Upload
michal-jablonsky
View
45
Download
0
Embed Size (px)
Citation preview
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
67
RELATIONSHIPS BETWEEN ELEMENTAL CARBON CONTENTS
AND HEATING VALUES OF LIGNINS
Jablonský, M.*, Ház, A., Orságová, A., Botková, M., Šmatko, L., Kočiš, J.
Slovak University of Technology, Faculty of Chemical and Food Technology,
Institute of Polymer Materials, Department of Chemical Technology of Wood, Pulp and Paper,
Radlinského 9, 831 07 Bratislava, Slovak Republic
e-mail: [email protected]
Abstract
Two precipitated lignins and seven commercial lignins were used in this study for predicting the correlation
between higher heating values (HHV) and their carbon content. There was found a highly significant linear
correlation between the HHV of the lignin and its C contents. The content of C was determined by elemental
analysis. The HHV (MJ/kg) of lignin was calculated using the following equation: HHV = 0.40659(C), for which
the correlation coefficient was: 0.9987. HHV prediction was applied to samples of 17 different lignins and data
for 53 samples of several biomass resources obtained from literature. The HHVs calculated from this equation
showed a mean difference of 0.49 % for different lignins and 2.13 % for biomass resources.
Keywords
Lignin, higher heating values, prediction
1. INTRODUCTION
The worldwide increase in the price and cost of petroleum and coal has created an interest in alternative source
of raw materials. Lignin is a complex phenolic polymer found in biomass feedstocks and biomass derived
products. The Nature produces vast amount of 150 – 170 billion metric tons of biomass per year [1] by
photosynthesis, 20 % of which can be assigned to the class of amorphous polymer consisting of methoxylated
phenylpropane structures. Lignin composition varies in different groups of vascular plants being guaiacyl- (G),
guaiacyl/syringyl- (GS), and hydroxyphenyl/guaiacyl/syringyl-type (HGS) lignin characteristic for softwoods
(woody gymnosperms), hardwoods (woody angiosperms), and graminaceous plants (non-woody angiosperms),
respectively [2]. The structural differences between isolated lignins have been investigated using UV-Vis and
FTIR spectroscopies, size exclusion chromatography, differential scanning calorimetry, nuclear magnetic
resonance, thermogravimetric analysis and heating values. In a review by Vargas-Moreno et al. [3], 104 models
of prediction of heating value for different resources were presented. These models are used to predict the HHV
of unrenewable and renewable raw materials comprising all types of agricultural and silvicultural vegetation.
The models use the results of proximal and ultimate analysis (weight percentage of C, H, N, S, O and other
elements). Proximal analysis is used to evaluate the moisture, volatile material, fixed carbon and ash in biomass
resources. In this study the HHVs obtained for different lignin samples are compared with their elemental carbon
content. A new prediction formula was used to calculation the HHV of lignins and biomass resources from
literature.
2. EXPERIMENTAL
2.1 Liquor and lignin characterization
Black liquor (modified alkaline anthraquinone cooking) characterization
The annual plants used for obtaining black liquor were kindly supplied by OP Papirna Ltd. (Olsany, Czech
Republic). Obtained black liquor present the following characteristics: pH of 12.9 ± 0.3 (was determined by
digital Jenway Model 3510 pH-meter), density 1.242 (g/mL) was determined by measuring the weight of the
black liquor in a known volume previously weighed.
Black liquor (kraft cooking) characterization
Kraft black liquor was kindly supplied by Bukoza Holding Inc. (Hencovce, Slovak Republic). The black liquor
presents the following characteristics: pH of 12.8 ± 0.4 was determined by digital Jenway Model 3510 pH-meter,
density of 1.358 (g/mL) was determined by measuring the weight of the black liquor in a known volume
previously weighed.
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
68
Commercial lignins
Borresperse N, BorrementCa 120, Vanisperse CB were purchased from BorregardLignoTech, Marasperse N-22
from Daishowa Chemical Inc., Orzan S from ITT Rayonier Inc., DP – 02, DP – 03 from Biotech.
