Online Monitoring of Kappa Number during Batch Pulping by Visible

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Online Monitoring of Kappa Number during Batch Pulping by Visible Spectroscopy Wenhao Shen* and Xiaoquan Chen State Key Laboratory of Pulp & Paper Engineering, South China UniVersity of Technology, Guangzhou, P. R. China, 510640

Aiming at the difficulties and problems of online measurement of pulp Kappa number during batch pulping, a novel measuring idea was proposed to predict the lignin content in pulp through the measurement of dissolved lignin in cooking liquor with spectroscopic technology. It was discovered that the spectral absorption of sulfite cooking liquor from Masson’s pine in 460-580 nm wave range resulted mainly from lignin sulfonate with high molecular weight, while saccharide and water in sulfite cooking liquor have no obvious absorption. The delignification study shows that the sulfite cooking delignification process can be observed with selected visible wavelength. Mathematical models of online Kappa number determination with visible spectroscopy were developed by chemometrics for batch sulfite pulping. After applying to sulfite pulp mill, the results showed that the new measuring method was much better than the manual method: The first-class proportion of pulp has been improved from 55% to 70%, the pulp Kappa number could be controlled within (2 units. With this new method, it is possible not only to measure sulfite pulp Kappa number but also to perform the end point controlling of the sulfite pulping process. 1. Introduction Kappa number is an important quality index of pulp; it indicates the degree of cooking of raw material in the cooking process, and it is a key parameter for pulping process control. The control based on the use of the constant Kappa number will maximize product yield and pulp quality while minimizing consumption of energy and chemicals. The measurement of residual lignin content in pulp has been traditionally done on an hourly basis as a laboratory analysis according to TAPPI standard method T236,1 which uses the back-titration of residual permanganate with potassium iodide. However, the method requires extensive workup and can take 30-60 min per sample. Jiang et al.2 have improved this standard technique by semiautomating the titration process with an automatic, multisample titrator. More recently, U.S. Patent 6,475,3393 proposed the use of rapid acidification to improve the accuracy of the potassium permanganate titration. Manganese dioxide precipitation is prevented and thus residual permanganate can be analyzed without spectral interference from MnO2, allowing the UV-visible spectrometry technique to be more accurate than titration. However, this method still requires sample preparation, a number of reagents, and a chemical reaction that takes 3-5 min to complete. Current commercially available Kappa number analyzers use UV light with a combination of reflectance, scattering, transmittance, and consistency measurements4,5 to analyze pulp samples with frequencies on the order of 10-20 min. Although the principle is simple, the actual measurement is complex, because lignin absorption cannot be measured accurately without accounting for the interferences produced by changes in pulp consistency and samples. Currently available commercial Kappa number analyzers do not provide accurate results for samples of unknown or rapidly changing composition.6 When the composition of chips is constantly changing, instruments have to be constantly recalibrated to follow the changes in samples. Updating the two-point * To whom correspondence should be addressed. Tel: +86 20 87110961. Fax: +86 20 87110961. E-mail: [email protected].

calibration and the sampling system requires constant attention from instrumentation personnel. Furthermore, owing to the added sample preparation step, throughput is relatively low, allowing throughput of only about two samples per hour for each location. Lignin chemists have been using vibrational spectroscopy for nearly 50 years to characterize wood and pulp samples. Marton and Sparks7 have determined the Kappa number of pulps by using the area beneath the lignin peak at 1510 cm-1 and the cellulose peak at 1100 cm-1 as an internal standard. The lignin/ cellulose peak-area ratio was found to be insensitive to variations in basis weight. Similarly, Berben et al.8 developed a method using infrared diffuse reflectance for estimating lignin content in unbleached pulp. A linear relationship for all species combined is found between the area of the band at 1510 cm-1 and the Kappa number for a wide variety of species. However, these methods use dry pulp samples and are not amenable to online process analysis of Kappa number for process control. U.S. Patent 4,743,3399 illustrates a method for determining pulp properties, including Kappa number, using FT-IR in the spectral range of 6300-7800 nm. In this method, a spectrum, acquired with 200 coadd averages, needs to be baseline corrected by first determining the water content and fiber content (consistency). Yuzak and Lohrke10 detailed the results of a series of experiments and showed that NIR could be used to estimate the Kappa number of properly prepared kraft pulp samples, i.e. dried handsheets, with an error of (2.0 kappa. Even though the authors utilized the spectral region of 1500-1750 and 2100-2400 nm, their reliance on homogenizing and drying the samples effectively abate its practicability by using NIR spectrometry as a rapid online method for determining Kappa numbers. U.S. Patent 5,536,94211 describes a method and apparatus for the measurement of properties, including Kappa number, of fibers in a fiber suspension with the aid of an NIR spectrometer. The invention details the steps and apparatus for extracting the samples from the process stream, repeated washing in a chamber, pumping the diluted solution to a cell

