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Comparative studies on the effect of mineral matter on physico-chemical properties, inherent moisture and drying kinetics of Chinese lignite
Energy Conversion and Management 93 (2015) 197–204
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Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman
Comparative studies on the effect of mineral matter on physico-chemical properties, inherent moisture and drying kinetics of Chinese lignite Pengfei Zhao a,b, Liping Zhong b, Yuemin Zhao b,⇑, Zhenfu Luo b a b
School of Electric Power Engineering, China University of Mining and Technology, Xuzhou 221116, China School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, China
a r t i c l e
i n f o
Article history: Received 4 October 2014 Accepted 8 January 2015 Available online 28 January 2015 Keywords: Lignite Characterization Inherent moisture Drying kinetics
a b s t r a c t The comparative study between the high-ash lignite (HAS) and low-ash lignite (LAS) demonstrated great effects of mineral matter on physico-chemical properties, inherent moisture and drying kinetics of Chinese lignite. The physico-chemical properties were characterized by X-ray diffraction (XRD), N2 physisorption, fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), and thermoanalytical methods. Raw and treated samples (screening, dry beneficiation, and flotation) were analyzed for inherent moisture content. Drying kinetic experiments were performed by isothermal thermogravimetry in combination with thin-layer models. In comparison with LAS, HAS had less cohesive features with higher amounts of heterogeneous crystalline minerals, less quantity of O-containing functional groups, and smaller surface areas as well as lower pore volumes, as evidenced by characterization analysis. Less cohesive features could allow the moisture to move easily through the lignite, which thus resulted in a lower inherent moisture contained in HAS. On the other hand, due to higher thermal conductivity and poorer holding-moisture structures resulted from the presence of abundant minerals, HAS revealed more promising drying kinetics with lower activation energies, which were determined by the combination of isothermal experiments and Page model analyses. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Low-rank coals, i.e. lignites, are considered as the main energy source, which constitutes significant supplies for both energy and chemical feedstock, mainly because they represent the most abundant and cheapest fossil fuel available [1]. It is estimated that nearly half of the world’s coal reserves consist of lignite. In China, lignite is extensively exploited and largely burnt for power generation [2,3]. Direct combustion of these low-grade coals can lead to low thermal efficiency, high pollutant emissions (particulate materials, SOx, trace elements and CO2) [4] and high operation and maintenance cost, partly due to high amount of moisture and ash-forming mineral matter [4,5]. Thus, it is great importance to removal of moisture and ashes from low-grade coals before combustion. Numerous coal cleaning technologies associated to de-watering [6–10] and de-ashing [11–14] processes have been proposed to sustainably utilize these lignites. However, most of them were not yet widely practiced by the power industry considering the high consumption of energy required during cleaning processes. ⇑ Corresponding author. Fax: +86 516 835900902. E-mail address: [email protected] (Y. Zhao). http://dx.doi.org/10.1016/j.enconman.2015.01.020 0196-8904/Ó 2015 Elsevier Ltd. All rights reserved.