2.2 Lignin recovery from black liquor
The precipitation of lignin from black liquor was initially studied as a single step process in which dilute acid
solution (5 % w/w) was added to the black liquor with the pH adjusted to the desired value. 100 mL of the black
liquor was treated with different amount of diluted sulphuric acid to obtain a final pH value 3. After complete
precipitation the content of each flask was filtered through a pre-weighed oven-dry filter paper using a vacuum
filtration unit. The precipitated lignin was twice washed with hot water to remove impurities. The lignin was
then dried at 25°C for 24 hour, using a lyophilisation equipment (LYOVAC TG) up to reaching constant weight.
2.3 Elemental analysis
Total nitrogen (N), total carbon (C), total hydrogen (H) and total sulphur (S) contents of all samples were
determined by dry combustion using a Vario Macro Cube C/H/N/S-analyser (Elementar, Hanau, Germany). Two
replicates were measured and the mean standard errors were 0.54 % for C, 0.04 % for N, 0.41 % H and 0.84 %
for S.
2.4 Higher heating value
HHV was determined by FTT Calorimetric Bomb as stipulated by EN ISO 1716. Benzoic acid was used as a
standard with higher heating value of 26.454 MJ/kg.
3. RESULTS AND DISCUSSION
To utilize lignin as a fuel in different applications requires, knowledge of its heating value is required. Several
studies investigated the heating values of isolated lignins and different biomass species. Pure lignin has a rather
higher heating value than cellulose and hemicelluloses. For this reason, lignin could be used as bio-fuel. On the
average, the heating value of pure dry lignins is 22.5 ± 3.9 MJ/kg. The weight percentages of elements C, H, N,
O, S, ash and HHV of the isolated precipitated lignins and commercial lignins are listed in Tab. 1. The H/C
ranges of the lignin are approximately 0.078 and 0.115 and their atomic O/C ratios range from 0.116 to 0.737.
Tab.1 Elemental analyses, ash content, O/C and H/C atomic ratios, heating value
Samples Elemental analysis (% wt)
H/C O/C Ash
(%)
HHV
(MJ/kg) N C H S O
Vanisperse 0.12 52.54 4.08 2.96 6.11 0.078 0.116 34.18 20.61
Orzan S 0.09 45.42 5.05 5.15 33.46 0.111 0.737 10.83 18.30
Borrement Ca120 0.14 46.63 5.35 5.62 28.96 0.115 0.621 13.13 19.46
Marasperse N 22 0.14 43.52 4.68 6.28 20.42 0.108 0.469 24.96 18.17
Boresperse N 0.14 44.11 4.65 6.49 21.27 0.106 0.482 23.34 18.36
DP-03 0.14 48.12 5.08 7.15 17.10 0,106 0,355 22.41 17.99
DP-02 0.16 42.86 4.38 5.12 27.84 0.102 0.649 19.64 17.31
Lignin Olsany 1.18 63.64 5.93 0.49 28.34 0.093 0.445 0.43 25.88
Kraft lignin Bukoza 0.28 55.68 4.62 3.91 31.65 0.083 0.568 3.85 23.62
The range of HHV measured in this study was between 17.31 and 25.88 MJ/kg with an overall mean of 19.96
MJ/kg. The HHV results obtained in this study by using a calorimeter were used to create mathematical models
by linear regression analysis. HHV linear regression of the precipitated and commercial lignins with carbon
content resulted in a square of the correlation coefficient (r2) value of 0.9987 (Fig. 1). The HHV of a lignin is a
function of its carbon content. For the model the following formula was used:
HHV = 0.40659*(C) (1)
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
69
where HHV is the higher heating value of fuel (MJ/kg) and C is the carbon content (wt %) determinate by
elemental analysis. The created model was used to calculate the HHV and then compared with the HHV data
obtained experimentally.
0 10 20 30 40 50 60 70
0
5
10
15
20
25
30
HH
V (
MJ/k
g)
C (wt %)
Equation y = a + b*x
Adj. R-Square 0,9987
Value Standard Error
D Intercept 0 --
D Slope 0,40659 0,00442
Fig.1 Plot of HHV vs. C content and calculated regression data
The average values of elemental analysis and experimentally determined HHV for 13 lignin samples analysed in
literature and 4 precipitated samples are given in Tab. 2. For all 17 samples, it was observed that C and HHV
ranges were within 29.67 – 66.2 wt % and 12.04 – 27.3 MJ/kg, respectively. The HHVs calculated by equation
showed a mean difference 0.49 %.
