’s extended plug flow model as adapted by Sovova´ [31,32]. This model takes into account the solubility of the extract (yr) in the solvent and the mass transfer coefficients both in the flowing phase (Z= Z[kf]) and in the solid phase (W= W[ks]). It also considers that the solute is evenly distributed throughout the matrix that contains it. In spite of this uniformity, two fractions of the same solute are considered; an easy-access fraction, which is the most superficial one, and a difficult-access fraction, which is in the nucleus of the particle. The mass transfer parameters Z and W can vary with particle size, but only Z will vary with solvent flow. By analyzing the data from the experiments we can identify the parameters of the model: yr, xo, xk, Z and W. yr represents the apparent solubility of the solute, xo and xk represent total initial solute content and initial difficult-access solute, respectively. The first parameter depends mainly on operating conditions (P and T). The second and third parameters will depend on the raw material and the selected particle size. The parameter for mass transfer inside the particle (W) can vary with particle size and the parameter for mass transfer in the fluid (Z) will depend on solvent flow, particle size, the properties of the fluid and the bed height. Parameters yr, xk, Z and W are of great interest when scaling up the process, since they contribute useful information for equipment design and for the selection of optimum operating conditions. The selected model presents the difficulty of requiring a large number of parameters that have to be adjusted based on information from the experiments. Nevertheless, some of these parameters could be established using information from independent experiments. We refer to solubility and the initial composition of the raw material. The advantage of this model is related to the
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inclusion of possible internal and external resistances to mass transfer, as well as the distribution of the solute inside vegetable matrices. Nevertheless, this model may fail to represent some phenomena, such as the possible adsorption of the product by the matrix [3]. The objective of the laboratory scale research is to facilitate the design of an industrial plant, which would involve determining the optimum operating conditions taking into account the quality of the product, and the yield and economy of the process. Such research can be carried out on laboratory or pilot scales, although it should not be assumed that scale-up will be a simple process since phenomena that are so insignificant as to be imperceptible at a reduced scale may become significant at production scale. In the bibliography there are a number of texts dealing with scale-ups in chemical industry processes [33], and some approaches for supercritical fluid extraction [34 – 37]. The proposed model has demonstrated its usefulness for representing different situations with different raw materials, provided they fit the basic ideas of the model, particularly with regard to the distribution of the solute in the matrix. The effect of the height of the particle bed is not specifically contemplated in this model and it has been little studied. It may be apparent in the amount of raw material and the mass transfer coefficient of the fluid phase. The estimation of mass transfer coefficients in systems with packing is dealt with in general mass transfer books. The effect of bed height is considered only in relation to certain procedures. For example Coulson et al. [38] and Perry et al. [39] reported some studies that take it into account. These studies show the effect of bed height on HEPT (height equivalent to a theoretical plate). Some of the proposed correlations show that HEPT is proportional to z 1/3 or z 1/2, where z is the height of the bed; that is to say, the mass transfer coefficient must decrease in the same way. This effect is not considered in other correlations. It seems interesting to approach our study as preparatory work for scale-up. Sovova´ et al. [32] studied the effect described above using two series of experiments on a small scale: an extractor of 12
229
ml and feed between 1 and 4 g, and an extractor of 150 ml with feed between 2 and 17 g. In these experiments there occurs a decrease in the effectiveness of the process when the amount of feed is reduced. This was evident in the case of the experiments with smaller supplies of raw material, but its effect was smaller in the rest. The interpretation of these results suggested the existence of a certain channeling of the fluid, which the authors represented by dividing the bed into n equal parallel sections. The modeling of the channeling phenomenon can be approached by representing the flows circulating via these sections as non-homogeneous. If we call the amount (kg) of solid feed free of solute M, in each section one will have M/n kg of solid free of solute. The flow rate of fluid (kg/s) that circulates for each section will be Qj, a fraction (aj) of the total flow rate Q. The following must be true: n
% Qj = Q
Qj = ajQ
j=1
n
% aj = 1
(1)
j=1
The specific flow rate of the fluid in each section (qj) will be related to the total (q): q; j = nQj/M=najq;
(2)
and the dimensionless amount of solvent passed through the jth section in the time t is: q; j = q; jt= najq;
(3)
The dimensionless amount of extract obtained from the jth section of the bed can be calculated with the equations of the model (Eqs. (1)–(8), in Mira et al. [27]) substituting qj for q. The overall dimensionless amount of extract obtained will be: n
e(q; = q; t)= % ej (t)/n
(4)
j=1
The lack of homogeneity of the fluid flow in the bed is represented by s.
n
s = % (naj − 1)2/n j=1
n
0.5
(5)
which is a measurement of this phenomenon. This information can be used to quantify the lack of homogeneity, but not to make predictions about the process.
