- Email: [email protected]
Thermal behavior and organic functional structure of poplar-fat coal blends during co-pyrolysis
Renewable Energy 136 (2019) 308e316
Contents lists available at ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
Thermal behavior and organic functional structure of poplar-fat coal blends during co-pyrolysis Shuxing Qiu a, b, Shengfu Zhang a, b, *, Xiaohu Zhou a, b, Qingyun Zhang a, b, Guibao Qiu a, b, Meilong Hu a, b, Zhixiong You a, b, Liangying Wen a, b, Chenguang Bai a, b a b
College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China Chongqing Key Laboratory of Vanadium-Titanium Metallurgy and Advanced Materials, Chongqing University, Chongqing 400044, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 July 2018 Received in revised form 17 December 2018 Accepted 3 January 2019 Available online 4 January 2019
The thermal behavior of poplar-fat coal (biomass-coal) blends and organic functional structure of formed coal-char in the co-pyrolysis temperature were investigated using Thermogravimetric analyzer, Differential scanning calorimetry, Mass spectrometry and Attenuated total reflection Fourier transform infrared spectroscopy analysis. Furthermore, the interactions between poplar and coal during copyrolysis were deduced. The results indicate that poplar decomposed prior to the decomposition of fat coal is not surprising, but results also indicate that the presence of poplar enhanced the thermal decomposition of fat coal at low temperature. The occurring interactions showed positive and negative effects with increasing temperature, which could be explained by chemical reaction and physical interaction, respectively. In the blends, these interactions lowered the apparent activation energy and frequency factor. The added poplar had a positive effect on decomposition of the organic functional groups. Interactions would indirectly cause higher hydrocarbon-generating potential and thermal maturity, and reduced aliphatic chains length and aromaticity. The synergistic effects between fat coal and poplar during co-pyrolysis occurred mainly at lower temperature. For the better application of poplar-fat coal blends, the suitable blending ratio of poplar to coal is below 16%. In addition, the pyrolysis temperature should be kept in 345e390 C to obtain biomass-coal tar. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Poplar-fat coal Co-pyrolysis Interaction Kinetics Coal-char structure
1. Introduction The use of biomass to replace fossil fuels has the potential to mitigate global warming and environmental pollution. Biomass has attracted extensive attention because it is a renewable and carbon neutral fuel and it currently provides about 14% of the world’s energy supply [1], and is the world’s fourth largest source of energy. However, the widespread use of biomass is constrained because of its low heating value and seasonal availability. Biomass is the only renewable energy source that can be converted into solid, liquid and gas [2], and its pyrolysis characteristics is very similar to that of coal. This means that there are opportunities in some processes to
* Corresponding author. College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China. E-mail addresses: [email protected] (S. Qiu), [email protected] (S. Zhang), [email protected] (X. Zhou), [email protected] (Q. Zhang), [email protected] (G. Qiu), [email protected] (M. Hu), [email protected] (Z. You), [email protected] (L. Wen), [email protected] (C. Bai). https://doi.org/10.1016/j.renene.2019.01.015 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
use biomass in place of coal to reduce greenhouse gases emission. In most cases, a full replacement by biomass would lead to deterioration in performance because its lower density and calorific value than coal. The level of substitution is often based on the level of changes that can be tolerated. However, what is not considered as often in studies is the interaction between biomass and coal when they are used together as a blend. The aim of this study is to investigate some of these interactions and, in particular, determine if some of these could actually be mutually advantageous. Understanding the co-pyrolysis of biomass and coal is important because this is the first step in their co-utilization and influences the other reactions that follow, hence, this area been widely studied [3e5]. In many previous co-pyrolysis studies no clear synergistic effect was established. Wu et al. [6] studied the thermal behaviors of biomass model compounds and coal by thermogravimetric analysis, and results indicated that positive and negative synergies exist in co-pyrolysis, depending on biomass type, mixed ratio and temperature range. Krerkkaiwan et al. [7] found higher gas and lower char yields than predicted values during co-pyrolysis of rice
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
straw/Leucaena leucocepha wood and Indonesian coal, which can be termed synergistic effects. Yuan et al. [8] confirmed that synergies enhance the denitrification rate of the rice straw/chinar leaves/sawdust and bituminous coal blends during rapid pyrolysis, and decrease (NH3þHCN) yields and more nitrogen convert to N2, which reduce environmental pollution. However, several works reported the absence of remarkable synergistic effects between biomass and coal due to the separate pyrolysis temperature interval [9,10]. Vuthaluru [11] reported that a linear relationship exists between the char yields generated during co-pyrolysis of wood waste/wheat straw with coal and biomass mass ratio at different temperature. Moghtaderi et al. [12] investigated the changes in gases evolved from the co-pyrolysis of pine and coal at different heating rate, and no synergistic effects could be found based on the allowable error in results. It can be concluded from previous studies that synergistic effect is a key factor for achieving effective coutilization of biomass and coal. However, many aspects of copyrolysis are still uncertain such as detail features of thermal behaviors and the evolution of structures. The evolution of functional groups in coal during heating process can be analyzed by Fourier transform infrared spectrum (FTIR) [13,14]. Montiano et al. [15] studied the structural parameters of co-pyrolysis tar by semiquantitative analysis from the FTIR spectra. However, to our best of knowledge, there is no report on structural evolution of coal-char generating from co-pyrolysis of biomass and coal by FTIR analysis. This work aims to study thermal behavior and organic functional structure during the co-pyrolysis of poplar-fat coal (biomasscoal) blends with Thermogravimetric analyzer (TGA), Differential scanning calorimetry (DSC), Mass spectrometry (MS) and Attenuated total reflection Fourier transform infrared spectroscopy (ATRFTIR) analysis, and discuss the synergistic effect in the co-pyrolysis process. The thermal behaviors of mixtures were studied, including weight loss rate, characteristic temperature, heat flow, released products, deviations of calculated and experimental values of TG and DSC curves, and kinetics including apparent activation energy (E) and frequency factor (A) during co-pyrolysis process. The ATRFTIR spectra of coal-chars in the co-pyrolysis were also investigated to identify changes in the functional groups. The structural parameters including A-factor, C-factor, CH2/CH3 and Aar/Aal were deduced from ATR-FTIR spectra. 2. Materials and methods 2.1. Materials Fat coal (FC) supplied from Anshan Iron and Steel in northeast China and poplar (P) taken from Gansu province in China were materials considered in this study. Proximate, ultimate and ash analysis of the individual materials are shown in Table 1, which were measured by Chinese Standard Methods GB/T 212-2008, GB/T 31391-2015 and GB/T 1574-2007. The samples were dried in an oven at a temperature of 110 C for two hours. Both the FC and P were ground and sieved to obtain a particle size of 74e150 mm for use in the experiments. The experiments carried out on five blends of P and FC. The levels of P, on a mass basis, in the blend were 4%, 8%, 12%, 16% and 32%, and these are given the notations of FCP4, FCP8, FCP12, FCP16 and FCP32, respectively. 2.2. TGA-DSC-MS analysis TGA-DSC experiments were carried out in a Netzsch STA 449C analyzer. About 10.0 ± 0.5 mg of the sample was used in an experiment to reduce the influence of heat and mass transfer limitations. The samples were heated from ambient temperature to 1000 C at three heating rates of 10, 20, 30 C/min under high purity nitrogen
309
Table 1 Proximate, ultimate and ash analysis of samples. Sample Proximate analysis (wt. %) Moisture, air dry Ash, dry Volatile, dry Fixed carbon, dry Ultimate analysis (dry, wt. %) Carbon Hydrogen Oxygen Nitrogen Sulphur Other H/C, ratio of atom O/C, ratio of atom Ash analysis (dry, wt. %) SiO2 Al2O3 TiO2 Fe2O3 MgO CaO Na2O K2O
FC
P
1.74 9.61 28.67 61.72
4.18 5.76 78.86 15.38
77.27 4.61 5.68 1.36 1.47 9.61 0.72 0.06
45.95 6.30 41.92 0.18 0.13 5.52 1.65 0.68
45.93 22.72 3.65 7.82 1.04 9.49 1.34 1.28
27.46 7.24 1.33 4.90 3.20 33.84 2.77 13.50
at flow rates of 50 ml/min. Then the weight and heat flow changes of each sample can be determined and recorded simultaneously. Relative pyrolysis characteristic parameters including Tin, Ti, Ri and Mf were obtained by thermogravimetric curves and the derivative of thermogravimetric curves (DTG), where Tin is the initial decomposition temperature. According to the American Society for Testing and Materials (ASTM), the value of Tin is defined by the intersection point of two lines. One is the connecting line of 5% and 50% weight loss of total weight loss in the first stage; the other is the extension baseline. Ti is the temperature of DTG peak and Ri is the decomposition rate corresponding to Ti. Mf represents the residual mass of samples at the final temperature. It is to be noted that all the parameters above were obtained when temperature is over 150 C. A mass spectrometry (MS, PFEIFFER VACUUM OMNI star, QMA 200M), was coupled to above TG analyzer through a heated line with stainless steel tube capillary to measure the released products. The mass-to-charge ratio (m/z) recorded were 2, 16, 28 and 44, which stand for H2, CH4, CO and CO2, as most probable parent molecules [4,16]. The products signals were normalized to that from 1 mg of samples because of the sample weight difference in each experiment. To reduce the experimental error and achieve the precision required, the TGA-DSC-MS experiments for the each sample have been done in triplicate. The three samples were carried out in the same experimental conditions. The results showed that the error value of the pyrolysis parameters obtained was under 2%. To infer interactions between coal and biomass during copyrolysis process, the measured values for the blends were compared with calculated ones from two individual fuels. The calculated values were obtained using the simple additive model principle, where the properties of the binary mix depended solely on the individual fuel properties and their mass proportions. When experimental results show deviations from calculated values, it is called that these are caused interactions between two components during co-pyrolysis. The calculated values were determined using Eqs. (1) and (2). In order to further investigate the degree of interactions, DM, DHF were defined with the difference between calculated and experimental values and could be shown by Eqs. (3) and (4).
310
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
Mcalculated ¼ aMfat coal þ bMpoplar
(1)
HFcalculated ¼ aHFfat coal þ bHFpoplar
(2)
DM ¼ Mcalculated Mexperimental
(3)
DHF ¼ HFcalculated HFexperimental
(4)
where Mcalculated, Mexperimental and HFcalculated, HFexperimental are the calculated and experimental mass weight/heat flow values of blends during co-pyrolysis separately; a and b are the mass ratios of FC and P in the blends separately; Mfat coal, Mpoplar and HFfat coal, HFpoplar are the experimental mass weight/heat flow values of FC and P, respectively. 2.3. Kinetics analysis A non-isothermal method was selected to investigate the kinetics of the co-pyrolysis process. As the co-pyrolysis of FC and P involves complex reactions, simple kinetic models are not applicable. The distributed activation energy model (DAEM) is widely used for the study of complex pyrolysis reactions and has been shown to describe the pyrolysis process in over wide temperature and heating rate range well [17e19]. Compared with the traditional DAEM, Miura and Maki [20] obtained a simpler and more accurate method of finding the activation energy (E) and frequency factor (A) using a step function. The Miura integral method can be applied in DAEM without the need to assume, in advance, the form of the activation energy distribution function and the fixed frequency factor values. The E and A of pyrolysis process are obtained directly from the TG curves, which means that the Miura integral method can be applied to study the kinetics in this work. The corresponding theoretical basis and derivation processes could be found from the literatures [17e21] and the final equation could be expressed as Eq. (5).
b AR E þ 0:6075 ln 2 ¼ ln E RT T
(5)
where b is the heating rate (K/s), T is the temperature (K), A is the frequency factor (1/s), R is the universal gas constant (8.314 J/ mol$K) and E is the activation energy (J/mol). 2.4. ATR-FTIR analysis The residual chars collected from the co-pyrolysis characteristic temperature were ground to less than 74 mm and then were subjected to ATR-FTIR. The generated spectra of the samples were recorded on a Nicolet iS5 FTIR in the absorbance mode, equipped with the attenuated total reflection (ATR) diamond coupling. The samples were analyzed at room temperature, from a collection of 32 scans per spectrum measured at a resolution of 4 cm1 with wavenumber from 4000 to 400 cm1. The FTIR spectra are appropriate for identifying functional groups in coals, tars and chars [13e15,22]. Previous studies have successfully used both peak values and integral area of FTIR spectra to provide qualitative and semi-quantitative analysis of the functional groups [23,24]. To analyze the differences of coal-char macromolecular structures during co-pyrolysis, semi-quantitative analysis were carried out using the integrated area (IA) to calculate selected structural parameters. A-factor, C-factor, CH2/CH3, and Aar/ Aal were calculated by the peak integrated area according to Dutta et al. [14], Xin et al. [25], Qiu et al. [26] and Li et al. [13]. The relevant
equations are as follows.