10.1021/ie802008r CCC: $40.75  2009 American Chemical Society Published on Web 04/14/2009

Ind. Eng. Chem. Res., Vol. 48, No. 10, 2009

that incorporates a screen whereby the fibers are concentrated and monitored at 950 nm to an absorbance of 2.0-4.5 absorbance unit (au) to obtain the preferred consistency (3%), and registering with the detector to obtain a transmission NIR spectrum in the range of 850-1050 nm. The requirement of extensive washing and concentrating prior to spectral data acquisition then followed by rehomogenizing, concentrating, and data acquisition also limits the true online feasibility of the measurement technique for process control. PCT Patent WO 01/7981612 describes a method for the determination of physical properties of fiber suspensions, such as viscosity, tensile strength, fiber lengths, density, burst index, coarseness, opacity, beating requirement, light scattering, and zero span, as well as chemical compositions such as lignin and hexanuronic acid levels. Spectroscopic measurement is made in the NIR range from 780 to 2500 nm. The stated method can only reach four analyses per hour and as described is unsuitable for an online application. Also, no data for Kappa number was presented. Birkett and Gambino13 detailed their result as obtained with a filtometer or filter-based spectrometer and showed correlations for Kappa number for handsheets made from Eucalyptus grandis and five specific wavelengths that have been optimized by multilinear regression. The authors showed that the filteredbased NIR system is sensitive to species variation and can only be applied to dried handsheets. In U.S. Patent 595,311,14 Millar et al. describes the use of a continuous in-line Kappa number measurement system whereby light from an excitation source is injected into a flowing conduit carrying pulp. As with many other systems currently available, this system mainly relies on the lignin absorbance in the visible region of a single wavelength, as in a filtometer or filter-based visible spectrometer. Poke et al.15 presented a NIR method for the determination of lignin in wood meal that requires the drying and grinding of samples. Again, this method is clearly unsuitable for an online application. To overcome the limitations of NIR spectrometry, Trung et al.16 have proposed the use of visible-excitation Raman spectrometry for measuring lignin in pulp. Even though this method overcomes some of the limitations associated with laser-induced fluorescence, this method requires the preparation of a highconsistency sample (15-30%) and a relatively long acquisition time (5-10 min), primarily because of the inherent weakness of the Raman signal produced by the small illumination spot used in the application. Therefore, all the analyzed samples in the prior methods are pulp directly, whether dry or wet. In this paper, we provide results obtained using an alternative method for determining Kappa number with spectrometric technology, achieved by the measurement of dissolved lignin in cooking liquor with visible light. 2. Experimental Section 2.1. Sulfite Pulping. Pulpings were carried out with a batch type digester (100 m3) with cooking liquor recycling at Guangzhou Paper Mill. Chips of Masson’s pine were used in the experiments. The cooking condition was as follows: Ca(HSO3)2-based cooking liquor, total acid (TA) was 6.43%, and combined acid (CA) was 1.08%. The cooking temperature was 138-139 °C. The liquor to wood ratio was 5.5:1.

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Figure 1. UV-vis-NIR absorption spectrum of sulfite cooking liquor with Masson’s pine.