Tab.2 Content of C and HHV of different lignin types used in this study.
Sample C
(wt %)
Experimental
HHV
(MJ/kg)
HHV from
Eq. 1
(MJ/kg)
Diff.
(%) Ref.
Precipitated lignin from rice straw 63.67 25.36 25.89 -2.08 [4]
Commercial lignin 48.20 20.38 19.60 3.84 [4]
Precipitated lignin from rice straw (Two steps process) 63.61 26.65 25.86 2.95 [4]
LignoBoost Kraft Lignin 65.10 27.10 26.47 2.33 [5]
LignoBoost Kraft Lignin 63.60 26.60 25.86 2.79 [5]
LignoBoost Kraft Lignin 66.20 27.30 26.92 1.41 [5]
LignoBoost Kraft Lignin 34.50 14.03 14.00 -0.20 [6]
LignoBoost Kraft Lignin 33.90 13.78 13.76 -0.20 [6]
LignoBoost Kraft Lignin 33.27 13.53 13.50 -0.20 [6]
LignoBoost Kraft Lignin 32.62 13.26 13.23 -0.22 [6]
LignoBoost Kraft Lignin 31.22 12.69 12.66 -0.24 [6]
LignoBoost Kraft Lignin 29.67 12.06 12.04 -0.24 [6]
LignoBoost Kraft Lignin 62.50 25.41 25.40 -0.05 [6]
Precipitated lignin Olsany (72 % wt H2SO4) 64.90 26.29 26.39 -0.37
un
pub
lish
ed
dat
a
Precipitated lignin Olsany (50 % wt H2SO4) 64.84 26.20 26.36 -0.62
Precipitated lignin Olsany (25 % wt H2SO4) 63.64 26.69 25.88 3.05
Precipitated lignin Olsany (5 % wt H2SO4) 65.75 26.86 26.73 0.47
Black liguor Olsany 34.24 13.36 13.92 -4.20
A database of carbon content as well as experimental HHV of several biomass samples [7] were obtained from
the literature and is presented in Tab. 3. The database includes 53 sets of data from different studies conducted
by researchers from all over the world. For all 53 samples, it was observed that C and HHV ranges were within
36.1 -54.6 and 14.7 – 22.6 MJ/kg, respectively. The HHVs calculated by using our equation showed a mean
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
70
difference of 2.13 %. The formula developed in this work show good agreement with experimental results for
lignin, but also biomass samples.
Tab.3 Content of C and HHV of several biomass types used in this study [7]
Sample C
(wt %)
Experimental
HHV
(MJ/kg)
HHV
from Eq. 1
(MJ/kg)
Diff.
(%) Lit.
Pistachio soft shell 45.53 18.57 18.51 0.31 [8]
Coconut shell 50.22 20.50 20.42 0.40 [9]
Wheat straw 42.95 17.99 17.46 2.93 [9]
Rice husk 38.50 14.69 15.65 -6.56 [9]
Sugarcane bagasse 45.48 18.73 18.49 1.27 [9]
Bamboo wood 48.76 20.55 19.83 3.53 [9]
Olive stones 49.00 20.23 19.92 1.52 [10]
Almond shell 48.80 19.92 19.84 0.39 [10]
Sunflower seed shell 51.70 17.60 21.02 -19.44 [11]
Esparto plant 46.94 19.10 19.09 0.08 [12]
Shea meal 48.56 19.80 19.74 0.28 [13]
Sugarcane bagasse 43.79 17.70 17.80 -0.59 [13]
Cotton stalk 47.07 17.40 19.14 -9.99 [13]
Peanut shell 47.40 18.60 19.27 -3.61 [14]
Hazelnut shell 50.90 19.90 20.70 -4.00 [14]
Dried grains – solubles 50.24 21.75 20.43 6.08 [15]
Wet grains 52.53 21.95 21.36 2.70 [15]
Corn stover 45.48 17.93 18.49 -3.13 [15]
Coffee husk 47.50 19.80 19.31 2.46 [16]
Sugar cane straw 43.50 17.19 17.69 -2.89 [16]
Marabú 48.60 20.72 19.76 4.63 [16]
Soplillo 48.80 22.58 19.84 12.13 [16]