Understanding of fundamental physical and chemical characteristics of lignite structure, particularly in relation to lignite-water interactions is essential to develop new technologies that are efficient, safe and cost-effective [15]. Due to the complicated lignite– water interactions, various aspects involving the forms of water present in low rank coals [16,17], physical–chemical structure of coal [18], migration of water during drying [19], coal structure changes during moisture loss [20], moisture re-adsorption [21], and effects of water removal on subsequent applications [22,23], were widely examined. Several characteristic techniques such as NMR [24], DSC [25] and FTIR [26] in determination and quantification of types of water and coal structures were also conducted. Moreover, a great variety of raw lignites, dried or dewatered lignites, and chemically treated lignites were extensively analyzed in most previous studies [27,28]. However, little information was available and probably could not be applied to the case of highash lignite considering characteristic differences among those moist materials. Study of the specific kinetics of drying process has also important academic and practical significances for the designing of a lignite drying system. Simultaneous heat and mass transfer behaviors, chemical and physical structure of coals, and the variation of heat supply method, all play a role in determining
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the kinetics of lignite dewatering process, which makes mathematical modeling of this complex drying process quite difficult [29]. There are several ways to describe the drying process. The methods used may be divided into three main groups: theoretical [30], semi-theoretical [31], and empirical models [32]. Rely on simultaneous heat and mass transfer, the theoretical models such as shrinking core model, the diffusion model, and multi-scale model were deemed an important method in literature [33]. With some theoretical background, semi-theoretical equations were similar to Newton’s law of cooling [31]. Based upon experimental results, empirical equations are widely used to describe the drying process, mainly due to the fact that these models need no assumptions in geometric, mass diffusivity and conductivity aspects [34]. Pickles et al. [35] using thin-layer empirical equations to examine the microwave drying kinetics of a low-rank sub-bituminous coal. Tahmasebi et al. [29] also gained the drying kinetics of a Chinese low rank coal in the superheated steam fluidized-bed and microwave. Zhao et al. [6] further obtained the drying kinetics of a Chinese low rank coal in a vibration-fluidized bed. Many researchers have revealed that thin-layer empirical equations are often used for description of drying kinetics of low-ash lignite, but little research is available to date on the potential impact of high-ash lignite. As mentioned above, examination on the lignite-water interactions and drying kinetics was limited to the low-ash lignite in most previous studies. However, the conclusions of these studies may be not suitable for the high-ash lignite. The presence of high amount of mineral matter not only could change the physical–chemical structures and inherent moisture content but also may affect the drying kinetics of lignite. Therefore, the physical–chemical structure, inherent moisture content and drying kinetics of high-ash lignite was re-determined in this work. A typical Chinese high-ash lignite was treated by several methods (screening, dry beneficiation, and flotation). The pore structures and functional groups of the de-ashing coal and parent coal were characterized. Then, the characteristics of inherent moisture and the drying kinetics were measured. All the results were comparatively used to demonstrate that the presence of high amount of mineral matter had a great influence on the physical– chemical structure, inherent moisture content and drying kinetics of Chinese lignite. This information can provide the theoretical guidelines for its industrial applications. 2. Experiment 2.1. Lignite properties A typical Chinese lignite sample (Shengli coal in east of Internal Mongolia) is used in this study. Proximate analysis was performed according to the ASTM standards (ASTM E871, D1102-84, D3172-89). Meanwhile, ultimate analysis was using Leco type analyzers CHN-600 and S532-500 (ASTM D3176-93, D3177-33). The proximate analysis and ultimate analysis are listed in Table 1. The coal ash sample was prepared according to Chinese standard procedures (GB/T1574-2001). Thereafter, its chemical composition was tested by X-ray Fluorite Spectroscopy S8 Tiger. This coal was crushed and sieved to five size fractions (0.25, 0.25–0.5, 0.5–1, 1–3 and 3–6 mm). For the size of 1–3 mm, the
dry beneficiation method using a special vibration fluidized bed can be found in our previous studies [14,36]. After fluidization for a certain time, this bed was divided into five layers in the axial direction and the ash content of each layer was measured. For the size of 0.5 mm, the common flotation method using the organic gravity solution was described everywhere [37]. The low drying temperature (<50 °C) was selected to eliminate the unfavorable effect on the pore structure of lignite. These particles were separated into several segments (<1.3, 1.3–1.4, 1.4–1.5, 1.5–1.6, 1.6–1.7, >1.8 g/cm3) based on their densities and the ash content of each segment was analyzed. The lowest and highest density segments were received as low-ash sample (LAS) and high-ash sample (HAS), respectively. The other segments were labeled as middleash sample (MAS). To determine the total moisture and inherent moisture content, 2 g sample as received basis or air-dry basis was dried in an oven at 105 °C for 2 h using a digital balance (Sartorius BT 224 S, with a precision of 0.1 mg). 2.2. Characterization XRD measurements were carried out on a Rigaku RINT2000 wide-angle goniometer with a Cu cathode using recorded in the range between 10° and 90°. Fourier transform infrared–attenuated total reflectance (FTIR) spectrums were collected by a Vertex 80v Spectrometer. The morphologies of samples were observed form FEI QuantaTM 250 instrument. Nitrogen adsorption/desorption isotherms measurements were carried out with a TriStar 3020 system to determine surface area and pore size distribution. The thermo-gravimetric (TG/DTG) and differential thermal (DTA) analysis were obtained simultaneously using a thermal analyzer (Toledo 851) at a heating rate of 10 °C/min, atmospheric air and temperature range 25–600 °C. A Micromeritics AccuPyc 1331 gas pycnometer was used to infer the true density of samples. Three analyses were performed and the results represent the mean values of the measurements. A laser particle analyzer (Microtrac S3500) was used to measure particle size distribution. A Quick Thermal Conductivity Meter (QM-500) was used to obtain the thermal conductivity. 2.3. Drying kinetics The drying characteristics were determined using the Gravimetric Analyzer (AG MA150). Application of infrared heating technology in the drying processing was easy to eliminate the transport effect on the kinetic. During experiments, 3 g sample was carried out at 80 °C, 105 °C, 150 °C and 180 °C drying temperatures and 1–3 mm sample heights. The weight of sample was automatically recorded using a digital balance (with a precision of 1 mg) every 6 s. The moisture content values were calculated on a wet basis by means of the following equations, respectively.