2.2. Kappa number Determination by Titration. After the batch cooking, pulps were washed thoroughly and screened. Their Kappa numbers were analyzed according to the TAPPI Standard.1 2.3. Visible Spectra Determination. During pulping, cooking liquor were sampled. Then, samples were pretreated by filtration with micro-pole-filters (0.45 µm). The visible spectra were determined by a Shimadzu UV-3150 UV-vis-NIR scanning spectrometer. 2.4. Ultrafiltration Separation of Sulfite Cooking Liquor. Ultrafiltration was carried out with a Millipore labscale TFF ultrafiltration separation system. The molecular weight cutoffs of membranes were 30 000 and 3000 kDa. 3. Results and Discussion 3.1. Selection of Wave Range. It is well-known that sulfite cooking liquor is a very complicated solution that is mainly composed of lignin sulfonate, carbohydrates, water, inorganic materials, and other organic compounds. The objective we want to achieve is to select a characteristic absorption wave range in which there is only absorption of lignin in the cooking liquor and no other absorption of carbohydrates, water, and inorganic materials in cooking liquor. This is the key point in the study. According to Lambert-Beer’s law, the characteristic absorption spectrum of matter is a kind of quantitative analysis tool. In the field of lignin analysis, the infrared and ultraviolet regions of the lignin spectrum have been the subjects of comparatively numerous investigations,17,18 while information on the visible region is sparse.19 In an earlier study, Norrstrom studied the ultraviolet, visible, and infrared spectra of lignin isolated from pulp and that of cooking liquor of bisulfite cooks. Although the lignin from the spent liquor had a lighter absorptivity than lignin from the pulp, both showed a continuous increase in absorptivity with decreasing wavelength in the visible light range (400-550 nm).20 After scanning the cooking liquor, saccharide (including glucose, xylose, and mannose), water, and sulfonated lignin with a spectrophotometer, we got four spectrograms (Figure 1-4). As seen in Figure 1, many compositions in sulfite cooking liquor have strong ultraviolet absorption, and the overlap exists in the infrared region, so we concentrated on the visible wavelength domain or near-infrared region for liquor analysis. The absorption of lignin sulfonate (Figure 2) is very intensive in the ultraviolet wavelength range, and the absorption in the visible wavelength domain is quite similar to that of sulfite cooking liquor. Being one of the main compositions in sulfite cooking liquor, the spectral absorptions of polysaccharides such as D-glucose, D-mannose, and D-xylose are presented in the ultraviolet region (Figure 3). The spectral absorption that comes from another component, water, has two distinct absorption

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Figure 2. UV-vis-NIR absorption spectrum of lignin sulfonate. Figure 5. UV-vis-NIR absorption spectrum of graded samples of sulfite cooking liquor with ultrafiltration separation: (1) filtered component with membrane of 3000 kDa, (2) retained component with membrane of 3000 kDa, and (3) retained component with membrane of 300 00 kDa.

Figure 3. UV-vis-NIR absorption spectrum of the saccharides (1) mannose, (2) xylose, and (3) glucose.

Figure 6. Vis characterization of delignification course during sulfite pulping with Masson’s pine.

Figure 4. UV-vis-NIR absorption spectrum and differential spectrum of sulfite cooking liquor and water: (1) sulfite cooking liquor, (2) water, (3) differential spectrum of sulfite cooking liquor and water.

peaks, at 968 and 1194 nm, in our spectrum scanning result (Figure 4). The differential spectrum between sulfite cooking liquor and water shows that the absorption of water has no influence on the spectrum of cooking liquor in the region of ultraviolet and visible light. Analyzing the above four figures, considering the smooth part of the absorption spectrum and the relationship between absorbance and relative error of measurements, the visible wavelength range (460-580 nm) for prediction of pulp Kappa number has been selected, in which the absorption of cooking liquor mainly comes from the lignin sulfonate, while xylose, mannose, glucose, and water in sulfite cooking liquor had no obvious absorption in this wavelength range. Therefore, through the measurement of the absorbance of cooking liquor, pulp Kappa number (residual lignin content) could be predicted online during pulping. 3.2. Validation of Wave Range. The ultrafiltration separation of sulfite cooking liquor from Masson’s pine proved that high molecular weight fraction (R30000) had much stronger absorption than the middle molecular weight fraction (R3000)

Figure 7. Comparison of sulfite pulp Kappa number determined in the laboratory and predicted with the principal components analysis-artificial neutral network model.