. IA3000 2800cm1 A factor ¼ IA3000 2800cm1 þ IA1650cm1 (6) . IA1800 1520cm1 C factor ¼ IA1800 1650cm1 (7) . IA2950cm1 CH2 =CH3 ¼ IA2920cm1 þ IA2860cm1 þ IA2890cm1
(8)
. Aar =Aal ¼ IA1650 1520cm1 IA3000 2800cm1
(9)
where A-factor stands for hydrocarbon-generating potential, Cfactor is suggested to reflect thermal maturity or the contribution degree of carbonyl (C]O), CH2/CH3 describes the aliphatic chain length, and Aar/Aal represents aromaticity. 3. Results and discussion 3.1. Pyrolysis characteristics The experimental TG, DTG and DSC curves, obtained at a heating rate of 10 C/min, for FC, P and their blends are illustrated in Fig. 1. In the same figure, calculated values are also shown. The corresponding pyrolysis characteristic parameters (Tin, Ti, Ri, etc.) of the individual fuels and their blends are listed in Table 2. From Fig. 1(a) and (b), it can be observed that the decomposition of FC starts at about 320 C and from 320 to 600 C weight loss is significant, increasing with increasing temperature. The corresponding maximum weight loss rate (Rmax) is 0.158%$min1 at 474 C and the total weight loss (Mt) is 22.69 wt.% of the initial sample weight. On the other hand, for the P sample, thermal decomposition begins at around 250 C and from that point to 400 C weight loss is very obvious resulting in the release of over 90% of total volatiles. The relevant Rmax is 0.82%$min1 at 345 C and about 75 wt.% of the initial weight occurs in the pyrolysis process. The Mt and Rmax of P are about 3 times and 5 times higher than those corresponding values for FC. Results also show that FC has higher decomposition temperature and wider thermal decomposition region. These findings are consistent with expectations, in that P has higher volatiles and lower fixed carbon values as indicated in Table 1. As Fig. 1(c) shows, three stages corresponding to endothermic and exothermic events exist in FC pyrolysis process. The first stage with pyrolysis temperature below 150 C is attributed to the moisture evaporation. With the pyrolysis temperature ranging from 150 to 570 C, several endothermic peaks can be observed, which mainly resulted from coal devolatilization [27]. An obvious exothermic event can be seen in the last stage (570e1000 C), which is due to the combination of coal polycondensation reaction and mineral matters decomposition. For the P sample, the endothermic event happened in the pyrolysis process, which is due to the large decomposition of P as described in TG-DTG analysis. The distinct differences in thermal behaviors between FC and P are not only related to their chemical components but also their structural properties. Biomass (P) is mainly made up of hemicellulose, cellulose and lignin. Fig. 2 shows the fitted DTG curves for P at 150e600 C. According to previous studies [28], changes in the
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
311
Fig. 2. The three main chemical components of P.
Fig. 1. TG, DTG and DSC curves for FC, P and their blends with b ¼ 10 C/min: (a) TG, (b) DTG, (c) DSC.
temperature range of 230e350 C can be attributed to hemicellulose decomposition, while that in the temperature range of 280e400 C mainly to cellulose decomposition. Lignin decomposition occurs at a much wider temperature of 200e550 C. The macromolecular structure of those components is mainly linked by weak ether bonds (R-O-R) with bond energies of 380e420 kJ/mol that can withstand temperatures of less than 400 C. On the other hand, the coal (FC) is mainly formed of polycyclic aromatic hydrocarbons linked by C]C bonds with high bond energy of 1000 kJ/ mol [9] and, therefore, more resistant to thermal decomposition at lower temperatures. Therefore, most of the material in P is decomposed before 400 C and the peak of Rmax is consistent with that of cellulose decomposition. The TG and DTG curves for the mixed samples indicate that some deviations existed between experimental and calculated values. The TG curves show that calculated values are greater than experimental values in every mixed sample, and the deviations increase with increasing mass ratio of P. For the DTG results, the shape and position of the curves remain unchanged with increasing the mass ratio of P. The Ti (i ¼ 1, 2, 3) values also have no obvious changed, indicating that the introduction of P into FC does not affect the relative pyrolysis temperature at the same heating rate. However, the peak intensity related to Ri (i ¼ 1, 2, 3) shows an evident change with the introduction of P. As the mass ratio of P increases, the value of R1 assigned to P increases from 0.051 to 0.26%$min1, while the R2 value related to FC decreases from 0.149 to 0.107%$min1, and the value of R3 that is attributed to the second reaction shows a slight decrease. The deviations between experimental values and calculated values for Ri increase with increasing
Table 2 Pyrolysis parameters of FC, P and their blends with b ¼ 10 C/min. Parameters
FC
P
FCP4
FCP8
FCP12
FCP16
FCP32
Exp.
Exp.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Tin ( C) T1 ( C) T2 ( C) T3 ( C) R1 (%$min1 101) R2 (%$min1 101) R3 (%$min1 101) Mf (%)
323 e 474 674 e 1.58 0.20 77.31
248 345 e e 8.20 e e 24.43
235 345 474 678 0.51 1.49 0.19 74.79
228 345 474 674 0.48 1.53 0.19 75.21
242 345 475 673 0.91 1.43 0.19 73.04
236 345 475 678 0.78 1.49 0.19 73.49
245 345 474 678 1.28 1.41 0.19 70.63
237 345 474 680 1.05 1.45 0.18 71.80
246 345 475 679 1.60 1.32 0.18 68.28
238 345 474 674 1.28 1.41 0.18 70.02
247 345 475 674 2.60 1.07 0.17 61.61
242 345 474 674 2.12 1.28 0.17 64.52
312
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
P addition. When the mass ratio of P is increased, calculated R1 increases from 0.048 to 0.212%$min1, and calculated R2 decreases from 0.153 to 0.128%$min1. The calculated R1 is lower than experimental values, while the calculated R2 is higher than experimental values. The corresponding deviations in R1 values increase from 0.003 to 0.048%$min1, and for R2 the deviation increases from 0.004 to 0.021%$min1. The observed deviations indicate that the addition of P affects both the decomposition of FC and P, indicating that interactions have occurred between FC and P in the copyrolysis process. Fig. 3 shows the release of gaseous products during co-pyrolysis of FC and P. Thermal decomposition of FC, P and their blends mainly leads to the release of H2, CH4, CO and CO2. For H2, CH4 and CO, it can be seen that their release rate of blends is larger than that of FC or P, which is consistent with the findings of Haykiri-Acma [29]. However, the rate of CO2 decreases when added P, which may be due to the large release of CH4, CO and ash components influences. These results indicate that the addition of P would promote the decomposition of volatiles and, consequently, increase the devolatilization rate. As the ultimate analysis (Table 1) describes, the atomic ratios of both H/C and O/C in P are two and eleven times higher than the respective values in FC. The higher levels of eH and eOH radicals produced from the pyrolysis of P have played a synergistic role in improving the decomposition of FC. On the other hand, the cellulose and hemicellulose from poplar are linked by bglycosidic bonds, which would break down into hydrogenous radicals and influence FC during co-pyrolysis [30]. At the same time, these hydrogenous radicals inhibit the formation of aromatic rings and prevent the recombination and cross-linking reactions of other free-radicals [29], which would result in increasing the release rate of light molecular compounds, eg. H2, CH4, and CO. Further, large amount of the alkali and alkaline earth metal (AAEMs) (as high as 50.11%) would also catalyze the reactions between volatiles and char to produce more gases [31]. Therefore, interactions would occur during co-pyrolysis process of FC and P, and these could result in the increase of devolatilization rate, which is consistent with the TG-DTG analysis. The DM and DHF term in Eqs. (3) and (4) defined the degree of the interactions are shown in Fig. 4. As Fig. 4(a) shows, with increasing blending ratio of P, the values of DM have an ascending trend. It can be seen that two turning points, located in 240 C and
Fig. 3. Mass spectra of gas release from FC, P and their blends with b ¼ 10 C/min.
Fig. 4. Differences between calculated and experimental values from TG and DSC curves with b ¼ 10 C/min: (a) DM from TG, (b) DHF from DSC.
650 C (640e650 C), exist in each curves. Furthermore, an obvious change of DM is found in this region (240e650 C). As shown in Fig. 4(b), the difference between the experimental and calculated heat flow values rises when added P. It can be seen two weak peaks in the region of 240e650 C. The first one located at 240e390 C indicates that the pyrolysis of blends obtained from the experimental has a larger heat absorption than that from the calculated with pyrolysis temperature ranging from 240 C to 390 C, and the other one in 390e650 C implies that it would absorb smaller heat at further temperature. Taking the DM and DHF into consideration, approximately three regions are identified with increasing temperature. The fluctuation of region (I) is caused by the instable removal of moisture in the mixed samples. The deviation in region (III) is insignificant, probably because the most of the volatiles have been removed and the reactivity of the blend is unaffected. However, the difference between the DHF may be caused by the minerals reactions and their influences on the coal polycondensation in this region. The interactions mainly occur in region (II) at the temperature range of 240e650 C, where the pyrolysis of both P and FC are occurring at significant rates. Within region II, from 240 to 390 C there is a promotion effect but from 390 to 650 C, while there is an inhibition effect e both of which can be explained by the heat and mass transfer effects. With pyrolysis temperature increasing from 240 C to 390 C, larger heat absorption in co-pyrolysis of blends would make the decomposition rate increase, and then result in the DM rising, which indicates that added P would accelerate the decomposition of molecular
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
313
compounds in FC. When temperature is over 390 C, most of the components in P are already decomposed except for the lignin because its pyrolysis temperature is greater than 550 C and occurs at a wider temperature range. When heated, softening, melting and fusing accompanies the formation of lignin char [32]. This could result in impeding the release of volatiles and producing the large pores in FC, and further deteriorates the heat and mass transfer ability within the mixture. Inorganic minerals in P could improve the reactivity of FC but probably has a non-dominant effect. Therefore, the experimental pyrolysis of blends has a smaller heat absorption than that of the calculated for decomposition. Consequently, the decomposition rate of blends decreases, and the DM declines. This can be regarded as an inhibition effect in the FC decomposition process with the addition of P. During co-pyrolysis, interactions occur mainly before the formation of semi-coke and they have either a promoting or inhibiting effect. The first is mainly caused by chemical reaction while second is mainly through physical interaction. This study shows that significant synergistic effects occur only at lower pyrolysis temperatures. 3.2. Kinetics analysis Interactions between FC and P occur at temperatures from 240 to 650 C, and the corresponding reaction conversions from x ¼ 0.2 to x ¼ 0.8. The kinetics parameters including E and A at different conversions can be obtained by DAEM methods. The value of E is the lowest energy and determines whether decomposition reaction occurs, while A shows the number of effective collisions between reaction molecules. Large values of E and A indicate that the reaction proceeds with greater difficulty and is more complex. To investigate the influence of P on the co-pyrolysis, it is necessary to study the kinetics of the co-pyrolysis process using the Miura integral method. Arrhenius plots of FC, P and their blends at various conversions are shown in Fig. 5. From the plot of ln(b/T2) vs 1/T for different conversion values, the E values were determined from the slope of the lines. The next step involved determining the A values using Eq. (5). The results shown in Fig. 5 are expressed quantitatively in Table 3. The high correlation coefficients (R2 > 0.940) obtained indicate that a high level of confidence can be given to the determined E values. On the other side, the apparent activation energy and frequency factor of blends samples vary with the different reaction conversion, indicating that more than one single mechanism exists during the pyrolysis of FC and P blends. A linear relationship between E and ln(A) shows that the kinetic compensation effect occurred in the poplar pyrolysis process, which agrees with the previous work [33]. For the FC and blends, with the increase of activation energy, the frequency factor also keeps a rising trend. As the previous study described [34], the compensation effect would be resulted from the ‘isokinetic’ temperature in homogeneous systems. However, coal is a mixture of organic and mineral matters, which would cause the nonlinear relationships between E and ln(A) during pyrolysis process of FC and blends. In addition, previous studies confirmed that the values of E in solid e state reactions are in 50e350 kJ/mol, implying that E values obtained in this work are also reasonable [35,36]. It can be seen from Table 3, the values of E and A of FC are 163.306 kJ/mol and e25.849 s1, respectively, while those of P are 106.348 kJ/mol and e19.728 s1, indicating that the decomposition of FC is harder and more complex than that of P. In addition, the values of E and A for both FC and P show that decomposition is more difficult as conversion increases. For the mixed samples, increasing P addition decreases the average E value from 149.582 to 90.799 kJ/ mol, and the average A value decreases from e21.867 to e14.932 s1.