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The objective here is to approach the study of the effect of the height of particles on the rate of the process with a different raw material (dehydrated orange peel) and larger equipment than that used in the above-mentioned study. In this way, we intend to test whether the model can be applied to systems in which the amount of solids used for extraction is very different. Moreover, we wish to determine if it is possible to approach the scale-up with the mentioned model or whether, on the other hand, it needs to be supplemented with other information on the phenomena associated with the amount of raw material.
2. Materials and methods The oranges used in this study were Citrus sinensis (L.) of the naveline and satsuma cultivars. In both cases the fruit was ripe. The naveline variety was selected because it is produced in volume and the satsuma because it is so frequently used for processing. Samples of the satsuma variety were obtained from a citrus co-operative (Agriconsa, Valencia, Spain) and oranges of the naveline cultivar were obtained from a local producer in Gandı´a (Valencia, Spain). Oranges of the naveline cultivar were peeled by means of an industrial procedure that separates the external part (flavedo), leaving 20% of the weight of the fresh product. Oranges of the satsuma cultivar were peeled manually by the co-operative supplier. The drying procedure and the characterization of these materials were described in a previous report [27]. The final moisture of the samples was 0.084 and 0.150 (kg H2O/kg m.s.) in the satsuma and in the naveline peel, respectively. The solvent used was dry CO2, supplied by Abello´-Linde (Valencia, Spain). It was over 99% pure. The operating conditions were 313 K and 200 bar (20 MPa). The selected solvent flow was 1 kg/h in the pilot scale experiments and 20 kg/h in the production scale experiments. The amount of orange peel used in each experiment varied between 0.045 and 0.145 kg in the pilot scale experiments and between 0.920 and 2.200 kg at production scale. Some of these experiments were also designed to study the scale-up of the process.
In this case, a scale relationship of 20 was applied for the amount of raw material and for the flow rate. Results of previous studies [27,28] were used as a guide in selecting operating conditions. Pressure was set at 20 MPa in order to allow extraction of a significant fraction and at the same time to facilitate the extraction of oxygenated compounds. The selected temperature is relatively low to avoid the deterioration of the extract and also to facilitate control of the process. The experiments were carried out on two different sets of equipment, one for the pilot-scale and another for the production-scale experiments. The pilot unit with an effective capacity of 0.36 l (SFE-500, SEPAREX) is described in a previous study [27]. We also used a set of equipment of our own design, with an extractor of approximately 5 l that also has two separation units, a cyclone and a decanter. This equipment is considered to represent production scale for the purpose of comparison. The amounts of the satsuma and naveline cultivars to be used were established as follows: in the pilot-scale experiments with the naveline cultivar two amounts corresponding to 50 and 70% of total capacity, respectively, were used. In the pilot-scale experiments with the satsuma cultivar a wider range of total capacity was studied (from 30 to 95%). The production-scale experiments were an adaptation of the pilot-scale experiments. Some relationships (q; and q) were kept constant and a scale factor was introduced. This procedure was proposed by Clavier et al. [35]. As has been pointed out previously, q; and q are the specific flow rate of the fluid (kg CO2 kg − 1 solute-free feed s − 1) and the dimensionless relationship between the amounts of solvent and raw material used in each experiment (kg CO2 kg − 1 solute-free feed), respectively. Twenty was selected as the scale factor for the amount of raw material. The conditions under which the experiments corresponding to the different scales and cultivars were conducted are shown in Table 1. The productionscale experiments that were adaptations of the pilot-scale ones are indicated with the same letter in capitals in Table 1.
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237
where N is the number of experimental points. This OF is on an absolute value basis, and has been used in a comparative way.