MR ¼
W wet W dry g water g wet coal W wet
ð1Þ
where MR is moisture content, Wwet is initial sample mass, Wdry is the mass of the dry coal. The most common empirical thin layer drying equations (Table 3) were used to describe moisture transfer in the lignite.
Table 1 The proximate and ultimate analysis of Chinese lignite (in wt%). Moisture (ad)
Volatile matter (ad)
Ash (ad)
Fixed carbon (ad)
C (ad)
H (ad)
N (ad)
S (ad)
O (ad)
25.85
22.36
22.93
28.86
57.30
3.08
0.93
0.53
38.16
ad, air dried.
P. Zhao et al. / Energy Conversion and Management 93 (2015) 197–204 Table 2 Chemical composition analysis of lignite ash (in wt%). SiO2
Al2O3
Fe2O3
CaO
TiO2
MgO
K2O
Na2O
SO3
P2O5
51.24
31.47
3.62
2.11
1.97
1.42
1.26
1.23
0.89
0.15
The correlation coefficient (R2) and chi-square (v2) were used for selecting the best equation expressing the drying curves of samples. The higher values of R2 as well as the lower values of v2 were the better model fitting [38]. These parameters were calculated from this statistical package based on the following equations: 2
v
2 PN i¼1 MR exp i MRpre i ¼ Np
ð2Þ
where MRexp and MRpre are experimental and predicted moisture ratio values, respectively, N is the number of observations and p is the number of constants in each set. 3. Results and discussion 3.1. Competitive characterizations Lignites have commonly a high ash content (Table 1) and probably a high mineral concentration. The chemical compositions using XRF for high-temperature coal ash are presented in Table 2. Minerals in this kind of lignite were enriched in SiO2, A12O3, Fe2O3, CaO, TiO2, K2O, and Na2O. These similar chemical compositions were also observed in other Chinese lignites [39]. Then the comparisons of physical and chemical structures between LAS and HAS are further analyzed combing measurements using XRD, SEM, N2 adsorption, and TGA. XRD patterns of LAS and HAS were conducted for individual minerals identified. As seen in Fig. 1, LAS exhibited a broad diffused peak in the 2h range 20–30°, which clearly indicated that this
sample was composed of an amorphous material (maybe porous carbon) as the major component. Only a slightly amount of crystalline impurities of quartz was presented. While, the peaks of other minerals were not visible, which indicated that the amounts could be lower than that of XRD detection limits. Conversely, HAS displayed a totally different XRD patterns with largely consisting of minerals. The major minerals in HAS were identified as quartz, kaolinite, gypsum, pyrite, muscovite, foshagite, and magnetite. Compared with organic matters, most of these minerals presented a relatively heavier manner, which are supported by the true density tests (2.848 g/cm3 showing in Table 3). Moreover, owing to the existence of high contents of these miners and their low ash melting-point, the lignite-boiler inevitably suffered troublesome slag. These distinct characteristics suggested that the floatation process could abandon some of crystalline impurities and thereby resulting in relatively clean and low-density (1.897 g/cm3) lignite. The number of O-containing functional groups is thought to play an important role in the lignite–water interactions by providing binding sites for the water molecules. The FTIR analysis reflecting characteristics of O-containing functional groups was then examined. Fig. 2 illustrates the comparative FTIR spectra of LAS and HAS. The spectral of LAS displayed a typical spectral feature of organic structure: OH groups in water and organic matter (3387 cm1), the aliphatic structures (2920 and 2850 cm1), and humic