Energy & Fuels 1992,6, 578-580
578
Optimization of Polymer Dosage for Peat Dewatering L. Ringqvist, P. Igsell, K. Bergner,* and E.-L. Lind Centre for Peat Research, Box 4097, S-904 03 Umeci, Sweden Received August 20, 1991. Revised Manuscript Received April 2, 1992
Mechanical peat dewatering is an alternative to the traditional sun and wind drying method. However, a pretreatment of the peat is necessary to enhance the separation of the solid and liquid phases. The most promising method so far is the combination of pH lowering and addition of a polymer. The aim of the present study was to find a cheap, fast, and easy way to optimize the polymer dosage that is independent of peat type and mechanical treatment as stirring time, grinding, etc. The particle size distribution and the surface charge for a number of different peat types are tested. An empirical model concerning optimum dosage of polyelectrolytes was developed using multivariate data analysis. The conclusion is that the surface charge of peat can model the optimum polymer dosage. Introduction
The main problem with the utilization of peat as a fuel is the dewatering. Peat contains in its natural state about 90 wt % water and this amount of water must be reduced to less than 50 wt % to be used as a fuel. The traditional sun and wind drying method is heavily dependent on weather conditions and also slow. Mechanical dewatering of peat, Le., pressing, is very difficult. Only about 15 wt % of the water may be reduced in a high-capacity units1 The reason why peat is so difficult to dewater by pressing is mainly due to the surface and colloidal properties of the peat? i.e., smallparticles in combinationwith electrostatic interactions. That means that the problems of peat dewatering have characteristics comparable to the dewatering of coal fines, cellulose fibers, clays, etc. The colloidally stable small particles carry a negative charge, due to dissociated carboxylicacids,that prevent them from aggregating. These small particles plug the drainage pores during pressing. Various pretreatment methods have been tested to facilitate aggregation and thereby subsequent separation of the solid and liquid phase^.^-^ The most promising pretreatment method so far is the combination of pH lowering and a polymer.1° Addition of chemicalsrequires a peat slurry, Le., dilution with water. Only filtration experiments, where 1&15% dry solids (DS) can be reached, were performed in this study. This step must be followed by a pressing stage to reach desired DS content in the cake. The chemical pretreatment has a greater effect on the filtration part than on the pressing part." (1) Fucheman, C. H. Peat and Water, Fuchsman, C. H., Ed.; Elsevier: Amsterdam, 1986;pp 1-7. (2)Kwak, J. C. T.; Latiff, A.; Sheppard, J. D. Peat and Water; Fuchsman, C. H.,Elsevier: Amsterdam, 1986;pp 95-118. (3)Ayub, A. L.; Sheppard, J. D. Colloid Surf. 1986,18,43-52. (4)Coowr. D.G.:Eccles, E. R. A.:. Shemard.. J. D. Can.J . Chem. Ena. 1986,66,94&949. (5)CooDer. D.G.:Pillon. D. W.: Mullirran. C. N.: Shemard. _. . J. D. Fuel 1986;65,i5g260. (6)Ayub, A. L.; Sheppard, J. D.; Kwak, J. C. T. Colloid Surf. 1987,26, 305-315. (7)Class, D.S.;Cooper, D. G.; Sheppard, J. D. Can. J . Chem. Eng. 1987,65,500-504. (8) Forsberg, S.; AldBn, L. Colloid Surf. 1988/89,34, 335-343. (9)Forsberg, S.;AldBn, L. Fuel 1989,68, 446-455. (10)Jhsson, B.; Pettersson, E.; Lindman, B. Fuel 1987,66,785-793.