Fig. 5. Arrhenius plots of FC, P and their blends at various conversion from x ¼ 0.2 to x ¼ 0.8 for experimental values.
The fact that the E value of the mix is lower than that of P when P addition reaches 16%, indicates that there has been interactions between FC and P during co-pyrolysis. Similar conclusions were reached in the previous study [37] and were mainly attributed to the release of hydrogen and hydroxyl radical and the catalytic effects of alkali and alkaline earth metals (AAEMs) in biomass (P). Therefore, the blending ratio of poplar to coal should be below 16% to control the deterioration in performance obtained from the replacement of coal by biomass within a reasonable range.
314
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
Table 3 Kinetic parameters of FC, P and their blends.
a FC
P
FCP4
FCP8
FCP12
FCP16
FCP32
E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
Average
141.918 27.036 0.999 77.378 14.917 0.990 152.103 24.140 0.994 112.508 20.179 0.999 105.770 20.382 0.978 108.423 20.184 0.996 101.00 19.372 0.999
160.593 25.509 0.975 83.835 16.048 0.999 144.531 23.775 0.999 102.190 17.738 0.956 115.164 16.785 0.998 93.758 16.752 0.991 104.13 19.591 0.996
169.796 29.349 0.994 93.002 17.753 0.999 158.073 23.808 0.999 101.763 17.223 0.886 115.544 21.291 0.925 80.835 13.788 0.972 97.56 17.863 0.999
156.496 24.085 0.967 103.155 19.587 0.999 151.938 23.936 0.999 99.394 16.189 0.907 69.001 11.357 0.989 80.601 13.238 0.948 92.16 16.443 0.993
180.246 29.318 0.999 105.843 19.889 0.997 161.589 23.413 0.996 126.119 20.701 0.956 96.956 16.262 0.918 80.940 12.444 0.882 91.51 16.088 0.996
171.951 26.081 0.992 111.031 20.775 0.999 161.854 24.867 0.999 122.348 19.106 0.996 127.654 21.248 0.956 68.589 9.832 0.993 84.42 12.332 0.955
182.061 28.629 0.999 116.820 21.703 0.995 159.942 23.695 0.989 133.547 20.629 0.975 125.312 20.152 0.916 86.074 12.574 0.994 98.65 19.950 0.999
165.924 24.529 0.999 120.778 22.360 0.998 152.221 22.655 0.999 105.206 15.289 0.937 114.422 17.309 0.956 101.005 14.842 0.989 73.57 10.187 0.975
165.515 27.162 0.998 120.570 22.097 0.971 154.062 22.002 0.980 145.317 21.616 0.988 118.081 17.243 0.910 110.104 16.102 0.999 103.04 16.431 0.999
166.750 23.966 0.991 115.533 20.942 0.967 144.605 20.786 0.996 109.572 15.191 0.985 103.167 14.296 0.854 118.361 19.143 0.970 80.43 11.506 0.975
168.123 27.056 0.983 122.233 22.110 0.968 133.224 16.798 0.959 137.282 19.237 0.997 114.501 15.759 0.904 109.177 15.261 0.999 90.91 12.931 0.970
115.281 14.864 0.898 113.354 21.219 0.976 149.564 20.371 0.999 93.671 11.586 0.978 139.072 19.311 0.922 93.113 17.284 0.997 79.26 10.500 0.938
178.317 28.453 0.978 98.993 17.063 0.918 120.863 14.025 0.859 145.739 18.743 0.996 139.684 19.055 0.999 110.100 14.372 0.953 83.75 10.926 0.826
163.306 25.849 0.982 106.348 19.728 0.983 149.582 21.867 0.982 118.051 17.956 0.966 114.179 17.650 0.940 95.468 15.063 0.976 90.799 14.932 0.971
3.3. ATR-FTIR spectra of coal-char The evolution of functional groups is the most obvious feature in the devolatilization process. The effects of biomass on the evolution of mixed-sample functional groups cannot be neglected. Information of the functional groups in coal-char or char can be obtained by infrared spectrum detection. In addition, the proposed synergistic effect can be confirmed by analyzing the evolution of functional groups. To obtain the best information, samples of FC, P and FCP16 was heated to 345, 390, 475 and 650 C, these four temperatures correspond to: the temperature of Rmax of P, the temperature at which most of P has decomposed, the temperature of Rmax of FC and, the temperature at which most of FC has decomposed. The ATR-FTIR spectra at these temperatures and also at room temperature were obtained and shown in Fig. 6(a)-(f). The spectra are
divided into ten regions and the corresponding assignments are shown in Table 4. All the samples under heating are featured by a similar distribution of functional groups. However, the peak intensity is affected by raw material type and temperature. For the case of FC and P, the spectra of FC are characterized by strong free eOH at 37003600 cm1, aromatic CeH stretching at 3030 cm1, aromatic C]C stretching vibrations at 1600 cm1 and CeH aromatic out-of-plane deformation at 950-750 cm1 (880, 805, and 745 cm1 peaks are correspond to the vibration of substituted aromatic rings with one, two or three, and four adjacent CeH groups). While P is characterized by strong eOH stretching at 3385 cm1, aldehyde C]O stretching at 1730 cm1, aliphatic ether CeOeC and alcohol CeO stretching at 1150-950 cm1. The different functional groups define the pyrolysis characteristics of FC and P. With increase in temperature, the intensity of some bands decreases or disappears. The broad region at 3600-3100 cm1 is assigned to eOH stretching vibrations, which is confirmed to be attributed to intermolecular H bonds and associated OH groups at the terminal of the aromatic clusters, and these functional groups decompose readily [38]. The bond energy reflects the difficulty in breaking the functional group. Generally, functional groups with lower bond energy decompose into small molecule groups to form gas and macromolecular structure by addition reaction. These functional groups include aliphatic CeH, carbonyl C]O, aromatic/ aliphatic CeOeC and alcohol CeO stretching vibrations, which is
Table 4 Band assignments for ATR-FTIR spectra of samples [13e15,22].
Fig. 6. ATR-FTIR spectra of FC, P and their blends at different temperature: (a) and (b) room temperature, (c) 345 C, (d) 390 C, (e) 475 C, (f) 650 C.
Band (cm1)
Assignments
1 2 3 4 5 6 7 8
3700e3600 3600e3100 3100e3000 3000e2800 1800e1650 1650e1520 1520e1350 1350e1150
9 10
1150e950 950e750 750-720
free OH OH stretching aromatic CeH stretching aliphatic CeH stretching carbonyl C]O stretching aromatic C]C ring stretching aliphatic CH2 and CH3 deformation aromatic ether CeOeC, phenolic CeO, and ester CeOeOeC stretching aliphatic ether CeOeC and alcohol CeO stretching CeH aromatic out-of-plane deformation polymethylenic chains (n 4) rocking
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
consistent with the MS result. Aromatic C]C rings with higher bond energy are difficulty to decomposed at low temperature. When temperature is over 650 C, most of functional groups disappear except for aromatic C]C and a few CeO stretching vibrations. It is noteworthy that at 650 C the char from P still has strong aliphatic CeH and CeH aromatic out-of-plane deformation vibration compared to the coal-char from FC. A possible reason could be that P is an inert material. Therefore, there is no solidification reaction in the pyrolysis process and thus no obvious polycondensation reaction between macromolecule aromatic rings. The obvious synergistic effect can be observed by contrasting the ATR-FTIR spectra of FC coal-char and P char with that of FCP16 coal-char at the same temperature. Form Fig. 6(c)-(e), it can be seen that the peak intensity of C]C ring of FCP16 coal-char is slightly lower than that of FC coal-char and P char, indicating that the C]C ring can be consumed during co-pyrolysis. The peak at 1695 cm1 which related to the carbonyl C]O stretching vibrations is observed in the FC coal-char and P char but not in FCP16 coal-char. The peaks at 1260 cm1 and 1200 cm1 which attributed to aromatic ether CeOeC and ester CeOeOeC stretching vibrations are detected in the P char but not in FC coal-char and FCP16 coal-char. This indicates that interactions have occurred between two fuels during co-pyrolysis, which is consistent with the TGA results. It can be inferred that some active substances presented in the volatiles of P have been adsorbed onto the surface of coal particles and reacted with the coal matrix. Unstable functional groups in the coal matrix react with these active substances causing in a loss in mass of the coal particles. At the same time, the early decomposed volatiles from FC can also react with the P matrix to accelerate the decomposition of functional groups present in P. At the higher temperatures, the synergistic interactions reduce and even disappear. Structural parameters from the infrared spectra can usually be used to provide information on coal-char characteristics. Due to the peaks overlapping, the actual spectra cannot be easily separated to represent individual functional groups. The spectral intensity of each functional group is obtained using a curve-fitting method. In the region of 3000-2750 cm1 and 1800-1480 cm1, Fig. 7 shows FC coal-char at 345 C determined using this method. In this study, structural parameters of A-factor, C-factor, CH2/CH3 and Aar/Aal are calculated using Eqs. (6)e(9) and the values listed in Table 5. From the spectra of the raw materials, the decomposition of P is easier than that of FC because P has greater hydrocarbongenerating potential (A-factor), and lower thermal maturity (Cfactor) and aromaticity (Aar/Aal). That P has lower values of CH2/CH3 is associated with the chemical compounds present. Both cellulose and hemicellulose are formed by the polymerization of monosaccharides and lignin contains a few aliphatic CeH stretching vibrations. For all the samples, at increasing temperature, the structural parameters show a decreasing tendency except for Aar/Aal. In spite of these changes, it is still possible to conclude that all the changes in structural parameters for FCP16 coal-char cannot be attributed to the contribution of FC coal-char and P char. There are clear deviations between calculated and experimental values. The addition of P decreases the aliphatic chain length and aromaticity, and increases the thermal maturity and hydrogen-generation potential of mixed samples, which resulted in higher decomposition reactivity of the mixed samples. This suggests that there are synergistic interactions happening during co-pyrolysis. At 345 C, the decomposition of P is the most significant reaction during co-pyrolysis. Part of hydrogen-rich volatiles adsorb onto the matrix of FC and promote the early decomposition of aliphatic chains. When the macromolecule structure of the FC matrix breaks down, part of aromatic rings can be stripped from coal matrix. These aromatic rings have a high activity and can cause
315
Fig. 7. Curve-fitting of region of 1800-1480 cm1 and 3000-2750 cm1 of FC coal-char at 345 C: (a) 1800-1480 cm1, (b) 3000-2750 cm1.
Table 5 Structure parameters deduced from ATR-FTIR spectra of coal-chars.