acids structures (carboxylic group, 1700 cm1; C@C in aromatic compounds, 1620 cm1). Comparatively, the spectral registered for HAS was mainly in the region of 500–1200 cm1. Specifically, the peaks at 1106, 1034 cm1 and 1009 cm1 were commonly owing to the vibrations of (SiAO) in silicates or aluminosilicates while the band at 900–700 cm1 was attributed to hydrogen in aromatic structure. Furthermore, the faint band at 3600–3800 cm1 was also observed, which was connected with the vibrations of free OH groups resulting from silicates or oxyhydroxides. These features could be associated to absorptions caused mainly by mineral matter of the coals (seen XRD analysis). The chemical composition and O-containing functional groups is important whereas insufficient characteristic for a reliable explanation of coal–water interactions. Some important are physical characteristics, especially the special pore structures, which also largely determine the moisture holding capacity of lignites [15]. Consequently, the microstructural pore properties were conducted comparatively by SEM and N2 adsorption. The surface of LAS appeared the almost pure carbonaceous material (Fig. 3a). Furthermore, at 150,000 magnification, several mesopores/microspores were distributed in the carbonaceous material (Fig. 3b). This
Fig. 1. Comparison of XRD patterns of HAS and LAS. A: Quartz (SiO2); B: Kaolinite (Al2O32SiO22H2O); C: Gypsum (CaSO42H2O); D: Pyrite (FeS2); E: Muscovite (KAl2Si3AlO10(OH)2); F: Foshagite, syn (Ca4 (SiO3)3 (OH)2); G: Magnetite (Fe3O4).
Table 3 Physical and chemical properties of lignite (in wt%). Sample
Ash content (wt%)
True density (g/cm3)
Mean diameter (mm)
Thermal conductivity (W/(m k))
LAS HAS
19.76 60.49
1.897 2.848
0.362 0.268
0.1106 0.1475
199
Fig. 2. Comparison of FTIR characteristics of HAS and LAS.
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Fig. 3. Comparison of SEM pictures of LAS and HAS. (a), (b) LAS at different magnifications; (c), (d) HAS at different magnifications.
cohesive structure could prevent the water movement through the lignite mass, which play an important role in the coal–water interactions. In contrast, HAS presented a different morphology. As seen, the surface of HAS obviously reveled heterogeneity due to different kinds of miners remained, which compose the matrix mass (Fig. 3c). This observation confirms the results of the XRD and FTIR results, in which the typical peaks of clay minerals are largely detectable. Moreover, these abundant minerals were ready to deposit/fill on the matrix of carbonaceous material during coalification process. It is not surprising to observe the only presence of large pores in HAS (Fig. 3d). The N2 adsorption/desorption isotherms and pore size distributions of analysis (Fig. 4) confirmed the morphological differences observed by SEM. According to the IUPAC classification, the isotherms obtained in LAS sample (Fig. 4a) displayed a higher hysteresis process, which strongly suggest the formation of mesoporous texture. Pore size distributions of LAS sample (Fig. 4b) showed that the pore size was mainly located in 2–50 nm, which also indicated the mesoporous texture. Previous studies also point out that the mesopore volume was relatively high for some Spanish lignite coals [40]. However, the isotherms of HAS exhibited isotherms of type III with a very narrow H3 type hysteresis loop. Pore size distributions of HAS sample was mainly in the range of 50–70 nm. Both results indicated the composition of macroporous materials. These texture differences could also be seen from the SEM results.