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Peat is a complex material originating from different plants and decomposed to different degrees which causes chemical and physical dissimilarities between the peat types.12 Besides the dissimilaritiesbetween different peat types, a peat sample is sensitive to mechanical treatment. Particle size distribution and thereby particle surface will change.1° The optimum dosage of the dewatering agents are related to the neutralization of the surface charge. Although several authors have studied the reltionship between surfaceproperties, adsorption, and dewatering?+ a predictive relation that can be used for different peat types (with different physical and chemical properties) treated in variousways seemsto be lacking. In most studies investigations are performed with only one peat type. The aim of the present study was to find a fast and easy way to optimize the polymer dosage for different peat types independent of pretreatment as stirring time, grinding, etc. Particle size distribution and particle surface charge as well as peat type and humification degree were measured. The shortest filtration time was used to find the optimum polymer dosage. Empirical mathematical modeling using modern multivariate techniques was used to verify the results. These methods have proven valuable in describing the complex peat dewatering characteristics.11J3 The results show that it is indeed possible to predict the optimum dosage range from the peat surface charge. Experimental Section The peat samples were collected in northern Sweden. They represent seven peat classes identified by principal component analysis based on botanical and chemical data.'* The differentiation was mainly due to botanical composition and degree of decomposition. These properties together with other data are presented in Table I. Chemicals. The polyelectrolyte A (a copolymer of (dimethy1amino)ethyl acrylate and acrylamide, Allied Colloids, England) was diluted from 50 to 0.5 % with deionized water. Solutions of the polyelectrolytespolybrene (3,6-ionene,Aldrich Chem. Co.) and potassium polyvinyl sulfate, KPVS (Wako Pure Chem. (11)Ringqvist, L. Proc. Conf.Peat 90,11-15 June 1990,Jyvbkylh, Finland: 1990,2,130-135. (12)Bohlin, E.;Hiuniliinen, M.; SundBn, T. Soil Sci. 1989,144,252263. (13)Herath, B.; Albano, C. Fuel 1989,68, 354-360.
08S7-062~/92/2506-0~78$03.00/0 0 1992 American Chemical Society
Polymer Dosage for Peat Dewatering
Energy & Fuels, Vol. 6, No. 5, 1992 579
Table I. General Description and Analytical Data of Analyzed Peat Types optimum charge: calorific value, dry MJ/kg ash PolConc, solids, mequiv/g peata Hb wt % DS free dry peat wt % of DS
S S NS C C C LC
2-4 5-6 7-8 2-3 5 6-7 4-6 3-4
9.2 7.5 12.9 7.7 11.3 12.8 11.4 10.3
0.21 0.32 0.25 0.13 0.12 0.12 0.20 0.14
20.9 22.1 23.3 23.9 23.8 25.0 23.4 23.3
Peal chirped pH.3.0 (mqvlg DS) 31
0.20 0.40 0.30 0.10 0.05 0.05 0.30 0.05
EuSC a C, carex; S, sphagnum; L, lignids (trees and shrubs); EuS, S p h a g n u m warndorfii;N, Nanolignids (ericaceaeous, dwarf shrubs). b H, degree of decomposition (von Post). Peat charge at pH = 3.0. Japan) containing 1 g/L, respectively,were prepared. The charge density of the KPVS solution was determined by correlating it to the known polybrene charge density. A solutionof the indicator o-toluidine blue, OTB, containing 0.2 g/L, was prepared. Equipment. Dewatering studies were performed at room temperature13J4with a laboratory pressure filter equipment. The filter cell consists of a plexiglass cylinder of i.d. 140 mm with stainless steel top and bottom plates. The bottom plate supports a perforated steel plate with a Munktell filter paper. The top plate is fitted with inlets for compressed air, a pressure gauge, and a pressure relief valve. The bottom plate is fitted with an outlet of i.d. 9 mm. Slurry Preparation. In each experiment, 300 g of 3% slurry was prepared from raw peat in the following manner. The peat was weighed taking into consideration the dry solids contents of the different peat types, as presented in Table I. Deionized water was added to 280 g, and the slurry mixed for 60s at 300 rpm. The pH of the slurry was set to pH = 3.0using 1 M HCI, during a total stirring time of 90 s at 200 rpm. Polymer A was added to the slurry, and the peat and polyelectrolyte were mixed for 30 s at 200 rpm. The weight of the sample was then corrected to 300 g by adding deionized water. Throughout the filtration experiment all the stirring and mixing was done by using a paddle stirrer. Filtration. The samples were transferred onto a filter paper (Munktell filter paper no. 1003)in the cylinder, making sure that the slurry was distributed homogeneously over the filter paper. The filtrations were done by applying a constant air pressure of 0.1 MPa above the slurry. The filtration was stopped when air penetrated the peat cake and the filtration time was noted. Surface Charge. The polyelectrolyte titrations were done on peat slurries, 0.5 g of DS. Peat was taken from a p H corrected 3% DS slurry prepared as for the filtration experiments, except the addition of polyelectrolyte. Deionized water was added to 100 g. A known amount of polybrene was added in excess, and the slurry was stirred for 30 min using a magnetic stirrer set at 300 rpm. The peat was filtered off, dried, and weighed to obtain the exact dry solids weight, for subsequent calculation of the surface charge. The filtrate containing the excess polybrene was back-titrated with KPVS, using o-toluidine blue (OTB) as indicator. ParticleSize Distribution. For the particle size distribution measurements a Malvern Master Sizer laser diffraction instrument was used. The peat sample was placed in the measuring chamber, diluted to suitable operating conditions, and gently stirred for 4 min before the measurements were carried out. The result from the analysis consisted of 32 size intervals spanning from 1.2 to 600 pm in particle size. Data Processing. The data analysis used to model the system relates the independent variables (factors X) and dependent variables (responses Y) to a mathematical model: (14)Herath,B.;Albano,C.;Geladi,P.FiltrationandSeparation; 1989, JanIFeb.