25 C 345 C
390 C
475 C
650 C
Samples
A-factor
C-factor
CH2/CH3
Aar/Aal
FC P FC P FCP16 FC P FCP16 FC P FCP16
0.306 0.583 0.250 0.295 0.268 [a 0.169 0.113 0.229 [ 0.114 0.067 0.129 [ e
0.225 0.604 0.363 0.535 0.247 Yb 0.190 0.441 0.232 [ 0.095 0.208 0.076 Y e
1.658 1.146 3.409 1.303 1.753 Y 1.476 1.227 1.231 Y 1.412 0.790 1.189 Y e
2.266 0.716 4.914 2.394 2.729 Y 3.003 7.856 3.360 Y 7.744 13.851 6.724 Y e
a
Higher than calculated values which obtained from simple additive model principle. b Lower than calculated values which obtained from simple additive model principle.
hydrogenation reactions between aromatic rings and free hydrogen to form cycloalkanes. The oxygen in carbonyl C]O has a strong electron-absorbing ability, which facilitates nucleophilic addition reactions involving the carbon atom and negatively charged H or OH radicals. The addition of P accelerates the consumption of carbonyl C]O due to its higher eH and eOH contents in the volatiles. This results in lower CH2/CH3, Aar/Aal and C-factor values and higher A-factor values as seen for FCP16 coal-char. With rising temperatures, there are still interactions but the intensity reduces gradually because of lower volatiles levels. When temperature is
316
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
over 390 C, the influence of P on FC is more related to their differences in physical properties, and these influence the heat and mass transfer processes that take place. Consequently, the changes in the structural parameters for FC are more in line with expectations. The observed smaller deviations in structural parameters can be attributed earlier interactions. It turns out that the interactions are beneficial to increase the hydrogen-generating potential, the chain length of the aliphatics and thermal maturity, and decrease the aromaticity of mixed coal-chars at low temperature. Combined with TGA-DSC-MS analysis, the pyrolysis temperature should be kept in 345e390 C to increase the devolatilization rate and hydrogen-generating potential to produce the biomass-coal tar as much as possible.
[9]
[10]
[11] [12] [13] [14]
4. Conclusions
[15]
The two fuels were studied separately and then in blends during co-pyrolysis. As expected, poplar was easier to decompose than the fat coal and, consequently, resulting in higher maximum weight loss rate and the total weight loss. Interactions mainly occurred in the main pyrolysis region of fat coal and poplar, and results indicated that at increasing temperatures there were promotion and inhibition effects, which could be attributed to chemical reaction and physical action respectively. The real synergistic effect occurred at lower temperature. The mixed sample had lower values of apparent activity energy and frequency factor in the interaction region. In the region where interactions occurred, the aromatic C] C of mixed coal-char had a tendency to decrease, and peaks of carbonyl C]O, ether CeOeC and ester CeOeOeC vibrations in mixture coal-char were much lower compared to those in the individual fuels at same temperature. Interactions caused higher hydrocarbon-generating potential, length of aliphatic chains and thermal maturity, and reduced the aromaticity of the mixed coalchars. For the better use of poplar-fat coal blends, the blending ratio of poplar to coal should be below 16%. Furthermore, the pyrolysis temperature should be kept in 345e390 C to produce biomass-coal tar as much as possible.
[16]
Acknowledgements This work was supported by the National Natural Science Foundation of China (Project No. 51474042 and 51774061) and the Fundamental Research Funds for Central Universities (Project No. 106112017CDJQJ138801). The authors also acknowledge the support provided by the Fund of Chongqing Science and Technology (Project No. cstc2018jscx-msyb0988). References [1] X. Zhang, W. Yang, W. Blasiak, Modeling study of woody biomass: interactions of cellulose, hemicellulose, and lignin, Energy Fuel 25 (10) (2011) 4786e4795. [2] F. Abnisa, W.M.A.W. Daud, A review on co-pyrolysis of biomass: an optional technique to obtain a high-grade pyrolysis oil, Energy Convers. Manag. 87 (2014) 71e85. [3] H.Y. Meng, S.Z. Wang, L. Chen, Z.Q. Wu, J. Zhao, Thermal behavior and the evolution of char structure during co-pyrolysis of platanus wood blends with different rank coals from northern China, Fuel 158 (2015) 602e611. [4] K. Jayaraman, M.V. Kok, I. Gokalp, Thermogravimetric and mass spectrometric (TG-MS) analysis and kinetics of coal-biomass blends, Renew. Energy 101 (2017) 293e300. [5] P. Yangali, A.M. Celaya, J.L. Goldfarb, Co-pyrolysis reaction rates and activation energies of West Virginia coal and cherry pit blends, J. Anal. Appl. Pyrol. 108 (2014) 203e211. [6] Z.Q. Wu, S.Z. Wang, J. Zhao, L. Chen, H.Y. Meng, Synergistic effect on thermal behavior during co-pyrolysis of lignocellulosic biomass model components blend with bituminous coal, Bioresour. Technol. 169 (5) (2014) 220e228. [7] S. Krerkkaiwan, C. Fushimi, A. Tsutsumi, P. Kuchonthara, Synergetic effect during co-pyrolysis/gasification of biomass and sub-bituminous coal, Fuel Process. Technol. 115 (2013) 11e18. [8] S. Yuan, Z.J. Zhou, J. Li, X.L. Chen, F.C. Wang, HCN and NH3 (NOx precursors)
[17]
[18]
[19] [20] [21] [22]
[23]
[24]
[25]
[26]
[27]
[28]
[29] [30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
released under rapid pyrolysis of biomass/coal blends, J. Anal. Appl. Pyrol. 92 (2011) 463e469. A.K. Sadhukhan, P. Gupta, T. Goyal, R.K. Saha, Modelling of pyrolysis of coalbiomass blends using thermogravimetric analysis, Bioresour. Technol. 99 (17) (2008) 8022e8026. M.S. Masnadi, R. Habibi, J. Kopyscinski, J.M. Hill, X.T. Bi, C.J. Lim, N. Ellis, J.R. Grace, Fuel characterization and co-pyrolysis kinetics of biomass and fossil fuels, Fuel 117 (8) (2014) 1204e1214. H.B. Vuthaluru, Thermal behaviour of coal/biomass blends during co-pyrolysis, Fuel Process. Technol. 85 (2e3) (2004) 141e155. B. Moghtaderi, C. Meesri, T.F. Wall, Pyrolytic characteristics of blended coal and woody biomass, Fuel 83 (6) (2004) 745e750. W. Li, Y.M. Zhu, Structural characteristics of coal vitrinite during pyrolysis, Energy Fuel. 28 (6) (2014) 3645e3654. S. Dutta, C. Hartkopf-Froder, K. Witte, R. Brocke, U. Mann, Molecular characterization of fossil palynomorphs by transmission micro-FTIR spectroscopy: implications for hydrocarbon source evaluation, Int. J. Coal Geol. 115 (2013) 13e23. M.G. Montiano, A.M. Fernandez, E. Diaz-Faes, C. Barriocanal, Tar from biomass/coal-containing briquettes, evaluation of PAHs, Fuel 154 (2015) 261e267. mez, Co-firing of coal and manure biomass: a M. Otero, M.E. S anchez, X. Go TGeMS approach, Bioresour. Technol. 102 (17) (2011) 8304e8309. Y. Xu, Y.F. Zhang, Y. Wang, G.J. Zhang, L. Chen, Thermogravimetric study of the kinetics and characteristics of the pyrolysis of lignite, React. Kinet. Mech. Catal. 110 (1) (2013) 225e235. A. Soria-Verdugo, N. Garcia-Hernando, L.M. Garcia-Gutierrez, U. Ruiz-Rivas, Analysis of biomass and sewage sludge devolatilization using the distributed activation energy model, Energy Convers. Manag. 65 (2013) 239e244. M.G. Montiano, E. Diaz-Faes, C. Barriocanal, Kinetics of co-pyrolysis of sawdust, coal and tar, Bioresour. Technol. 205 (2016) 222e229. K. Miura, T. Maki, A simple method for estimating f(E) and k0(E) in the distributed activation energy model, Energy Fuel. 12 (5) (1998) 864e869. J. Cai, W. Wu, R. Liu, G.W. Huber, A distributed activation energy model for the pyrolysis of lignocellulosic biomass, Green Chem. 15 (5) (2013) 1331e1340. Z.Q. Wu, S.Z. Wang, J. Zhao, H.Y. Meng, Thermal behavior and char structure evolution of bituminous coal blends with edible fungi residue during co-pyrolysis, Energy Fuel. 28 (3) (2014) 1792e1801. X.G. Sun, The investigation of chemical structure of coal macerals via transmitted-light FT-IR microspectroscopy, Spectrochim. Acta A 62 (1e3) (2005) 557e564. J.A. Orrego, R.C. Hernandez, E. Mejia-Ospino, Structural study of colombian coal by fourier transform infrared spectroscopy coupled to attenuated total reflectance (FTIR-ATR), Rev. Mex. Fis. 56 (3) (2010) 251e254. H.H. Xin, D.M. Wang, X.Y. Qi, G.S. Qi, G.L. Dou, Structural characteristics of coal functional groups using quantum chemistry for quantification of infrared spectra, Fuel Process. Technol. 118 (2) (2014) 287e295. S. Qiu, S. Zhang, Y. Wu, G. Qiu, C. Sun, Q. Zhang, J. Dang, L. Wen, M. Hu, J. Xu, R. Zhu, C. Bai, Structural transformation of fluid phase extracted from coal matrix during thermoplastic stage of coal pyrolysis, Fuel 232 (2018) 374e383. Z. Niu, G. Liu, H. Yin, C. Zhou, Devolatilization behaviour and pyrolysis kinetics of coking coal based on the evolution of functional groups, J. Anal. Appl. Pyrol. 134 (2018) 351e361. E. Kastanaki, D. Vamvuka, P. Grammelis, E. Kakaras, Thermogravimetric studies of the behavior of lignite-biomass blends during devolatilization, Fuel Process. Technol. 77 (2002) 159e166. H. Haykiri-Acma, S. Yaman, Interaction between biomass and different rank coals during co-pyrolysis, Renew. Energy 35 (1) (2010) 288e292. S. Matsuoka, H. Kawamoto, S. Saka, What is active cellulose in pyrolysis? An approach based on reactivity of cellulose reducing end, J. Anal. Appl. Pyrol. 106 (2014) 138e146. D.M. Keown, J.I. Hayashi, C.Z. Li, Effects of volatileechar interactions on the volatilisation of alkali and alkaline earth metallic species during the pyrolysis of biomass, Fuel 87 (7) (2008) 1187e1194. D.L. Guo, H.Y. Yuan, X.L. Yin, C.Z. Wu, S.B. Wu, Z.Q. Zhou, Effects of chemical form of sodium on the product characteristics of alkali lignin pyrolysis, Bioresour. Technol. 152 (2014) 147e153. J. Cai, W. Wu, R. Liu, An overview of distributed activation energy model and its application in the pyrolysis of lignocellulosic biomass, Renew. Sustain. Energy Rev. 36 (2014) 236e246. D. Xu, M. Chai, Z. Dong, M.M. Rahmana, X. Yu, J. Cai, Kinetic compensation effect in logistic distributed activation energy model for lignocellulosic biomass pyrolysis, Bioresour. Technol. 265 (2018) 139e145. J. Wang, W. Lian, P. Li, Z. Zhang, J. Yang, X. Hao, W. Huang, G. Guan, Simulation of pyrolysis in low rank coal particle by using DAEM kinetics model: reaction behavior and heat transfer, Fuel 207 (2017) 126e135. J. Cai, R. Liu, New distributed activation energy model: numerical solution and application to pyrolysis kinetics of some types of biomass, Bioresour. Technol. 99 (8) (2008) 2795e2799. X.F. Zhu, K. Li, L.Q. Zhang, X. Wu, X.F. Zhu, Synergistic effects on thermochemical behaviors of co-pyrolysis between bio-oil distillation residue and bituminous coal, Energy Convers. Manag. 151 (2017) 209e215. Y. Guo, R.M. Bustin, Micro-FTIR spectroscopy of liptinite macerals in coal, Int. J. Coal Geol. 36 (3) (1998) 259e275.