and low molecular weight fraction (P3000) in the 460-580 nm wavelength range. The IR spectra of the fractions also showed that the high molecular weight fraction had very high lignin content, while the low molecular weight fraction contains many carbohydrates. These results indicated that high molecular lignin sulfonate had much contribution to the absorption of the cooking liquor in the visible wave range. Figure 5 is the spectrum of graded samples of sulfite cooking liquor with ultrafiltration separation. The sulfite cooking delignification process with visible spectrum has been studied by measuring the absorbance (λ ) 460 nm) of cooking liquor during the pulping process with a spectrophotometer. As shown in Figure 6, the relation curve of absorbance and pulping time can be divided into three parts. The flat slope of the first part (0-120 min) means that it is the early stage of delignification; the delignification rate is relatively slow. The slope of the second part

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Table 1. Standard Errors of Various Predicting Models for Sulfite Kappa Number model

460 nm

490 nm

510 nm

530 nm

550 nm

580 nm

MLR

SRA

PCR

ANN

SRA-ANN

PCA-ANN

standard error of prediction (%)

1.67

1.51

1.45

1.35

1.29

2.18

1.37

1.33

1.48

1.32

1.43

1.27

Table 2. Comparison of Determined Kappa Number (KND) and That Predicted (KNP) with the PCA-ANN Model

KND KNP

KND KNP

KND KNP

1

2

3

4

5

6

7

8

9

10

11

12

13

17.8 19.1

17.5 18.1

19.2 19.8

18.6 19.8

17.5 19.0

18.2 19.3

18.0 19.1

18.3 19.1

18.6 19.0

20.8 19.7

17.4 19.3

19.6 18.4

18.9 18.0

14

15

16

17

18

19

20

21

22

23

24

25

26

17.7 18.0

18.0 18.0

17.8 18.8

18.2 18.1

18.5 17.9

15.8 18.3

19.9 17.7

18.3 17.5

16.7 17.6

17.8 17.6

16.1 17.6

16.6 18.1

18.4 17.5

27

28

29

30

31

32

33

34

35

36

37

38

17.1 17.3

17.1 17.2

18.9 16.9

15.2 17.0

19.1 17.4

18.9 17.7

18.4 16.5

16.8 16.8

19.4 16.8

17.5 16.9

18.8 17.8

19.4 17.7

(120-270 min, the part between points A and B) rises, indicating that the bulk delignification process is on going fast. It is then followed by the even much faster rate of rising in the last part, which shows that it is the final stage of delignification before blowing out of pulp. The delignification study shows that the sulfite cooking delignification process can be observed with selected visible wavelength, where the result agrees with the description of ref 21. These results verify that the selected visible wavelength range is appropriate for measuring pulp Kappa number with online analysis of cooking liquor. In addition, they establish the theoretical basis for the further development of online Kappa number determination model with visible spectroscopy. 3.3. Mathematical Models for Kappa Number Prediction. At the end of pulping, the brown stock and the spent liquor were sampled separately. The Kappa number of the washed pulp and the absorbance of the spent liquor were determined separately. From 25 sets of calibration samples, several chemometrics methods, unary linear regression (ULR), multivariable linear regression (MLR), stepwise regression analysis (SRA), principal component regression (PCR), and artificial neural network (ANN) were applied for data processing. In Table 1, it could be found that the standard error of Kappa number predicted by principal components analysis-artificial neutral network (PCA-ANN) model was the lowest in all kinds of models. The standard error of 38 validation samples was 1.27, which could satisfy the accuracy for Kappa number control in industry (about 2 Kappa number). When large multivariate data sets are analyzed, it is often desirable to reduce their dimensionality. Principal component analysis is one technique for doing this. Through the analysis of the PCA-ANN program, which was developed with Matlab software, the first principal component with 97.8% contribution to variance was found. As a linear combination of the original variables, it represented the principal information of raw spectroscopic data; the dimensionality reduction has been made with it from six dimensions (the absorbance at 460, 490, 510, 530, 550, and 580 nm of cooking liquor) to one principal component. Being the input of artificial neural network, the principal component was trained by ANN, and the comparison results of Kappa number determined by titration and predicted by PCA-ANN model are shown in Table 2. In order to quantitatively demonstrate the agreement between the predicted and determined Kappa numbers, direct comparisons of the pulp Kappa numbers of 38 validation samples were made, as shown in Figure 7. As compared with the results of other models, the results with PCA-ANN model in the figure were more