Extraction kinetics were recorded through periodic measurement of the weight loss of the orange peel. The procedure was described in a previous work [27]. A base of diatomaceous earth was used in the experiments with the satsuma variety. This base was added in order to achieve homogeneous fluid flow. A procedure of least square has been used with the Solver function of the Excel-97 spreadsheet to identify the parameters of the proposed model. The objective function that had to be minimized was:
3. Results and discussion The results of the four series of experiments are shown in Figs. 1–4. They were carried out with the satsuma and naveline cultivars, and the only difference among the experiments in each series is the height of the bed of particles. These results are, partly, similar to those of the above mentioned authors [31,32]. The rate of the process increases slightly with the amount of the raw material.
N
OF= % (eexp −ecalc)2n/N
231
(6)
n=1
Table 1 Equipment and raw materials used for the study of the effect of the height of the beda a) Equipment Scale
Pilot
Volume (l) Diameter (cm) Height (cm)
Production
0.36 5.50 15.0
5.18 13.0 39.0
b) Culti6ars b1) Na6eline culti6ar Series Flow rate (kg/h) Time (h) Scale
1N 1 7 Pilot
2N 20 7
Experiment
a
Production b
A
Feed (g) Height of bed (cm) q; (kg/kg h) q (kg/kg)
109 10.4 10.2 72.5
80.4 7.7 14.0 97.9
b2) Satsuma culti6ar Series Flow rate (kg/h) Time (h) Scale Experiment
1S 1 2.5 Pilot c
2S 20 2.5
Feed (g) Height of bed (cm) q; (kg/kg h) q (kg/kg)
148 14.1 7.1 17.9
a
Operation conditions (40°C and 20 MPa).
d 100 9.5 10.6 26.4
B
2199 37.7 10.3 72.4
e
1630 28.0 13.9 97.6
Production E
f 69 6.6 15.4 38.6
46 4.3 23.1 57.9
1380 23.7 15.2 38.0
F 919 15.7 22.8 56.9
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Fig. 1. Kinetics of the extraction of essential oils from orange peel (naveline cultivar). Experiments carried out at 40°C and 20 MPa, pilot scale and different amounts of raw material, 109 g (1Na); ×80 g (1Nb); — model.
Fig. 2. Kinetics of the extraction of essential oils from orange peel (satsuma cultivar). Experiments carried out at 40°C and 20 MPa, pilot scale and different amounts of raw material, 148 g (1Sc); × 100 g (1Sd); 69 g (1Se); + 45 g (1Sf); — model.
The results of the experiments were interpreted using the proposed model. Initially, all the data for each series of pilot experiments on both cultivars were adjusted simultaneously. This allows us to test the capacity of the model to incorporate the effect of the height of the bed. The results of the adjustment are shown in Table 2 and in Figs. 1 and 2. As can be seen, the model represents the results of the experiments appropriately. However, it shows a series of differences and possible incoherences with the physical implications of the parameters. Thus, the solubility figure changes from one series of experiments to another. The mass transfer coefficients for the two phases also vary. One can explain the differences between the solubilities (yr) of the essential oil obtained from
Fig. 4. Kinetics of the extraction of essential oils from orange peel (satsuma cultivar). Experiments carried out at 40°C and 20 MPa, production scale and different amounts of raw material, 1380 g (2SE); ×919 g (2SF); — model. Table 2 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/pilot
Fig. 3. Kinetics of the extraction of essential oils from orange peel (naveline cultivar). Experiments carried out at 40°C and 20 MPa, production scale and different amounts of raw material, 2199 g (2NA); ×1630 g (2NB); — model.
Naveline/pilot
yr 102 xo 102 xk 102 Wq; 104 Zq; 102
1.32 5.80 4.47 4.33 517
1.93 12.6 6.44 2.11 5.12
OF 106
8.6
16.2
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model.