,121
0
C
K t3
06
c-H2-3 09
12
15
18
21
24
27
3
33
35
39
42
obrrmd optimum polymrr conuntntlon (Mof DS)
Figure 1. Graph of the observed filtration time obtained from dewatering studies at different polymer concentrations. C, carex; S, sphagnum; L, lignids (trees and shrubs); EuS, Sphagnum warndorfii; N, nanoligands (ericaceaeous, dwarf shrubs); H, humification (von Post).
Y = bo + b,xl
+ ... + bnxn + bllx12+ ...+ b,,x; + blplx2+ ...+ b~n-l)nxn-lxn + e
(1)
where e = residual. In this model the different factors (XI, x2, ...) and the interaction between factors ( ~ 1 x 2 ~, 1 x 3 , ) were introduced. To be able to model nonlinearities the square of the factors ( x l 2 , ~ 2 ...) ~ were . introduced. Partial least-squares regressions (PLSR)lS and principal component analysis (PCA)lBwere usedto estimate the coefficients (bo, bl, .,,) in the model. The coefficients give information on the influence of the respective factors. The variables were standardized, i.e., the variables were weighted by the inverse standard deviation to give variance equal to 1.0 for all variables. The statistical significance of PLS and PCA components (latent variables) were determined by using cross validation'' to verify the significant number of components needed to span the systematic variation.
...
Results and Discussion The results from the dewatering studies are presented in Figure 1 as filtration time plotted versus the amount of added polymer. The polymer A used turned out to be very efficient, more efficient than the earlier studied polymer Be1'Polymer B ((dimethylamino)methylacrylate, Allied Colloids,England)have a straight chain, a molecular weight of 500 OOO, and a calculated cationic value of 4.8 mequiv/g. Polymer A is a branched polymer with a high molecular weight (12X 10s)and a calculated catonic value of 4.13 mequiv/g. It can be seen from the figure that Sphagnum and Carex peat have different polymer demand independent of humification degree. The range of optimum polymer concentration, Le., lowest filtration time for the respective peat types, are readily seen, especially for the Sphagnum peat types and the highly humified Carex peat types. As for the lowly humified CQreX peat types, the first point on the leveling curve is assumed as the optimum. A slight increase in fiitration times can be noted as the polymer levels are increased beyond this point. The particle size distribution studies were performed as described in the Experimental Section. Data from the 32 size intervals were considered to be too many variables (15)Martens, H.; Naes, T. Multivariate Calibratione; Wiley: New York, 1989;pp 54-60. (16)Johnwon, R.A.; Wichem,D. W. AppliedMultiuariate Statistical Analysis; Prentice Halk New York, 1982;pp 361-399. (17)Wold, S.Technometrics 1978,20, 397-406.
Ringqoist et al.
580 Energy & Fuels, Vol. 6, No. 5, 1992 obmrd Rltntlon Umi (6)
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term w-ma
*LS_Hc6
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Eusc-l!3.4
35 A
I , ~
P o m r carnxntntlon,Polymer A (wpx 01 DS)
Figure 2. Graph of the total charge of peat at pH = 3.0 w the optimum polymer concentration a~ obtained from dewatering studies (r = 0.94). C, carex; S, sphagnum; L, lignids (trees and shrubs); EuS, Sphagnum warndorfii; N, nanolignids (ericaceaeous, dwarf shrubs); H, humification (von Post).