Casuarina equisetifolia leaf 46.12 18.48 18.75 -1.47 [17]
Lantana Camara leaf 45.01 18.50 18.30 1.08 [17]
Oil palm fruit bunch 45.90 16.96 18.66 -10.04 [17]
Olive kernel 54.60 22.40 22.20 0.89 [18]
Olive kernel shell 53.20 21.40 21.63 -1.08 [18]
Olive cake 53.70 21.60 21.83 -1.08 [18]
Olive kernel 52.44 19.90 21.32 -7.14 [19]
Forest residue 53.16 19.50 21.61 -10.84 [19]
Cotton residue 47.03 16.90 19.12 -13.15 [19]
Alfalfa stems 47.17 18.67 19.18 -2.73 [20]
Rice straw 38.24 15.09 15.55 -3.04 [20]
Switch grass 46.68 18.06 18.98 -5.09 [20]
Willow wood 49.90 19.59 20.29 -3.57 [20]
Hybrid poplar 50.18 19.02 20.40 -7.27 [20]
Almond hulls 47.53 18.89 19.33 -2.30 [20]
Oak wood (small branch) 48.76 19.20 19.83 -3.26 [21]
Oak wood (medium branch) 48.62 19.24 19.77 -2.75 [21]
Oak wood (large branch) 48.57 19.17 19.75 -3.02 [21]
Pine chips 49.66 19.79 20.19 -2.03 [22]
Corn straw 44.73 17.68 18.19 -2.87 [22]
Rape straw 46.17 18.34 18.77 -2.36 [22]
Palm kernels 48.34 20.71 19.65 5.10 [22]
B-wood 50.26 20.05 20.44 -1.92 [22]
Pepper plant 36.11 15.39 14.68 4.60 [22]
Biomass mix 49.59 18.40 20.16 -9.58 [22]
Sugarcane bagasse 47.20 17.32 19.19 -10.80 [16]
Ipil ipil 48.30 20.22 19.64 2.88 [16]
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
71
Rice husk 38.20 16.47 15.53 5.70 [16]
Olive pitts 52.80 21.59 21.47 0.57 [20]
Pistachio shell 50.20 18.22 20.41 -12.02 [20]
Almond shells 49.30 19.49 20.04 -2.85 [20]
4. CONCLUSION
One new simply empirical correlation based on elemental analysis of lignin has been developed via linear
regression method for prediction of HHV. This correlation is easy to apply via simple manual calculation and
require only carbon contents (wt % dry materials basis).
5. ACKNOWLEDGEMENTS
This work was supported by the Slovak Research and Development Agency under the contract No. APVV-0850-
11.
6. REFERENCES
[1] Rosillo-Calle, F.; Groot, P. de; Hemstock, S.L.; Woods, J. Non-woody Biomass and Secondary Fuels. F.
Rosillo-Calle. The Biomass Assesment Handbook: Bioenergy for a Sustainable Environment. Sterling,
VA: Earthscan, 2007.
[2] Sun, SN, Li, MF, Yuan, TQ, Xu, F, Sun, RC.: Sequential extractions and structural characterization of
lignin with ethanol and alkali from bamboo (Neosinocalamusaffinis). Industrial crops and products, 2012,
Vol. 37, No.1: 51-60.
[3] Vargas-Moreno, J.M, Callejón-Ferre, A.J., Pérez-Alonso, J., Velázquez-Mártí, B.: A review of the
mathematical models for predictiong the heating value of biomass materials. Renewable and Sustainable
Energy Reviews, (2012), Vol. 16, No. 5, 3065-3083.
[4] Minu, K., KurianJiby, K., Kishore, V.V.N.: Isolation and purification of lignin and silica from black liquor
generated during the production of bioethanol from rice straw. Biomass & Bioenergy, (2012), Vol. 39, No.
SI, 210-217.
[5] Tomani, P.: The lignoboost process. Cellulose Chem. Technol., (2010), Vol. 44, No. 1-3, 53-58.