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237 Table 3 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/production
yr 102 xo 102 xk 102 Wq; 104 Zq; 102 OF 106
1.32 5.80 4.47 4.33 0.10 12.2
Naveline/production 1.93 12.6 6.44 2.11 0.12 710
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model. The first four parameters are the parameters of the pilot scale in Table 2.
the two cultivars, because their composition is different. The differences in the parameters relating to overall composition (xo and xk) illustrate this. The different value of the mass transfer coefficient of the solid phase (Wq; ) may be related to the differing oil content of the raw material and its differing distribution. This parameter represents the ease with which the solute is transferred in the solid phase. In this sense it will be related to the xk parameter. When the weight of the fraction of difficult-access solute (xk) increases and the particle size is the same, transfer will be easier, and the mass transfer coefficient will increase, because solute is closer to the surface. The satsuma cultivar, which has lower essential oil content, has an xk value that represents 77% of the total content, while the naveline cultivar, which has higher oil content, has an xk value representing only 51% of the total. As we assume that solute is evenly distributed it would appear that the difficult-access solute is deeper in the naveline cultivar, making it more difficult to extract. This would explain the lower Wq; value in this cultivar. A higher xk value may also be related to the formation of masses of particles. This possibility is small in the case of the satsuma cultivar because of its lower oil content, and seems a little more probable at pilot scale perhaps due to the lower flow rate. The opposite is true in the case of the naveline cultivar due to its higher oil content. The
233
possibility of the formation of masses of particles is greater at production scale where there are more solid particles. The differences in the values of the mass transfer coefficient for the fluid phase (Zq; ) are more difficult to explain because this parameter takes into account the ease with which solute transfer takes place in the fluid phase. It will be influenced by flow rate, height of the particle bed and particle diameter. The differences between the two series of experiments do not justify these different values. They may be the result of compensation among parameters. In order to make the model more meaningful and attempt to extend the results from pilot to production scale, we identified the parameters for the experiment data at production scale. When making this adjustment we assumed as common to each cultivar the first four parameters (yr, xo, xk and Wq; ), and we selected for them the values obtained at pilot scale. In the satsuma variety these parameters represent the behavior of four experiments. We tried to adjust the production scale experiments using Zq; . The results are shown in Table 3. The objective function is worse than in Table 2. The dramatic increase in this function for the naveline variety should be noted. It may be related to the fact that in this case the base of diatomaceous earth was not added to homogenize the fluid flow. This effect may have distorted the process and produced the difference between the scales. The loss of quality of the modeling in the satsuma variety is less pronounced. The adjusted parameter shows a significant decrease in both cases, which is related to the increase in the height of the bed. To increase the quality of the representation a further adjustment of the production-scale data was carried out based on the pilot-scale results. In this case we assumed as common to each cultivar only the first two parameters (yr, xo). It seems more realistic for solubility and composition of the raw material to remain the same for the two scales, and to allow that the other parameters are responsible for the possible effects of lack of homogeneity of flow and agglomeration of particles. The results of this analysis are shown in Table 4 and in Figs. 3 and 4. Both series now
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show a reduction in the objective function to a similar level to that found in Table 2. The naveline series shows a significant decrease and its OF is better than that of the original series (pilot scale). In the case of the satsuma cultivar, the xk and Wq; values are very similar to those in Table 3. However, there is a more significant change in Zq; . Thus, the interpretation would be the same as above. In the case of the naveline cultivar, the values of the three parameters change; xk increases and Wq; and Zq; decrease. The changes in xk and Wq; suggest the possible formation of masses of particles. The decrease in Zq; may be related to the increase in the height of the bed of particles. In order to improve the representation of the results of the experiments we can include the Table 4 Extraction kinetics of essential oils from orange peela Parameters
Raw material/scale Satsuma/production
yr 102 xo 102 xk 102 Wq; 104 Zq; 102 OF 106
1.32 5.80 4.47 2.88 2.51 11.2
Naveline/production 1.93 12.6 7.41 0.44 1.06 6.6
a Experiments carried out at 40°C and 20 MPa, with different amounts of raw material. Parameters of Sovova´’s model. The first two parameters are the parameters of the pilot scale in Table 2.