Contents lists available at ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
Thermal behavior and organic functional structure of poplar-fat coal blends during co-pyrolysis Shuxing Qiu a, b, Shengfu Zhang a, b, *, Xiaohu Zhou a, b, Qingyun Zhang a, b, Guibao Qiu a, b, Meilong Hu a, b, Zhixiong You a, b, Liangying Wen a, b, Chenguang Bai a, b a b
College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China Chongqing Key Laboratory of Vanadium-Titanium Metallurgy and Advanced Materials, Chongqing University, Chongqing 400044, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 July 2018 Received in revised form 17 December 2018 Accepted 3 January 2019 Available online 4 January 2019
The thermal behavior of poplar-fat coal (biomass-coal) blends and organic functional structure of formed coal-char in the co-pyrolysis temperature were investigated using Thermogravimetric analyzer, Differential scanning calorimetry, Mass spectrometry and Attenuated total reflection Fourier transform infrared spectroscopy analysis. Furthermore, the interactions between poplar and coal during copyrolysis were deduced. The results indicate that poplar decomposed prior to the decomposition of fat coal is not surprising, but results also indicate that the presence of poplar enhanced the thermal decomposition of fat coal at low temperature. The occurring interactions showed positive and negative effects with increasing temperature, which could be explained by chemical reaction and physical interaction, respectively. In the blends, these interactions lowered the apparent activation energy and frequency factor. The added poplar had a positive effect on decomposition of the organic functional groups. Interactions would indirectly cause higher hydrocarbon-generating potential and thermal maturity, and reduced aliphatic chains length and aromaticity. The synergistic effects between fat coal and poplar during co-pyrolysis occurred mainly at lower temperature. For the better application of poplar-fat coal blends, the suitable blending ratio of poplar to coal is below 16%. In addition, the pyrolysis temperature should be kept in 345e390 C to obtain biomass-coal tar. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Poplar-fat coal Co-pyrolysis Interaction Kinetics Coal-char structure
1. Introduction The use of biomass to replace fossil fuels has the potential to mitigate global warming and environmental pollution. Biomass has attracted extensive attention because it is a renewable and carbon neutral fuel and it currently provides about 14% of the world’s energy supply [1], and is the world’s fourth largest source of energy. However, the widespread use of biomass is constrained because of its low heating value and seasonal availability. Biomass is the only renewable energy source that can be converted into solid, liquid and gas [2], and its pyrolysis characteristics is very similar to that of coal. This means that there are opportunities in some processes to
* Corresponding author. College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China. E-mail addresses: [email protected] (S. Qiu), [email protected] (S. Zhang), [email protected] (X. Zhou), [email protected] (Q. Zhang), [email protected] (G. Qiu), [email protected] (M. Hu), [email protected] (Z. You), [email protected] (L. Wen), [email protected] (C. Bai). https://doi.org/10.1016/j.renene.2019.01.015 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
use biomass in place of coal to reduce greenhouse gases emission. In most cases, a full replacement by biomass would lead to deterioration in performance because its lower density and calorific value than coal. The level of substitution is often based on the level of changes that can be tolerated. However, what is not considered as often in studies is the interaction between biomass and coal when they are used together as a blend. The aim of this study is to investigate some of these interactions and, in particular, determine if some of these could actually be mutually advantageous. Understanding the co-pyrolysis of biomass and coal is important because this is the first step in their co-utilization and influences the other reactions that follow, hence, this area been widely studied [3e5]. In many previous co-pyrolysis studies no clear synergistic effect was established. Wu et al. [6] studied the thermal behaviors of biomass model compounds and coal by thermogravimetric analysis, and results indicated that positive and negative synergies exist in co-pyrolysis, depending on biomass type, mixed ratio and temperature range. Krerkkaiwan et al. [7] found higher gas and lower char yields than predicted values during co-pyrolysis of rice
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
straw/Leucaena leucocepha wood and Indonesian coal, which can be termed synergistic effects. Yuan et al. [8] confirmed that synergies enhance the denitrification rate of the rice straw/chinar leaves/sawdust and bituminous coal blends during rapid pyrolysis, and decrease (NH3þHCN) yields and more nitrogen convert to N2, which reduce environmental pollution. However, several works reported the absence of remarkable synergistic effects between biomass and coal due to the separate pyrolysis temperature interval [9,10]. Vuthaluru [11] reported that a linear relationship exists between the char yields generated during co-pyrolysis of wood waste/wheat straw with coal and biomass mass ratio at different temperature. Moghtaderi et al. [12] investigated the changes in gases evolved from the co-pyrolysis of pine and coal at different heating rate, and no synergistic effects could be found based on the allowable error in results. It can be concluded from previous studies that synergistic effect is a key factor for achieving effective coutilization of biomass and coal. However, many aspects of copyrolysis are still uncertain such as detail features of thermal behaviors and the evolution of structures. The evolution of functional groups in coal during heating process can be analyzed by Fourier transform infrared spectrum (FTIR) [13,14]. Montiano et al. [15] studied the structural parameters of co-pyrolysis tar by semiquantitative analysis from the FTIR spectra. However, to our best of knowledge, there is no report on structural evolution of coal-char generating from co-pyrolysis of biomass and coal by FTIR analysis. This work aims to study thermal behavior and organic functional structure during the co-pyrolysis of poplar-fat coal (biomasscoal) blends with Thermogravimetric analyzer (TGA), Differential scanning calorimetry (DSC), Mass spectrometry (MS) and Attenuated total reflection Fourier transform infrared spectroscopy (ATRFTIR) analysis, and discuss the synergistic effect in the co-pyrolysis process. The thermal behaviors of mixtures were studied, including weight loss rate, characteristic temperature, heat flow, released products, deviations of calculated and experimental values of TG and DSC curves, and kinetics including apparent activation energy (E) and frequency factor (A) during co-pyrolysis process. The ATRFTIR spectra of coal-chars in the co-pyrolysis were also investigated to identify changes in the functional groups. The structural parameters including A-factor, C-factor, CH2/CH3 and Aar/Aal were deduced from ATR-FTIR spectra. 2. Materials and methods 2.1. Materials Fat coal (FC) supplied from Anshan Iron and Steel in northeast China and poplar (P) taken from Gansu province in China were materials considered in this study. Proximate, ultimate and ash analysis of the individual materials are shown in Table 1, which were measured by Chinese Standard Methods GB/T 212-2008, GB/T 31391-2015 and GB/T 1574-2007. The samples were dried in an oven at a temperature of 110 C for two hours. Both the FC and P were ground and sieved to obtain a particle size of 74e150 mm for use in the experiments. The experiments carried out on five blends of P and FC. The levels of P, on a mass basis, in the blend were 4%, 8%, 12%, 16% and 32%, and these are given the notations of FCP4, FCP8, FCP12, FCP16 and FCP32, respectively. 2.2. TGA-DSC-MS analysis TGA-DSC experiments were carried out in a Netzsch STA 449C analyzer. About 10.0 ± 0.5 mg of the sample was used in an experiment to reduce the influence of heat and mass transfer limitations. The samples were heated from ambient temperature to 1000 C at three heating rates of 10, 20, 30 C/min under high purity nitrogen
309
Table 1 Proximate, ultimate and ash analysis of samples. Sample Proximate analysis (wt. %) Moisture, air dry Ash, dry Volatile, dry Fixed carbon, dry Ultimate analysis (dry, wt. %) Carbon Hydrogen Oxygen Nitrogen Sulphur Other H/C, ratio of atom O/C, ratio of atom Ash analysis (dry, wt. %) SiO2 Al2O3 TiO2 Fe2O3 MgO CaO Na2O K2O
FC
P
1.74 9.61 28.67 61.72
4.18 5.76 78.86 15.38
77.27 4.61 5.68 1.36 1.47 9.61 0.72 0.06
45.95 6.30 41.92 0.18 0.13 5.52 1.65 0.68
45.93 22.72 3.65 7.82 1.04 9.49 1.34 1.28
27.46 7.24 1.33 4.90 3.20 33.84 2.77 13.50
at flow rates of 50 ml/min. Then the weight and heat flow changes of each sample can be determined and recorded simultaneously. Relative pyrolysis characteristic parameters including Tin, Ti, Ri and Mf were obtained by thermogravimetric curves and the derivative of thermogravimetric curves (DTG), where Tin is the initial decomposition temperature. According to the American Society for Testing and Materials (ASTM), the value of Tin is defined by the intersection point of two lines. One is the connecting line of 5% and 50% weight loss of total weight loss in the first stage; the other is the extension baseline. Ti is the temperature of DTG peak and Ri is the decomposition rate corresponding to Ti. Mf represents the residual mass of samples at the final temperature. It is to be noted that all the parameters above were obtained when temperature is over 150 C. A mass spectrometry (MS, PFEIFFER VACUUM OMNI star, QMA 200M), was coupled to above TG analyzer through a heated line with stainless steel tube capillary to measure the released products. The mass-to-charge ratio (m/z) recorded were 2, 16, 28 and 44, which stand for H2, CH4, CO and CO2, as most probable parent molecules [4,16]. The products signals were normalized to that from 1 mg of samples because of the sample weight difference in each experiment. To reduce the experimental error and achieve the precision required, the TGA-DSC-MS experiments for the each sample have been done in triplicate. The three samples were carried out in the same experimental conditions. The results showed that the error value of the pyrolysis parameters obtained was under 2%. To infer interactions between coal and biomass during copyrolysis process, the measured values for the blends were compared with calculated ones from two individual fuels. The calculated values were obtained using the simple additive model principle, where the properties of the binary mix depended solely on the individual fuel properties and their mass proportions. When experimental results show deviations from calculated values, it is called that these are caused interactions between two components during co-pyrolysis. The calculated values were determined using Eqs. (1) and (2). In order to further investigate the degree of interactions, DM, DHF were defined with the difference between calculated and experimental values and could be shown by Eqs. (3) and (4).
310
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
Mcalculated ¼ aMfat coal þ bMpoplar
(1)
HFcalculated ¼ aHFfat coal þ bHFpoplar
(2)
DM ¼ Mcalculated Mexperimental
(3)
DHF ¼ HFcalculated HFexperimental
(4)
where Mcalculated, Mexperimental and HFcalculated, HFexperimental are the calculated and experimental mass weight/heat flow values of blends during co-pyrolysis separately; a and b are the mass ratios of FC and P in the blends separately; Mfat coal, Mpoplar and HFfat coal, HFpoplar are the experimental mass weight/heat flow values of FC and P, respectively. 2.3. Kinetics analysis A non-isothermal method was selected to investigate the kinetics of the co-pyrolysis process. As the co-pyrolysis of FC and P involves complex reactions, simple kinetic models are not applicable. The distributed activation energy model (DAEM) is widely used for the study of complex pyrolysis reactions and has been shown to describe the pyrolysis process in over wide temperature and heating rate range well [17e19]. Compared with the traditional DAEM, Miura and Maki [20] obtained a simpler and more accurate method of finding the activation energy (E) and frequency factor (A) using a step function. The Miura integral method can be applied in DAEM without the need to assume, in advance, the form of the activation energy distribution function and the fixed frequency factor values. The E and A of pyrolysis process are obtained directly from the TG curves, which means that the Miura integral method can be applied to study the kinetics in this work. The corresponding theoretical basis and derivation processes could be found from the literatures [17e21] and the final equation could be expressed as Eq. (5).
b AR E þ 0:6075 ln 2 ¼ ln E RT T
(5)
where b is the heating rate (K/s), T is the temperature (K), A is the frequency factor (1/s), R is the universal gas constant (8.314 J/ mol$K) and E is the activation energy (J/mol). 2.4. ATR-FTIR analysis The residual chars collected from the co-pyrolysis characteristic temperature were ground to less than 74 mm and then were subjected to ATR-FTIR. The generated spectra of the samples were recorded on a Nicolet iS5 FTIR in the absorbance mode, equipped with the attenuated total reflection (ATR) diamond coupling. The samples were analyzed at room temperature, from a collection of 32 scans per spectrum measured at a resolution of 4 cm1 with wavenumber from 4000 to 400 cm1. The FTIR spectra are appropriate for identifying functional groups in coals, tars and chars [13e15,22]. Previous studies have successfully used both peak values and integral area of FTIR spectra to provide qualitative and semi-quantitative analysis of the functional groups [23,24]. To analyze the differences of coal-char macromolecular structures during co-pyrolysis, semi-quantitative analysis were carried out using the integrated area (IA) to calculate selected structural parameters. A-factor, C-factor, CH2/CH3, and Aar/ Aal were calculated by the peak integrated area according to Dutta et al. [14], Xin et al. [25], Qiu et al. [26] and Li et al. [13]. The relevant
equations are as follows.