Meanwhile, LAS displayed higher surface areas and a more porosity structure in comparisons to the case of HAS, which is also supported by the presence of porous microstructures (Fig. 3b). The TG/DTA curves of both samples are illustrated in Fig. 5. Both of the thermograms appeared to show similar behavior. For temperature between 100 °C and 300 °C, it could be inferred that inherent water was the major product that was released. As temperature further increased, both TG curves revealed continuous weight loss during heating up to 600 °C, which was mainly due to burning of the organic compounds (FTIR results) [41]. Furthermore, the TG observations were corroborated by the DTA analyses. In the DTA curves, the first endothermic peak occurred at approximately 110 °C, which was obviously attributed by inherent moisture evaporation. An exothermic peak in the range 350–450 °C for both samples in DTA curve was ascribed to the combustion of organic compounds. However, in comparison with the case of LAS, TG and DAT curve in HAS exhibited less drastic destruction behaviors and mild peaks. For temperature between 100 °C and 300 °C, The TG curve obtained a lower weight loss, which indicated smaller amount of inherent moisture. In the temperature range 300–600 °C, this cure also presented a lower weight loss. This behavior was mainly due to less number of O-containing functional groups, which was caused by the presence of abundant minerals in HAS. Apparently, as an increase in minerals content, the inherent moisture content exhibited a decrease trend. The relationship
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3.2. The relationship between minerals content and inherent moisture content
Fig. 4. Comparison of N2 sorption characteristics and pore size distributions of LAS and HAS (a): N2 sorption characteristics; (b) pore size distributions.
Fig. 6a–c shows the variations between ash content and moisture content in lignite after different treatments (screening, dry beneficiation, and flotation). For the lignite treated by screening (Fig. 6a), the obtaining ash content gradually increased with the reduction of grain size, which was opposite to the case of the high rank coals. Previous researchers [42] observed that the ash content in high rank coals increased with the increase of grain size. This unusual trend can be explained as follows: the clay miners (XRD results) in lignite were prone to fragile during crushing process and thereby leading to more ash-forming mineral matters enriched in small particles. While, the contents of total moisture and inherent moisture both decreased with the reduction of grain size. Moreover, as the ash content increased, the content of moisture decreased. Tahmasebi et al. [20] also noticed similar behaviors. However, they could not further identify the relationship between minerals and inherent moisture, which can be of significance in anticipating their use, characterization of combustion wastes and for minimizing some environmental problems. For the lignite treated by dry beneficiation and flotation (Fig. 6band c), increasing the layer number or the density of gravity solution, the obtaining ash content gradually increased. This trend was the nature of treating process. Some distinct variations in the ash content were also observed between these two treatments, which were induced by their different separation efficiencies. To eliminate interference effect of particle size, the lignite samples in both dry beneficiation and flotation tests were in the same particle range (1–3 mm and 0.5 mm). However, the particle size distribution was still different. For the particles size lower than 0.5 mm, the laser particle analysis showed that the mean diameter of highest-ash sample (0.268 mm showing in Table 3) was smaller than the case of lowest-ash sample (0.362 mm). These extra experiments were consistent with the trend observed in Fig. 6a, and proved that as the reduction of grain size the obtaining ash content gradually increased whereas the inherent moisture content decreased. In fact, the particular relationship between minerals and inherent moisture was also confirmed by the sequent tests. As displayed in Fig. 6b and c, it was clearly obtained that the content of inherent moisture exhibited a decreased trend in both cases when an increase in ash content. However, several researchers also argued that the presence of some authigenic minerals, especially (alkali and alkaline earth metals) could improve the moisture holding capacity of coals [15]. While, our results here seemed to suggest that the magnanimous other clay minerals may counteract the improvement of alkali and alkaline earth metals. This decreased trend in the moisture content was mainly caused by the presence of other clay miners. With abundant heterogeneous crystalline minerals, the high-ash lignite sample obtained a small quantity of O-containing functional groups, small surface area and low pore volumes, which largely determined the moisture holding capacity of coals. Therefore, the inherent moisture content of high-ash lignite declined significantly.
Fig. 5. Comparison of TG-DTA characteristics of LAS and HAS.
3.3. Effect of minerals on the drying kinetics between minerals and inherent moisture was rarely reported, which will be described in the following section. Based on these above characterizations, it was concluded that the presence of minerals could potentially play important roles in the phase composition, O-containing functional groups, microstructure, surface areas and pore volumes of lignite. With abundant minerals, HAS thus revealed the heterogeneous crystalline impurities, a smaller quantity of O-containing functional groups, smaller surface area and lower pore volumes.
Temperature is one of most important variables while attempting to achieve high performance of dying process [30]. Thus, in the section, the effects of inlet air temperature and minerals content on the moisture ratio are firstly conducted. The drying curve equations of the mathematical models and drying kinetics are then presented. For the size of 1–3 mm, the variation of MR reduction of different lignites (with different ash contents) with drying time
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Fig. 6. The variations between ash content and moisture content in lignite after different treatments (a): screening; and (b) dry beneficiation; (c) flotation.