Fig. 5. Modeling of the experiments using 148 g (1Sc, ) and 1380 g (2SE, ) of raw material (satsuma cultivar), considering the bed formed by six parallel sections, — model.
variation in the mass transfer coefficient in the fluid phase (Zq; ) with the height of the particle bed (z) or its equivalent variable the amount of raw material used (M). This analysis was done using the pilot-scale satsuma cultivar series, because it includes a greater number of experiments. The relationship proposed is a potential one based on the correlations suggested in the bibliography. The first four parameters were fixed at the values shown in Table 2. The relationship found was: Zq; = 10.0 M − 1.04
(7)
The value of the objective function for this series fell to 1.3 10 − 6. The base of earth described was used in all the experiments with satsuma peel at pilot scale except in the experiment with 148 g of raw material, because in this case the extractor was nearly full. This experiment shows a different pattern from the rest of the series. The deviation of this experiment seems to indicate poor distribution of the fluid flow. One way of taking this effect into account is to suppose that the bed of particles is divided into a series of n similar sections of bed, and that the flow of the fluid is divided among them (not necessarily homogeneously) [32]. This procedure was applied to this experiment using six parallel sections [32]. The parameters of the model are the same as those established for the overall series (Table 2). This is how we calculated the distribution of flow to simulate the experiment. The parameters for distribution of flow (aj) were calculated by means of a least square procedure. The value of s obtained for this experiment is 0.20, which seems to indicate a low level of lack of homogeneity. Results of the adjustment are shown in Fig. 5. A similar analysis with experiment 2SE, which is not reproduced well by the model (Fig. 4) permits to improve lightly its representation, this analysis is also shown in Fig. 5. The value of s obtained for this experiment is 7.6 10 − 3. We can, therefore, conclude that this interpretation explains the phenomena that appeared in the experiments with different amounts of raw material and at different scales. The model is able to represent the behavior of these experiments. The small differences between the experimental and
A. Berna et al. / J. of Supercritical Fluids 18 (2000) 227–237
calculated points may be due to variations in the characteristics of the raw material [40,41]. The experiments shown in Figs. 1 – 4 are also part of a program of experiments to study scaleup of the supercritical fluid process. They are used here to discuss hypotheses on lump formation and lack of homogeneity in fluid. Though differing amounts of raw material were used in these experiments, they always corresponded to ordinary values fitting the capacity of the extractor.
4. Conclusions In this essay we have examined the influence of the height of the bed on the rate of the extraction process. Dehydrated orange peel was used as raw material for the study. We have seen that a variety of phenomena arise during the extraction process and hinder it. The raw material may contain lumps of particles. However, this phenomenon was hardly observed at all, or its effects were barely noticeable. Another phenomenon that can distort the process is imperfect fluid flow as a result of poor distribution of flow (lack of homogeneity). The addition of a bed of particles of sand or diatomaceous earth in the bottom of the extractor can reduce poor distribution of flow. The Sovova´’s extended flow model has been used to interpret the experimental results. This has been able to represent the process including the effect of the height of the bed.
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OF is the objective function, Eq. (6), q is the dimensionless amount of CO2 consumed (kg CO2 kg−1 solute-free feed), Q is the flow rate of fluid (kg s−1), Qj is the flow rate of fluid circulating by jth section (kg s−1), qj is the dimensionless amount of CO2 consumed by jth section (kg CO2 kg−1 solute-free feed), q; is the specific flow rate of solvent (kg CO2 kg−1 solute-free feed s−1), q; is the specific flow rate of solvent in the jth section (kg CO2 kg−1 solute-free feed s−1), W is the dimensionless mass transfer parameter in the solid phase, xk is the initial difficult access solute fraction (kg difficult access solute kg−1 solute-free feed), xo is the initial solute content (kg total solute kg−1 solute-free feed), represents the solubility of the solute in yr CO2 (kg extract kg−1 of CO2), z is the height of the particle bed (m), Z is the dimensionless mass transfer parameter in the fluid phase, aj is the fraction of the flow rate circulating via the jth section, s is a measurement of the lack of homogeneity in the bed.
Acknowledgements 5. Nomenclature e kf kS M n N
is the fraction of extract (kg extract kg−1 solute-free feed), is the mass transfer coefficient in the supercritical phase (m s−1), is the mass transfer coefficient in the solid phase (m s−1), is the amount of solid feed free of solute (kg), is de number of sections considered in the bed, is the number of points,
This work was funded through grant ALI971227-CO2 from the Comisio´n Interministerial de Ciencia y Tecnologı´a (CICYT). Their contribution is greatly appreciated.
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