. IA3000 2800cm1 A factor ¼ IA3000 2800cm1 þ IA1650cm1 (6) . IA1800 1520cm1 C factor ¼ IA1800 1650cm1 (7) . IA2950cm1 CH2 =CH3 ¼ IA2920cm1 þ IA2860cm1 þ IA2890cm1
(8)
. Aar =Aal ¼ IA1650 1520cm1 IA3000 2800cm1
(9)
where A-factor stands for hydrocarbon-generating potential, Cfactor is suggested to reflect thermal maturity or the contribution degree of carbonyl (C]O), CH2/CH3 describes the aliphatic chain length, and Aar/Aal represents aromaticity. 3. Results and discussion 3.1. Pyrolysis characteristics The experimental TG, DTG and DSC curves, obtained at a heating rate of 10 C/min, for FC, P and their blends are illustrated in Fig. 1. In the same figure, calculated values are also shown. The corresponding pyrolysis characteristic parameters (Tin, Ti, Ri, etc.) of the individual fuels and their blends are listed in Table 2. From Fig. 1(a) and (b), it can be observed that the decomposition of FC starts at about 320 C and from 320 to 600 C weight loss is significant, increasing with increasing temperature. The corresponding maximum weight loss rate (Rmax) is 0.158%$min1 at 474 C and the total weight loss (Mt) is 22.69 wt.% of the initial sample weight. On the other hand, for the P sample, thermal decomposition begins at around 250 C and from that point to 400 C weight loss is very obvious resulting in the release of over 90% of total volatiles. The relevant Rmax is 0.82%$min1 at 345 C and about 75 wt.% of the initial weight occurs in the pyrolysis process. The Mt and Rmax of P are about 3 times and 5 times higher than those corresponding values for FC. Results also show that FC has higher decomposition temperature and wider thermal decomposition region. These findings are consistent with expectations, in that P has higher volatiles and lower fixed carbon values as indicated in Table 1. As Fig. 1(c) shows, three stages corresponding to endothermic and exothermic events exist in FC pyrolysis process. The first stage with pyrolysis temperature below 150 C is attributed to the moisture evaporation. With the pyrolysis temperature ranging from 150 to 570 C, several endothermic peaks can be observed, which mainly resulted from coal devolatilization [27]. An obvious exothermic event can be seen in the last stage (570e1000 C), which is due to the combination of coal polycondensation reaction and mineral matters decomposition. For the P sample, the endothermic event happened in the pyrolysis process, which is due to the large decomposition of P as described in TG-DTG analysis. The distinct differences in thermal behaviors between FC and P are not only related to their chemical components but also their structural properties. Biomass (P) is mainly made up of hemicellulose, cellulose and lignin. Fig. 2 shows the fitted DTG curves for P at 150e600 C. According to previous studies [28], changes in the
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
311
Fig. 2. The three main chemical components of P.
Fig. 1. TG, DTG and DSC curves for FC, P and their blends with b ¼ 10 C/min: (a) TG, (b) DTG, (c) DSC.
temperature range of 230e350 C can be attributed to hemicellulose decomposition, while that in the temperature range of 280e400 C mainly to cellulose decomposition. Lignin decomposition occurs at a much wider temperature of 200e550 C. The macromolecular structure of those components is mainly linked by weak ether bonds (R-O-R) with bond energies of 380e420 kJ/mol that can withstand temperatures of less than 400 C. On the other hand, the coal (FC) is mainly formed of polycyclic aromatic hydrocarbons linked by C]C bonds with high bond energy of 1000 kJ/ mol [9] and, therefore, more resistant to thermal decomposition at lower temperatures. Therefore, most of the material in P is decomposed before 400 C and the peak of Rmax is consistent with that of cellulose decomposition. The TG and DTG curves for the mixed samples indicate that some deviations existed between experimental and calculated values. The TG curves show that calculated values are greater than experimental values in every mixed sample, and the deviations increase with increasing mass ratio of P. For the DTG results, the shape and position of the curves remain unchanged with increasing the mass ratio of P. The Ti (i ¼ 1, 2, 3) values also have no obvious changed, indicating that the introduction of P into FC does not affect the relative pyrolysis temperature at the same heating rate. However, the peak intensity related to Ri (i ¼ 1, 2, 3) shows an evident change with the introduction of P. As the mass ratio of P increases, the value of R1 assigned to P increases from 0.051 to 0.26%$min1, while the R2 value related to FC decreases from 0.149 to 0.107%$min1, and the value of R3 that is attributed to the second reaction shows a slight decrease. The deviations between experimental values and calculated values for Ri increase with increasing
Table 2 Pyrolysis parameters of FC, P and their blends with b ¼ 10 C/min. Parameters
FC
P
FCP4
FCP8
FCP12
FCP16
FCP32
Exp.
Exp.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Exp.
Cal.
Tin ( C) T1 ( C) T2 ( C) T3 ( C) R1 (%$min1 101) R2 (%$min1 101) R3 (%$min1 101) Mf (%)
323 e 474 674 e 1.58 0.20 77.31
248 345 e e 8.20 e e 24.43
235 345 474 678 0.51 1.49 0.19 74.79
228 345 474 674 0.48 1.53 0.19 75.21
242 345 475 673 0.91 1.43 0.19 73.04
236 345 475 678 0.78 1.49 0.19 73.49
245 345 474 678 1.28 1.41 0.19 70.63
237 345 474 680 1.05 1.45 0.18 71.80
246 345 475 679 1.60 1.32 0.18 68.28
238 345 474 674 1.28 1.41 0.18 70.02
247 345 475 674 2.60 1.07 0.17 61.61
242 345 474 674 2.12 1.28 0.17 64.52
312
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
P addition. When the mass ratio of P is increased, calculated R1 increases from 0.048 to 0.212%$min1, and calculated R2 decreases from 0.153 to 0.128%$min1. The calculated R1 is lower than experimental values, while the calculated R2 is higher than experimental values. The corresponding deviations in R1 values increase from 0.003 to 0.048%$min1, and for R2 the deviation increases from 0.004 to 0.021%$min1. The observed deviations indicate that the addition of P affects both the decomposition of FC and P, indicating that interactions have occurred between FC and P in the copyrolysis process. Fig. 3 shows the release of gaseous products during co-pyrolysis of FC and P. Thermal decomposition of FC, P and their blends mainly leads to the release of H2, CH4, CO and CO2. For H2, CH4 and CO, it can be seen that their release rate of blends is larger than that of FC or P, which is consistent with the findings of Haykiri-Acma [29]. However, the rate of CO2 decreases when added P, which may be due to the large release of CH4, CO and ash components influences. These results indicate that the addition of P would promote the decomposition of volatiles and, consequently, increase the devolatilization rate. As the ultimate analysis (Table 1) describes, the atomic ratios of both H/C and O/C in P are two and eleven times higher than the respective values in FC. The higher levels of eH and eOH radicals produced from the pyrolysis of P have played a synergistic role in improving the decomposition of FC. On the other hand, the cellulose and hemicellulose from poplar are linked by bglycosidic bonds, which would break down into hydrogenous radicals and influence FC during co-pyrolysis [30]. At the same time, these hydrogenous radicals inhibit the formation of aromatic rings and prevent the recombination and cross-linking reactions of other free-radicals [29], which would result in increasing the release rate of light molecular compounds, eg. H2, CH4, and CO. Further, large amount of the alkali and alkaline earth metal (AAEMs) (as high as 50.11%) would also catalyze the reactions between volatiles and char to produce more gases [31]. Therefore, interactions would occur during co-pyrolysis process of FC and P, and these could result in the increase of devolatilization rate, which is consistent with the TG-DTG analysis. The DM and DHF term in Eqs. (3) and (4) defined the degree of the interactions are shown in Fig. 4. As Fig. 4(a) shows, with increasing blending ratio of P, the values of DM have an ascending trend. It can be seen that two turning points, located in 240 C and
Fig. 3. Mass spectra of gas release from FC, P and their blends with b ¼ 10 C/min.
Fig. 4. Differences between calculated and experimental values from TG and DSC curves with b ¼ 10 C/min: (a) DM from TG, (b) DHF from DSC.
650 C (640e650 C), exist in each curves. Furthermore, an obvious change of DM is found in this region (240e650 C). As shown in Fig. 4(b), the difference between the experimental and calculated heat flow values rises when added P. It can be seen two weak peaks in the region of 240e650 C. The first one located at 240e390 C indicates that the pyrolysis of blends obtained from the experimental has a larger heat absorption than that from the calculated with pyrolysis temperature ranging from 240 C to 390 C, and the other one in 390e650 C implies that it would absorb smaller heat at further temperature. Taking the DM and DHF into consideration, approximately three regions are identified with increasing temperature. The fluctuation of region (I) is caused by the instable removal of moisture in the mixed samples. The deviation in region (III) is insignificant, probably because the most of the volatiles have been removed and the reactivity of the blend is unaffected. However, the difference between the DHF may be caused by the minerals reactions and their influences on the coal polycondensation in this region. The interactions mainly occur in region (II) at the temperature range of 240e650 C, where the pyrolysis of both P and FC are occurring at significant rates. Within region II, from 240 to 390 C there is a promotion effect but from 390 to 650 C, while there is an inhibition effect e both of which can be explained by the heat and mass transfer effects. With pyrolysis temperature increasing from 240 C to 390 C, larger heat absorption in co-pyrolysis of blends would make the decomposition rate increase, and then result in the DM rising, which indicates that added P would accelerate the decomposition of molecular
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
313
compounds in FC. When temperature is over 390 C, most of the components in P are already decomposed except for the lignin because its pyrolysis temperature is greater than 550 C and occurs at a wider temperature range. When heated, softening, melting and fusing accompanies the formation of lignin char [32]. This could result in impeding the release of volatiles and producing the large pores in FC, and further deteriorates the heat and mass transfer ability within the mixture. Inorganic minerals in P could improve the reactivity of FC but probably has a non-dominant effect. Therefore, the experimental pyrolysis of blends has a smaller heat absorption than that of the calculated for decomposition. Consequently, the decomposition rate of blends decreases, and the DM declines. This can be regarded as an inhibition effect in the FC decomposition process with the addition of P. During co-pyrolysis, interactions occur mainly before the formation of semi-coke and they have either a promoting or inhibiting effect. The first is mainly caused by chemical reaction while second is mainly through physical interaction. This study shows that significant synergistic effects occur only at lower pyrolysis temperatures. 3.2. Kinetics analysis Interactions between FC and P occur at temperatures from 240 to 650 C, and the corresponding reaction conversions from x ¼ 0.2 to x ¼ 0.8. The kinetics parameters including E and A at different conversions can be obtained by DAEM methods. The value of E is the lowest energy and determines whether decomposition reaction occurs, while A shows the number of effective collisions between reaction molecules. Large values of E and A indicate that the reaction proceeds with greater difficulty and is more complex. To investigate the influence of P on the co-pyrolysis, it is necessary to study the kinetics of the co-pyrolysis process using the Miura integral method. Arrhenius plots of FC, P and their blends at various conversions are shown in Fig. 5. From the plot of ln(b/T2) vs 1/T for different conversion values, the E values were determined from the slope of the lines. The next step involved determining the A values using Eq. (5). The results shown in Fig. 5 are expressed quantitatively in Table 3. The high correlation coefficients (R2 > 0.940) obtained indicate that a high level of confidence can be given to the determined E values. On the other side, the apparent activation energy and frequency factor of blends samples vary with the different reaction conversion, indicating that more than one single mechanism exists during the pyrolysis of FC and P blends. A linear relationship between E and ln(A) shows that the kinetic compensation effect occurred in the poplar pyrolysis process, which agrees with the previous work [33]. For the FC and blends, with the increase of activation energy, the frequency factor also keeps a rising trend. As the previous study described [34], the compensation effect would be resulted from the ‘isokinetic’ temperature in homogeneous systems. However, coal is a mixture of organic and mineral matters, which would cause the nonlinear relationships between E and ln(A) during pyrolysis process of FC and blends. In addition, previous studies confirmed that the values of E in solid e state reactions are in 50e350 kJ/mol, implying that E values obtained in this work are also reasonable [35,36]. It can be seen from Table 3, the values of E and A of FC are 163.306 kJ/mol and e25.849 s1, respectively, while those of P are 106.348 kJ/mol and e19.728 s1, indicating that the decomposition of FC is harder and more complex than that of P. In addition, the values of E and A for both FC and P show that decomposition is more difficult as conversion increases. For the mixed samples, increasing P addition decreases the average E value from 149.582 to 90.799 kJ/ mol, and the average A value decreases from e21.867 to e14.932 s1.