[6] Black Liquor Lignin Recovery as a Means for Pulp Mill Capacity Raise. 43rd Pulp and Paper International
Congress & Exhibition, 4-6.October, 2010,
http://www.abtcp.org.br/arquivos/File/ABTCP%202010/Congresso/06%20de%20outubro/Recupera%C3%
A7%C3%A3o%20de%20.
[7] Yin, Ch-Y. Prediction of higher heating values of biomass from proximate and ultimate analyses. Fuel 90
2011, 1128-1132.
[8] Demiral, I., Atilgan, N.G., Şensöz, S.: Production of biofuel from soft shell of pistachio (Pistaciavera L.).
ChemEngCommun, (2009), Vol. 196, No. 1-2, 104–115.
[9] Channiwala, S.A., Parikh, P.P.: A unified correlation for estimating HHV of solid, liquid and gaseous
fuels. Fuel, (2002), Vol. 81, No. 8, 1051–1063.
[10] Cordero, T., Marquez, F., Rodriguez-Mirasol, J., Rodriguez, J.: Predicting heating values of
lignocellulosics and carbonaceous materials from proximate analysis. Fuel, (2001), Vol. 80, No. 11, 1567–
1571.
[11] Haykiri-Acma, H., Yaman S.: Effect of biomass on burnouts of Turkish lignites during co-firing. Energy
Convers Manage, (2009), Vol. 50, No. 9, 2422–2427.
[12] Debdoubi, A. El-Amarti, A., Colacio, E.: Production of fuel briquettes from esparto partially pyrolyzed.
Energy Convers Manage, (2005), Vol. 46, No. 11-12, 1877–1884.
[13] Munir, S., Daood, S. S., Nimmo, W., Cunliffe, A.M., Gibbs, B.M.: Thermal analysis and devolatilization
kinetics of cotton stalk, sugar cane bagasse and shea meal under nitrogen and air atmospheres
BioresourTechnol, (2009), Vol. 100, No. 3, 1413–1418.
[14] Bonelli, P.R., Cerrella, E.G., Cukierman, A.L.: Slow pyrolysis of nutshells: characterization of derived
chars and of process kinetics. Energy Sources, (2003), Vol. 25, No. 8, 767–778.
4th
International Conference May 21-23, 2013 Tatranské Matliare
Renewable Energy Sources 2013 High Tatras, Slovak Republic
72
[15] Morey, R.V., Hatfield, D.L., Sears, R., Haak, D., Tiffany, D.G., Kaliyan, N.: Fuel properties of biomass
feed streams at ethanol plants. ApplEngAgric, (2009), Vol. 25, No. 1, 57–64.
[16] Suárez, J.A., Luengo, C.A., Felfli, F.F., Bezzon, G., Beatón, P.A.: Thermochemical properties of Cuban
biomass. Energy Sources, (2000), Vol. 22, No. 10, 851–857.
[17] Sugumaran, P., Seshadri, S.: Evaluation of selected biomass for charcoal production. J SciInd Res, (2009),
Vol. 68, No. 8, 719–723.
[18] Demirbas, A., Ilten N.: Fuel analyses and thermochemical processing of olive residues. Energy Sources,
(2004), Vol., 26, No. 8, 731–738.
[19] Vamvuka, D., Kakaras, E., Kastanaki, E., Grammelis, P.: Pyrolysis characteristics and kinetics of biomass
residuals mixtures with lignite. Fuel, (2003), Vol. 82, No. 15-17, 1949–1960.
[20] Jenkins, B.M., Baxter, L. L, Miles Jr., T.R., Miles T.R.: Combustion properties of biomass. Fuel Process
Technol, (1998), Vol. 54, No. 1-3, 17–46.
[21] Miranda, M.T., Arranz, J.I., Rojas, S., Montero, I.: Energetic characterization of densified residues from
Pyrenean oak forest Fuel, (2009), Vol. 88, No. 11, 2106–2112.
[22] Tortosa-Masiá, A.A., Buhre, B.J.P., Gupta, R.P., Wall, T.F.: Characterising ash of biomass and waste. Fuel
Process Technol, (2007), Vol. 88, No. 11, 1071–1081.