to be handled and were therefore reduced by using PCA into two latent variables. These explained 91% of the variation in the data. The first and most significant of these componentsdistinguished between small and large particles dividing the 32 size intervals into two groups, one containing relatively small particles and the other containing relatively large particles. The second, less significant component, described variations within these groups. The scores of these componentswere used when particle size was included in estimating a model of the system. To measure the peat particle charge, a polyelectrolyte titration method, used by the cellulose industry for determination of fiber charge,18 was used. Polybrene is commonly used in polyelectrolyte titrations. Both polybrene and polymer A are highly charged cationicpolymers. They are therefore expected to behave in the same way when exposed to peat. Polymer A was not used directly as titrating agent as it is no standard chemical in this field. Cationicpolymers act as flocculating agents on peat by neutralizing the carboxylic acids and by bridging mechanisms. In Figure 2 the total surface charge of the pH = 3.0 corrected peat types as measured by polybrene titrations are plotted against the optimum concentration of polymer A as obtained from the dewatering studies. As can be seen the expected similar behavior of the two polyelectrolytes is confirmed. The peat charge directly reflects the optimum concentration of polymer A. To confirm the relationship between the surface charge and optimum polymer dosage, and to rule out other variables, an empirical modelingof the data was conducted. The filtration time was chosen as the dependent variable (response Y). The relationship between the independent variables and the filtration time was investigated through PLSR. A model consisting of the variables polymer concentration, humification degree, surface charge at pH = 3.0,the two PCA components scores obtained from the particle size distribution measurements,and the two PCA components scores from ref 12 was computed. Twelve significant components explained 86.4% of the variance (18) Winter, L.; WAgberg, L.; bberg, L.; Interface Sa. 1986, 111, 537.
Lindstrem, T. J. Colloid
Bo Bi B2 Bs B4 B5 &3
Table 11. Regression on Filtration T i m e coeff term coeff 5.0 B26 0.1 -2.7 B28 -0.1 0.3 Bn -0.1 5.9 BS3 8.2 0.0 B3.4 0.2 0.2 B36 0.1 -0.6 B36 -2.6 -0.1 Bsi -0.1 75.4 Bu 0.0 9.2 B46 -0.0 -417.2 B46 0.0 -4.5 &I -0.3 -3.0 B.56 -0.1 6.3 Bh3 0.2 -7.0 &I -0.6 0.0 BM -0.1 0.7 &I -1.0 0.0 BII 0.7
BI Bii Biz B13 B14 Bis B16 Bii B22 B23 B24 a All factors have been scaled. BO,constant. B1, polymer concentration, polymer A. B2, degree of decomposition (von Post). Bs, peat charge at pH = 3.0. B,, PCA component 1 from particle size distributionmeasurements. B5,PCA component 2 from particle size distribution measurements. Be, PCA component 1 from ref 13.B7, PCA component 2 from ref 13.
of the dependent variable. The coefficients of the terms in the model are listed in Table 11. As the factors have been standardized by the inverse standard deviation to give variance equal to 1 for all variables, the coefficients can be compared. A higher absolute value means a higher significance of the factor. It is obvious that the polymer concentration and the peat charge have the greatest influence on the filtration time. It can also be shown that the particle size distribution of the peat is a factor of minor importance when a polymer addition, is optimized. To verify the usefulness in determining the peat charge, a Carex peat sample with humification degre 6-7 was chosen. From the sample a pH = 3.0 corrected 3% DS slurry was prepared. The slurry was then left stirring for half an hour at 250 rpm, on a paddle stirrer (mechanical treatment of peat slurries has proven to increase the f i e particle fraction in the peat). The peat charge and the optimum polymer concentration were then determined according to methods previously described. The results show an almost doubled increase in peat charge from 0.12 to 0.21 mequivlg DS. By using Figure 2 a predicted optimum polymer concentration of 0.20 wt % can be found for this particular peat charge. The optimum polymer concentration determined from filtration experimentsfor this mechanically treated peat shows a significantly increased polymer demand. The optimum is about 0.15 wt 5% compared to 0.06 wt % for the nonmechanically treated peat. In summary this work has shown that measuring the peat charge by polyelectrolyte titrations is in fact a fast and easy way of optimizing the polymer dosage for peat pretreatment. To refine the model more peat types will be investigated and the results are to be published in the near future. Acknowledgment. Financial support from the Swedish Energy Administration through Grants 216089-2and 216044-1is gratefully acknowledged. Registry No, (Acrylamide)(dimethylaminoethyl acrylate) (copolymer),54240-53-8;polybrene, 28728-55-4;potassium poly vinyl sulfate, 26837-42-3.