Fig. 7. Drying characteristics for different samples (1–3 mm) at different temperatures (a) 80 °C; (b) 105 °C; (c) 150 °C; (d) 180 °C.
P. Zhao et al. / Energy Conversion and Management 93 (2015) 197–204
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Table 4 Mathematical thin layer drying models used in this study. No. 1 2
Model name Page Logarithmic
Model
Reference n
X = exp(k(t )) X = a exp(kt) + c
Zhang and Litchfield [46] Yagcioglu et al. [47]
Table 5 Statistical results for mathematical modeling of drying curves for all cases. Drying temperature (°C)
R2 (LAS)
Page
80 105 150 180
Logarithmic
80 105 150 180
Model
v2
R2 (HAS)
v2
(LAS) 0.99801 0.99794 0.99738 0.99837
0.12214 0.08687 0.05147 0.06668
0.99901 0.99705 0.99500 0.99785
0.05623 0.10075 0.51668 0.21644
0.99706 0.99611 0.99679 0.99773
0.20142 0.04684 0.13298 0.08594
0.99833 0.99434 0.99527 0.99751
0.11318 0.29440 0.34734 0.12520
(HAS)
at different air temperatures is shown in Fig. 7a–d. Under all experimental conditions, the drying process showed some similar patterns. During drying, there were commonly two periods: an initial rapid constant rate period followed by the slow falling rate stage [43]. Meanwhile, the moisture was gradually evaporated until the moisture approached to the critical moisture content. These similar drying processes were also reported in both the drying of coal and of other solids [44,45]. Moreover, as increasing the inlet temperature, the evaporation process was accelerated and the drying times reduced. These above observations indicated that higher temperature was favorable for the drying characteristics in both periods. It was interesting to note that the increasing of minerals content had also significant effect on the drying rate although the effect was not as pronounced as with the increased temperature. Previous studies demonstrated that both of constant rate period and falling rate period were enhanced when the lignite surface temperature increased [7]. However, they rarely noticed the effect of minerals content on the drying process. It was inferred that some imprecise results could be obtained when ignored the effect of minerals content. For concision purpose, only the highest-ash sample and lowest-ash sample were analyzed in the further study. To describe moisture transfer in the lignite at different conditions, two thin layer-drying models (Table 4) were examined. Both statistical parameters (R2 and v2) were adopted to evaluate the fitness with the comparison results showed in Table 5. As seen, the Page model obtained the highest value of R2 the lowest values of v2, which suggested that this model provided the best fitness. The parameters (k and n) were then obtained from the Page model with their results listed in Table 6. For the same temperature and
Table 6 Fitting results of drying equation at different operational parameters. Drying temperature (°C)
Sample
k
n
80
LAS HAS
0.07199 0.09238
1.3032 1.3357
105
LAS HAS
0.12989 0.16833
1.3542 1.4216
150
LAS HAS
0.27469 0.30472
1.5593 1.7586
180
LAS HAS
0.35263 0.36256
1.8292 2.0859
Fig. 8. Plots of ln k versus 1/T for drying processes of HAS and LSA.