centralized on the ideal correlated line of two Kappa numbers with two different methods, indicating the agreement between the Kappa number predicted with the optical method and the Kappa number determined by the traditonal titration. Therefore, the PCA-ANN regression model has better accuracy in predicting Kappa number during sulfite pulping. 3.4. Controlling the End Point of Sulfite Pulping. After a period of running the sulfite pulp mill (Figure 8), the results showed that there was not only the feasibility but also the good effect of controlling the sulfite pulping with the optical method. The proportion of first-class pulp has improved from 55% to 70%. According to the absorbance of the cooking liquor, the residual pulping time could also be predicted. In most cases the pulp Kappa number after pulping could be controlled within (2 units around the desired value of 18.9. Figure 9 is a comparison of the statistical analysis for control of pulp Kappa number with the optical and manual methods. The current manual methods for controlling pulping end point are as follows: (1) the typical empirical method based on the comparison of the color of the cooking liquor with that of last

Figure 8. Schematic diagram of online optical pulp Kappa number measuring system used in the present study.

Figure 9. Comparison of controlled pulp quality in the end of sulfite pulping with optical and manual methods.

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batch, (2) the chemical analysis of total acid and combined acid concentrations of the cooking liquor, and (3) the comparison of pulping records with those of the last batch, whose pulp quality is already known. Owing to the multiform uncertain human elements, the pulping end points are determined differently and the pulp rank differences are generated. As shown in Figure 9, it is clear that the proportion of firstclass pulp with optical method is higher than that of manual method. Most of the qualities of pulp met the requirement of techniques (within (2 units around the desired value 18.9) and were closed to the desired Kappa number. Although the percentage of pulp quality with the manual method was not very low, the quality of pulps was unstable and far from the desired Kappa number. It is difficult to control the pulp Kappa number at the desired value with the manual method. Furthermore, how much better is the optical method compared to the manual method? The answer is visualized in the following statistical analysis. The means (KN) and variances (σ) of pulp Kappa numbers with the optical method and manual method were (the subscript “o” for optical method, the subscript “m” for manual method) KNo ) 17.69 σo ) 0.77 KNm ) 16.92 σm ) 1.11 According to the statistical knowledge, this means that approximately 95% of pulp Kappa number could be controlled within the range of 17.69 ( 1.54 for the optical method and 16.92 ( 2.22 for the manual method. Therefore, using the optical method can not only control the pulp Kappa number within the qualified range but also increase the Kappa number, retain more lignin in the pulp, improve the yield of pulp, shorten pulping time, reduce the usage of steam, and bring a series of economic benefits. 4. Conclusions It was shown that lignin sulfonate in sulfite cooking liquor had a characteristic absorption in the region of 460-580 nm, which was selected as the determinated wavelength range in the experiment, while saccharide and water in sulfite cooking liquor have no obvious absorption and the high molecular weight lignin sulfonate fraction had a much greater contribution to the absorption of the cooking liquor than the low molecular weight fraction in the visible wave range. The pulp Kappa number was determined quantitatively by the absorbance of cooking liquor. Several chemometrics methods were applied for data processing. The results of data processing showed that the predicting models determined by most of the methods had good learning accuracy and predicting accuracy, and the best model of all was determined by the principal components analysis-artificial neutral network method. On the basis of studies in the laboratory, the results have been applied in a sulfite pulp mill. The results showed that the method was successful in controlling sulfite pulp Kappa number and predicting the end point of pulping. Compared to manual method, the optical method was much better and could bring a series of economic benefits. Acknowledgment The authors thank everyone involved in State Key Laboratory of Pulp & Paper Engineering, for fruitful cooperation. Financial