Fig. 5. Arrhenius plots of FC, P and their blends at various conversion from x ¼ 0.2 to x ¼ 0.8 for experimental values.
The fact that the E value of the mix is lower than that of P when P addition reaches 16%, indicates that there has been interactions between FC and P during co-pyrolysis. Similar conclusions were reached in the previous study [37] and were mainly attributed to the release of hydrogen and hydroxyl radical and the catalytic effects of alkali and alkaline earth metals (AAEMs) in biomass (P). Therefore, the blending ratio of poplar to coal should be below 16% to control the deterioration in performance obtained from the replacement of coal by biomass within a reasonable range.
314
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
Table 3 Kinetic parameters of FC, P and their blends.
a FC
P
FCP4
FCP8
FCP12
FCP16
FCP32
E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2 E (kJ/mol) lnA (s1) R2
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
Average
141.918 27.036 0.999 77.378 14.917 0.990 152.103 24.140 0.994 112.508 20.179 0.999 105.770 20.382 0.978 108.423 20.184 0.996 101.00 19.372 0.999
160.593 25.509 0.975 83.835 16.048 0.999 144.531 23.775 0.999 102.190 17.738 0.956 115.164 16.785 0.998 93.758 16.752 0.991 104.13 19.591 0.996
169.796 29.349 0.994 93.002 17.753 0.999 158.073 23.808 0.999 101.763 17.223 0.886 115.544 21.291 0.925 80.835 13.788 0.972 97.56 17.863 0.999
156.496 24.085 0.967 103.155 19.587 0.999 151.938 23.936 0.999 99.394 16.189 0.907 69.001 11.357 0.989 80.601 13.238 0.948 92.16 16.443 0.993
180.246 29.318 0.999 105.843 19.889 0.997 161.589 23.413 0.996 126.119 20.701 0.956 96.956 16.262 0.918 80.940 12.444 0.882 91.51 16.088 0.996
171.951 26.081 0.992 111.031 20.775 0.999 161.854 24.867 0.999 122.348 19.106 0.996 127.654 21.248 0.956 68.589 9.832 0.993 84.42 12.332 0.955
182.061 28.629 0.999 116.820 21.703 0.995 159.942 23.695 0.989 133.547 20.629 0.975 125.312 20.152 0.916 86.074 12.574 0.994 98.65 19.950 0.999
165.924 24.529 0.999 120.778 22.360 0.998 152.221 22.655 0.999 105.206 15.289 0.937 114.422 17.309 0.956 101.005 14.842 0.989 73.57 10.187 0.975
165.515 27.162 0.998 120.570 22.097 0.971 154.062 22.002 0.980 145.317 21.616 0.988 118.081 17.243 0.910 110.104 16.102 0.999 103.04 16.431 0.999
166.750 23.966 0.991 115.533 20.942 0.967 144.605 20.786 0.996 109.572 15.191 0.985 103.167 14.296 0.854 118.361 19.143 0.970 80.43 11.506 0.975
168.123 27.056 0.983 122.233 22.110 0.968 133.224 16.798 0.959 137.282 19.237 0.997 114.501 15.759 0.904 109.177 15.261 0.999 90.91 12.931 0.970
115.281 14.864 0.898 113.354 21.219 0.976 149.564 20.371 0.999 93.671 11.586 0.978 139.072 19.311 0.922 93.113 17.284 0.997 79.26 10.500 0.938
178.317 28.453 0.978 98.993 17.063 0.918 120.863 14.025 0.859 145.739 18.743 0.996 139.684 19.055 0.999 110.100 14.372 0.953 83.75 10.926 0.826
163.306 25.849 0.982 106.348 19.728 0.983 149.582 21.867 0.982 118.051 17.956 0.966 114.179 17.650 0.940 95.468 15.063 0.976 90.799 14.932 0.971
3.3. ATR-FTIR spectra of coal-char The evolution of functional groups is the most obvious feature in the devolatilization process. The effects of biomass on the evolution of mixed-sample functional groups cannot be neglected. Information of the functional groups in coal-char or char can be obtained by infrared spectrum detection. In addition, the proposed synergistic effect can be confirmed by analyzing the evolution of functional groups. To obtain the best information, samples of FC, P and FCP16 was heated to 345, 390, 475 and 650 C, these four temperatures correspond to: the temperature of Rmax of P, the temperature at which most of P has decomposed, the temperature of Rmax of FC and, the temperature at which most of FC has decomposed. The ATR-FTIR spectra at these temperatures and also at room temperature were obtained and shown in Fig. 6(a)-(f). The spectra are
divided into ten regions and the corresponding assignments are shown in Table 4. All the samples under heating are featured by a similar distribution of functional groups. However, the peak intensity is affected by raw material type and temperature. For the case of FC and P, the spectra of FC are characterized by strong free eOH at 37003600 cm1, aromatic CeH stretching at 3030 cm1, aromatic C]C stretching vibrations at 1600 cm1 and CeH aromatic out-of-plane deformation at 950-750 cm1 (880, 805, and 745 cm1 peaks are correspond to the vibration of substituted aromatic rings with one, two or three, and four adjacent CeH groups). While P is characterized by strong eOH stretching at 3385 cm1, aldehyde C]O stretching at 1730 cm1, aliphatic ether CeOeC and alcohol CeO stretching at 1150-950 cm1. The different functional groups define the pyrolysis characteristics of FC and P. With increase in temperature, the intensity of some bands decreases or disappears. The broad region at 3600-3100 cm1 is assigned to eOH stretching vibrations, which is confirmed to be attributed to intermolecular H bonds and associated OH groups at the terminal of the aromatic clusters, and these functional groups decompose readily [38]. The bond energy reflects the difficulty in breaking the functional group. Generally, functional groups with lower bond energy decompose into small molecule groups to form gas and macromolecular structure by addition reaction. These functional groups include aliphatic CeH, carbonyl C]O, aromatic/ aliphatic CeOeC and alcohol CeO stretching vibrations, which is
Table 4 Band assignments for ATR-FTIR spectra of samples [13e15,22].
Fig. 6. ATR-FTIR spectra of FC, P and their blends at different temperature: (a) and (b) room temperature, (c) 345 C, (d) 390 C, (e) 475 C, (f) 650 C.
Band (cm1)
Assignments
1 2 3 4 5 6 7 8
3700e3600 3600e3100 3100e3000 3000e2800 1800e1650 1650e1520 1520e1350 1350e1150
9 10
1150e950 950e750 750-720
free OH OH stretching aromatic CeH stretching aliphatic CeH stretching carbonyl C]O stretching aromatic C]C ring stretching aliphatic CH2 and CH3 deformation aromatic ether CeOeC, phenolic CeO, and ester CeOeOeC stretching aliphatic ether CeOeC and alcohol CeO stretching CeH aromatic out-of-plane deformation polymethylenic chains (n 4) rocking
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
consistent with the MS result. Aromatic C]C rings with higher bond energy are difficulty to decomposed at low temperature. When temperature is over 650 C, most of functional groups disappear except for aromatic C]C and a few CeO stretching vibrations. It is noteworthy that at 650 C the char from P still has strong aliphatic CeH and CeH aromatic out-of-plane deformation vibration compared to the coal-char from FC. A possible reason could be that P is an inert material. Therefore, there is no solidification reaction in the pyrolysis process and thus no obvious polycondensation reaction between macromolecule aromatic rings. The obvious synergistic effect can be observed by contrasting the ATR-FTIR spectra of FC coal-char and P char with that of FCP16 coal-char at the same temperature. Form Fig. 6(c)-(e), it can be seen that the peak intensity of C]C ring of FCP16 coal-char is slightly lower than that of FC coal-char and P char, indicating that the C]C ring can be consumed during co-pyrolysis. The peak at 1695 cm1 which related to the carbonyl C]O stretching vibrations is observed in the FC coal-char and P char but not in FCP16 coal-char. The peaks at 1260 cm1 and 1200 cm1 which attributed to aromatic ether CeOeC and ester CeOeOeC stretching vibrations are detected in the P char but not in FC coal-char and FCP16 coal-char. This indicates that interactions have occurred between two fuels during co-pyrolysis, which is consistent with the TGA results. It can be inferred that some active substances presented in the volatiles of P have been adsorbed onto the surface of coal particles and reacted with the coal matrix. Unstable functional groups in the coal matrix react with these active substances causing in a loss in mass of the coal particles. At the same time, the early decomposed volatiles from FC can also react with the P matrix to accelerate the decomposition of functional groups present in P. At the higher temperatures, the synergistic interactions reduce and even disappear. Structural parameters from the infrared spectra can usually be used to provide information on coal-char characteristics. Due to the peaks overlapping, the actual spectra cannot be easily separated to represent individual functional groups. The spectral intensity of each functional group is obtained using a curve-fitting method. In the region of 3000-2750 cm1 and 1800-1480 cm1, Fig. 7 shows FC coal-char at 345 C determined using this method. In this study, structural parameters of A-factor, C-factor, CH2/CH3 and Aar/Aal are calculated using Eqs. (6)e(9) and the values listed in Table 5. From the spectra of the raw materials, the decomposition of P is easier than that of FC because P has greater hydrocarbongenerating potential (A-factor), and lower thermal maturity (Cfactor) and aromaticity (Aar/Aal). That P has lower values of CH2/CH3 is associated with the chemical compounds present. Both cellulose and hemicellulose are formed by the polymerization of monosaccharides and lignin contains a few aliphatic CeH stretching vibrations. For all the samples, at increasing temperature, the structural parameters show a decreasing tendency except for Aar/Aal. In spite of these changes, it is still possible to conclude that all the changes in structural parameters for FCP16 coal-char cannot be attributed to the contribution of FC coal-char and P char. There are clear deviations between calculated and experimental values. The addition of P decreases the aliphatic chain length and aromaticity, and increases the thermal maturity and hydrogen-generation potential of mixed samples, which resulted in higher decomposition reactivity of the mixed samples. This suggests that there are synergistic interactions happening during co-pyrolysis. At 345 C, the decomposition of P is the most significant reaction during co-pyrolysis. Part of hydrogen-rich volatiles adsorb onto the matrix of FC and promote the early decomposition of aliphatic chains. When the macromolecule structure of the FC matrix breaks down, part of aromatic rings can be stripped from coal matrix. These aromatic rings have a high activity and can cause
315
Fig. 7. Curve-fitting of region of 1800-1480 cm1 and 3000-2750 cm1 of FC coal-char at 345 C: (a) 1800-1480 cm1, (b) 3000-2750 cm1.
Table 5 Structure parameters deduced from ATR-FTIR spectra of coal-chars.