ash content, the value of n was approximately a factor of 10 greater than the value of k. Similar values were also found in fluidized bed dryers [38]. It was observed that the values of parameters (k and n) were both increased when temperature and ash content increased. These similar trends may result from the semblable impacts of temperature and ash content. In addition, using this model, the mean of standard deviation between the experimental data and fitting results was approximate 8%. To analyze quantitatively these results, we obtained the activation energies by the Arrhenius equation:
k ¼ k0 expðE=RTÞ
ð3Þ
where k (s1) is the reaction rate constant, k0 (s1) is the pre-exponential factor, E (J mol1) is the activation energy, R is the gas constant, and T (K) is absolute temperature. As seen in Fig. 8, the plots of ln k versus 1/T can be fitted well, and then the activation energy was obtained. The calculated activation energy in this study was consistent with those reported in literature. Moreover, the activation energy of high-ash sample was a bit smaller than that of low-ash sample, which highlighted the important role of minerals. On one hand, additional thermal conductivity experiments (Table 3) indicated that high content minerals resulted in high values of coefficient of thermal conductivity and lower heat transfer resistance, which sped the moisture transfer from inside the particle to the surface. On the other hand, the characterization results also demonstrated that high content minerals led to a poor cohesive structure of holding moisture, which also facilitated the moisture migration. As a consequence of these double effects, the moisture transfer is improved in HSA. 4. Conclusion XRD results indicated prevalence of quartz, kaolinite, gypsum, pyrite, muscovite, foshagite, and magnetite in HAS as compared with LAS obtaining almost homogeneous woody material with minor amounts of quartz. Chemical compositional differences of the examined lignite materials were also revealed by FTIR spectroscopy. HAS exhibited the abundance of minerals in the matrix whereas LAS displayed a typical spectral feature of organic structure containing high contents of O-containing functional groups. SEM imagines combined with the N2 physisorption and TG/DTA results were, in fact, supported XRD and FTIR analyses. HAS revealed few macroporous materials, however, tremendous mesoporous were dispersed in LAS. These completely distinct crystalline patterns, O-containing functional groups and pore structures
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between HAS and LAS were used to further interpret their different inherent moisture behaviors and drying kinetics. Three treatment moisture examinations suggested that the inherent moisture content declined as increasing of ash amounts. This behavior was mainly caused by the presence of clay minerals, which resulted in the less cohesive features as evident by the characterization results. The poor cohesive structure could allow the water movement through the lignite mass, and thereby leading to lower content inherent moisture. The drying results showed that higher minerals were favorable for drying. The Page model achieved the best fitness expressing these drying results and further indicated that HAS provided more excellent drying kinetics with lower activation energies compared with the case of LAS. This enhanced drying kinetics was attributed to higher thermal conductivity and poorer holding-moisture structures resulted from the presence of abundant minerals. Acknowledgements Financial support was sponsored by the Key Project of Chinese National Programs for Fundamental Research and Development (973 program) (2012CB214904), the National Natural Science Foundation of China (51404253) and the National Natural Science Foundation of China for Innovative Research Group (51221462). References [1] Kotowicz J, Balicki A. Enhancing the overall efficiency of a lignite-fired oxyfuel power plant with CFB boiler and membrane-based air separation unit. Energy Convers Manage 2014;80:20–31. [2] Lin Y, Li Q, Li X, Ji K, Zhang H, Yu Y, et al. Pyrolysates distribution and kinetics of Shenmu long flame coal. Energy Convers Manage 2014;86:428–34. [3] Lin B, Ouyang X. A revisit of fossil-fuel subsidies in China: challenges and opportunities for energy price reform. Energy Convers Manage 2014;82:124–34. [4] Saikia BK, Khound K, Baruah BP. Extractive de-sulfurization and de-ashing of high sulfur coals by oxidation with ionic liquids. Energy Convers Manage 2014;81:298–305. [5] Ge L, Zhang Y, Wang Z, Zhou J, Cen K. Effects of microwave irradiation treatment on physicochemical characteristics of Chinese low-rank coals. Energy Convers Manage 2013;71:84–91. [6] Zhao P, Zhao Y, Luo Z, Chen Z, Duan C, Song S. Effect of operating conditions on drying of Chinese lignite in a vibration fluidized bed. Fuel Process Technol 2014;128:257–64. [7] Kim HS, Matsushita Y, Oomori M, Harada T, Miyawaki J, Yoon SH, et al. Fluidized bed drying of Loy Yang brown coal with variation of temperature, relative humidity, fluidization velocity and formulation of its drying rate. Fuel 2013;105:415–24. [8] Katalambula H, Gupta R. Low-grade coals: a review of some prospective