support from the Special Foundation for Guangdong Province Major Science & Technology Program (No. 2008A090300016) and the cooperation programs of Industry-Academia-Research of Guangdong Province and Ministry of Education of the P. R. China (No. 2007A090302069) is gratefully acknowledged. The authors also would like to thank the reviewers for their insightful comments. Literature Cited (1) Kappa Number of Pulp, Test Method T 236; TAPPI Press: Atlanta, GA. (2) Jiang, Z. H.; Audet, A.; van Lierop, B.; Berry, R. Kappa Number Testing with Better Repeatability and at Lower Cost. Pulp and Paper Technical Association of Canada (PAPTAC) 90th Annual Meeting Montreal, Quebec, Canada, 27-29 Jan, 2004; PAPTAC: Montreal, Quebec, Canada, 2004; pp C111-C115. (3) Chai, X.-S., Zhu, J.-Y. Method for Rapidly Determining a Pulp Kappa Number Using Spectrophotometry. U.S. Patent 6,475,339, 2002. (4) Kubulnieks, E.; Lundqvist, S. O.; Pettersson, T. The STFI OPTIKappa Analyzer: Applications and Accuracy. TAPPI J. 1987, 70 (11), 38– 42. (5) Yeager, R. Online K Number Analysis Smoothes Fiberline Operation at Northwood Kraft. Pulp Paper 1998, 72 (9), 87-88–91-92. (6) Bentley, R. G. An Optical Approach to the Measurement of the Lignin Content of Kraft Pulps. Part A: Using Ultraviolet Measurements. Proc. SPIE 1986, 665, 265–279. (7) Marton, J.; Sparks, H. E. Determination of Lignin in Pulp and Paper by Infrared Multiple Internal Reflectance. TAPPI J. 1967, 50 (50), 363– 368. (8) Berben, S.; Rademacher, J.; Sell, L.; Easty, D. Estimation of Lignin in Wood Pulp by Diffuse Reflectance Fourier-Transform Infrared Spectrometry. TAPPI J. 1987, 70 (11), 129–133. (9) Faix, O.; Welkener, U.; Patt, R. Method for Controlling the Digestion of Pulp by IR Spectroscopy. U.S. Patent 4,743,339, 1988. (10) Yuzak, E.; Lohrke, C. At-Line Kappa Number Measurement by Near-Infrared Spectroscopy. In TAPPI Pulping Conference, 1993; TAPPI Press: Atlanta, GA, 1993; pp 663-671. (11) Barringer, N.; Norder, S. Method and Arrangement for Determining Fibre Properties by Near-Infrared-Spectroscopy. U.S. Patent 5,536,942, 1996. (12) Badenlid, R.; Andersson, S.; Stromberg, E. L.; Bergstrom, J. Method in Connection with the Production of Pulp, Paper or Paperboard. U.S. Patent 01/79816 A1, 2001. (13) Birkett, M.; Gambino, M. Estimation of Pulp Kappa Number with Near-Infrared Spectroscopy. TAPPI J. 1989, 72 (9), 193–197. (14) Van Fleet, R. J.; Millar, O. D. Continuous In-Line Kappa Measurement System. U.S. Patent 5,953,111, 1999. (15) Poke, F. S.; Wright, J. K.; Raymond, C. A. Predicting Extractives and Lignin Contents in Eucalyptus globulus Using Near Infrared Reflectance Analysis. J. Wood Chem. Technol. 2004, 24 (1), 55–67. (16) Trung, T. P.; Leclerc, D. Method for Determining Lignin Content in Chemical Pulps Using Raman Spectrometry. U.S. Patent 6,551,451, 2003. (17) Pearl, I. A. The Chemistry of Lignin; Academic: New York, 1967. (18) Brauns, F. E.; Brauns, D. A. The Chemistry of Lignin: Supplment Volume; Academic Press: New York, 1960. (19) Brauns, F. E.; Brauns, D. A. The Chemistry of Lignin: Supplement Volume; Academic Press: New York, 1960. (20) Norrstro¨m, H. Light Absorbing Properties of Spruce Bisulfite Pulp. 1. Effect of Cooking Conditions, Part 2. Effect of Lignin Preserving Bleaching. SVensk Papperstidning 1970, 73 (15), 455–461. (21) Long, Y. Q. The Comparison of Miscanthus sacchariflorus’s Delignification in Sulphate Cooking and Bisulfite Cooking. Pulp Paper China 1984, 4 (4), 3.

ReceiVed for reView December 29, 2008 ReVised manuscript receiVed March 22, 2009 Accepted March 25, 2009 IE802008R