25 C 345 C
390 C
475 C
650 C
Samples
A-factor
C-factor
CH2/CH3
Aar/Aal
FC P FC P FCP16 FC P FCP16 FC P FCP16
0.306 0.583 0.250 0.295 0.268 [a 0.169 0.113 0.229 [ 0.114 0.067 0.129 [ e
0.225 0.604 0.363 0.535 0.247 Yb 0.190 0.441 0.232 [ 0.095 0.208 0.076 Y e
1.658 1.146 3.409 1.303 1.753 Y 1.476 1.227 1.231 Y 1.412 0.790 1.189 Y e
2.266 0.716 4.914 2.394 2.729 Y 3.003 7.856 3.360 Y 7.744 13.851 6.724 Y e
a
Higher than calculated values which obtained from simple additive model principle. b Lower than calculated values which obtained from simple additive model principle.
hydrogenation reactions between aromatic rings and free hydrogen to form cycloalkanes. The oxygen in carbonyl C]O has a strong electron-absorbing ability, which facilitates nucleophilic addition reactions involving the carbon atom and negatively charged H or OH radicals. The addition of P accelerates the consumption of carbonyl C]O due to its higher eH and eOH contents in the volatiles. This results in lower CH2/CH3, Aar/Aal and C-factor values and higher A-factor values as seen for FCP16 coal-char. With rising temperatures, there are still interactions but the intensity reduces gradually because of lower volatiles levels. When temperature is
316
S. Qiu et al. / Renewable Energy 136 (2019) 308e316
over 390 C, the influence of P on FC is more related to their differences in physical properties, and these influence the heat and mass transfer processes that take place. Consequently, the changes in the structural parameters for FC are more in line with expectations. The observed smaller deviations in structural parameters can be attributed earlier interactions. It turns out that the interactions are beneficial to increase the hydrogen-generating potential, the chain length of the aliphatics and thermal maturity, and decrease the aromaticity of mixed coal-chars at low temperature. Combined with TGA-DSC-MS analysis, the pyrolysis temperature should be kept in 345e390 C to increase the devolatilization rate and hydrogen-generating potential to produce the biomass-coal tar as much as possible.
[9]
[10]
[11] [12] [13] [14]
4. Conclusions
[15]
The two fuels were studied separately and then in blends during co-pyrolysis. As expected, poplar was easier to decompose than the fat coal and, consequently, resulting in higher maximum weight loss rate and the total weight loss. Interactions mainly occurred in the main pyrolysis region of fat coal and poplar, and results indicated that at increasing temperatures there were promotion and inhibition effects, which could be attributed to chemical reaction and physical action respectively. The real synergistic effect occurred at lower temperature. The mixed sample had lower values of apparent activity energy and frequency factor in the interaction region. In the region where interactions occurred, the aromatic C] C of mixed coal-char had a tendency to decrease, and peaks of carbonyl C]O, ether CeOeC and ester CeOeOeC vibrations in mixture coal-char were much lower compared to those in the individual fuels at same temperature. Interactions caused higher hydrocarbon-generating potential, length of aliphatic chains and thermal maturity, and reduced the aromaticity of the mixed coalchars. For the better use of poplar-fat coal blends, the blending ratio of poplar to coal should be below 16%. Furthermore, the pyrolysis temperature should be kept in 345e390 C to produce biomass-coal tar as much as possible.
[16]
Acknowledgements This work was supported by the National Natural Science Foundation of China (Project No. 51474042 and 51774061) and the Fundamental Research Funds for Central Universities (Project No. 106112017CDJQJ138801). The authors also acknowledge the support provided by the Fund of Chongqing Science and Technology (Project No. cstc2018jscx-msyb0988). References [1] X. Zhang, W. Yang, W. Blasiak, Modeling study of woody biomass: interactions of cellulose, hemicellulose, and lignin, Energy Fuel 25 (10) (2011) 4786e4795. [2] F. Abnisa, W.M.A.W. Daud, A review on co-pyrolysis of biomass: an optional technique to obtain a high-grade pyrolysis oil, Energy Convers. Manag. 87 (2014) 71e85. [3] H.Y. Meng, S.Z. Wang, L. Chen, Z.Q. Wu, J. Zhao, Thermal behavior and the evolution of char structure during co-pyrolysis of platanus wood blends with different rank coals from northern China, Fuel 158 (2015) 602e611. [4] K. Jayaraman, M.V. Kok, I. Gokalp, Thermogravimetric and mass spectrometric (TG-MS) analysis and kinetics of coal-biomass blends, Renew. Energy 101 (2017) 293e300. [5] P. Yangali, A.M. Celaya, J.L. Goldfarb, Co-pyrolysis reaction rates and activation energies of West Virginia coal and cherry pit blends, J. Anal. Appl. Pyrol. 108 (2014) 203e211. [6] Z.Q. Wu, S.Z. Wang, J. Zhao, L. Chen, H.Y. Meng, Synergistic effect on thermal behavior during co-pyrolysis of lignocellulosic biomass model components blend with bituminous coal, Bioresour. Technol. 169 (5) (2014) 220e228. [7] S. Krerkkaiwan, C. Fushimi, A. Tsutsumi, P. Kuchonthara, Synergetic effect during co-pyrolysis/gasification of biomass and sub-bituminous coal, Fuel Process. Technol. 115 (2013) 11e18. [8] S. Yuan, Z.J. Zhou, J. Li, X.L. Chen, F.C. Wang, HCN and NH3 (NOx precursors)
[17]
[18]
[19] [20] [21] [22]
[23]
[24]
[25]
[26]
[27]
[28]
[29] [30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
released under rapid pyrolysis of biomass/coal blends, J. Anal. Appl. Pyrol. 92 (2011) 463e469. A.K. Sadhukhan, P. Gupta, T. Goyal, R.K. Saha, Modelling of pyrolysis of coalbiomass blends using thermogravimetric analysis, Bioresour. Technol. 99 (17) (2008) 8022e8026. M.S. Masnadi, R. Habibi, J. Kopyscinski, J.M. Hill, X.T. Bi, C.J. Lim, N. Ellis, J.R. Grace, Fuel characterization and co-pyrolysis kinetics of biomass and fossil fuels, Fuel 117 (8) (2014) 1204e1214. H.B. Vuthaluru, Thermal behaviour of coal/biomass blends during co-pyrolysis, Fuel Process. Technol. 85 (2e3) (2004) 141e155. B. Moghtaderi, C. Meesri, T.F. Wall, Pyrolytic characteristics of blended coal and woody biomass, Fuel 83 (6) (2004) 745e750. W. Li, Y.M. Zhu, Structural characteristics of coal vitrinite during pyrolysis, Energy Fuel. 28 (6) (2014) 3645e3654. S. Dutta, C. Hartkopf-Froder, K. Witte, R. Brocke, U. Mann, Molecular characterization of fossil palynomorphs by transmission micro-FTIR spectroscopy: implications for hydrocarbon source evaluation, Int. J. Coal Geol. 115 (2013) 13e23. M.G. Montiano, A.M. Fernandez, E. Diaz-Faes, C. Barriocanal, Tar from biomass/coal-containing briquettes, evaluation of PAHs, Fuel 154 (2015) 261e267. mez, Co-firing of coal and manure biomass: a M. Otero, M.E. S anchez, X. Go TGeMS approach, Bioresour. Technol. 102 (17) (2011) 8304e8309. Y. Xu, Y.F. Zhang, Y. Wang, G.J. Zhang, L. Chen, Thermogravimetric study of the kinetics and characteristics of the pyrolysis of lignite, React. Kinet. Mech. Catal. 110 (1) (2013) 225e235. A. Soria-Verdugo, N. Garcia-Hernando, L.M. Garcia-Gutierrez, U. Ruiz-Rivas, Analysis of biomass and sewage sludge devolatilization using the distributed activation energy model, Energy Convers. Manag. 65 (2013) 239e244. M.G. Montiano, E. Diaz-Faes, C. Barriocanal, Kinetics of co-pyrolysis of sawdust, coal and tar, Bioresour. Technol. 205 (2016) 222e229. K. Miura, T. Maki, A simple method for estimating f(E) and k0(E) in the distributed activation energy model, Energy Fuel. 12 (5) (1998) 864e869. J. Cai, W. Wu, R. Liu, G.W. Huber, A distributed activation energy model for the pyrolysis of lignocellulosic biomass, Green Chem. 15 (5) (2013) 1331e1340. Z.Q. Wu, S.Z. Wang, J. Zhao, H.Y. Meng, Thermal behavior and char structure evolution of bituminous coal blends with edible fungi residue during co-pyrolysis, Energy Fuel. 28 (3) (2014) 1792e1801. X.G. Sun, The investigation of chemical structure of coal macerals via transmitted-light FT-IR microspectroscopy, Spectrochim. Acta A 62 (1e3) (2005) 557e564. J.A. Orrego, R.C. Hernandez, E. Mejia-Ospino, Structural study of colombian coal by fourier transform infrared spectroscopy coupled to attenuated total reflectance (FTIR-ATR), Rev. Mex. Fis. 56 (3) (2010) 251e254. H.H. Xin, D.M. Wang, X.Y. Qi, G.S. Qi, G.L. Dou, Structural characteristics of coal functional groups using quantum chemistry for quantification of infrared spectra, Fuel Process. Technol. 118 (2) (2014) 287e295. S. Qiu, S. Zhang, Y. Wu, G. Qiu, C. Sun, Q. Zhang, J. Dang, L. Wen, M. Hu, J. Xu, R. Zhu, C. Bai, Structural transformation of fluid phase extracted from coal matrix during thermoplastic stage of coal pyrolysis, Fuel 232 (2018) 374e383. Z. Niu, G. Liu, H. Yin, C. Zhou, Devolatilization behaviour and pyrolysis kinetics of coking coal based on the evolution of functional groups, J. Anal. Appl. Pyrol. 134 (2018) 351e361. E. Kastanaki, D. Vamvuka, P. Grammelis, E. Kakaras, Thermogravimetric studies of the behavior of lignite-biomass blends during devolatilization, Fuel Process. Technol. 77 (2002) 159e166. H. Haykiri-Acma, S. Yaman, Interaction between biomass and different rank coals during co-pyrolysis, Renew. Energy 35 (1) (2010) 288e292. S. Matsuoka, H. Kawamoto, S. Saka, What is active cellulose in pyrolysis? An approach based on reactivity of cellulose reducing end, J. Anal. Appl. Pyrol. 106 (2014) 138e146. D.M. Keown, J.I. Hayashi, C.Z. Li, Effects of volatileechar interactions on the volatilisation of alkali and alkaline earth metallic species during the pyrolysis of biomass, Fuel 87 (7) (2008) 1187e1194. D.L. Guo, H.Y. Yuan, X.L. Yin, C.Z. Wu, S.B. Wu, Z.Q. Zhou, Effects of chemical form of sodium on the product characteristics of alkali lignin pyrolysis, Bioresour. Technol. 152 (2014) 147e153. J. Cai, W. Wu, R. Liu, An overview of distributed activation energy model and its application in the pyrolysis of lignocellulosic biomass, Renew. Sustain. Energy Rev. 36 (2014) 236e246. D. Xu, M. Chai, Z. Dong, M.M. Rahmana, X. Yu, J. Cai, Kinetic compensation effect in logistic distributed activation energy model for lignocellulosic biomass pyrolysis, Bioresour. Technol. 265 (2018) 139e145. J. Wang, W. Lian, P. Li, Z. Zhang, J. Yang, X. Hao, W. Huang, G. Guan, Simulation of pyrolysis in low rank coal particle by using DAEM kinetics model: reaction behavior and heat transfer, Fuel 207 (2017) 126e135. J. Cai, R. Liu, New distributed activation energy model: numerical solution and application to pyrolysis kinetics of some types of biomass, Bioresour. Technol. 99 (8) (2008) 2795e2799. X.F. Zhu, K. Li, L.Q. Zhang, X. Wu, X.F. Zhu, Synergistic effects on thermochemical behaviors of co-pyrolysis between bio-oil distillation residue and bituminous coal, Energy Convers. Manag. 151 (2017) 209e215. Y. Guo, R.M. Bustin, Micro-FTIR spectroscopy of liptinite macerals in coal, Int. J. Coal Geol. 36 (3) (1998) 259e275.