upgrading technologies. Energy Fuels 2009;23:3392–405. [9] Osman H, Jangam SV, Lease JD, Mujumdar AS. Drying of low-rank coal (LRC)—a review of recent patents and innovations. Drying Technol 2011;29:1763–83. [10] Karthikeyan M, Zhonghua W, Mujumdar AS. Low-rank coal drying technologies—current status and new developments. Drying Technol 2009;27:403–15. [11] Zhao P, Zhao Y, Chen Z, Luo Z. Dry cleaning of fine lignite in a vibrated gasfluidized bed: Segregation characteristics. Fuel 2015;142:274–82. [12] Dong L, Zhao Y, Luo Z, Duan C, Wang Y, Yang X, et al. A model for predicting bubble rise velocity in a pulsed gas solid fluidized bed. Int J Min Sci Technol 2013;23:227–30. [13] He J, Zhao Y, Luo Z, He Y, Duan C. Numerical simulation and experimental verification of bubble size distribution in an air dense medium fluidized bed. Int J Min Sci Technol 2013;23:387–93. [14] Zhao PF, Zhao YM, Luo ZF, Chen ZQ, Duan CL, Song SL, et al. Feasibility studies of the sequential dewatering/dry separation of Chinese lignite in a vibration fluidized-bed dryer: effect of physical parameters and operation conditions. Energy Fuels 2014;28:4383–91. [15] Yu J, Tahmasebi A, Han Y, Yin F, Li X. A review on water in low rank coals: the existence, interaction with coal structure and effects on coal utilization. Fuel Process Technol 2013;106:9–20. [16] Stanmore BR, Hosking A, White ET, Firth BA. Pore, surface and fillet moisture in centrifuged beds of coarse coal. Fuel 2003;82:41–7. [17] Allardice DJ, Clemow LM, Favas G, Jackson WR, Marshall M, Sakurovs R. The characterisation of different forms of water in low rank coals and some hydrothermally dried products. Fuel 2003;82:661–7.
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Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman
Comparative studies on the effect of mineral matter on physico-chemical properties, inherent moisture and drying kinetics of Chinese lignite Pengfei Zhao a,b, Liping Zhong b, Yuemin Zhao b,⇑, Zhenfu Luo b a b
School of Electric Power Engineering, China University of Mining and Technology, Xuzhou 221116, China School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, China
a r t i c l e
i n f o
Article history: Received 4 October 2014 Accepted 8 January 2015 Available online 28 January 2015 Keywords: Lignite Characterization Inherent moisture Drying kinetics
a b s t r a c t The comparative study between the high-ash lignite (HAS) and low-ash lignite (LAS) demonstrated great effects of mineral matter on physico-chemical properties, inherent moisture and drying kinetics of Chinese lignite. The physico-chemical properties were characterized by X-ray diffraction (XRD), N2 physisorption, fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), and thermoanalytical methods. Raw and treated samples (screening, dry beneficiation, and flotation) were analyzed for inherent moisture content. Drying kinetic experiments were performed by isothermal thermogravimetry in combination with thin-layer models. In comparison with LAS, HAS had less cohesive features with higher amounts of heterogeneous crystalline minerals, less quantity of O-containing functional groups, and smaller surface areas as well as lower pore volumes, as evidenced by characterization analysis. Less cohesive features could allow the moisture to move easily through the lignite, which thus resulted in a lower inherent moisture contained in HAS. On the other hand, due to higher thermal conductivity and poorer holding-moisture structures resulted from the presence of abundant minerals, HAS revealed more promising drying kinetics with lower activation energies, which were determined by the combination of isothermal experiments and Page model analyses. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Low-rank coals, i.e. lignites, are considered as the main energy source, which constitutes significant supplies for both energy and chemical feedstock, mainly because they represent the most abundant and cheapest fossil fuel available [1]. It is estimated that nearly half of the world’s coal reserves consist of lignite. In China, lignite is extensively exploited and largely burnt for power generation [2,3]. Direct combustion of these low-grade coals can lead to low thermal efficiency, high pollutant emissions (particulate materials, SOx, trace elements and CO2) [4] and high operation and maintenance cost, partly due to high amount of moisture and ash-forming mineral matter [4,5]. Thus, it is great importance to removal of moisture and ashes from low-grade coals before combustion. Numerous coal cleaning technologies associated to de-watering [6–10] and de-ashing [11–14] processes have been proposed to sustainably utilize these lignites. However, most of them were not yet widely practiced by the power industry considering the high consumption of energy required during cleaning processes. ⇑ Corresponding author. Fax: +86 516 835900902. E-mail address: [email protected] (Y. Zhao). http://dx.doi.org/10.1016/j.enconman.2015.01.020 0196-8904/Ó 2015 Elsevier Ltd. All rights reserved.
Understanding of fundamental physical and chemical characteristics of lignite structure, particularly in relation to lignite-water interactions is essential to develop new technologies that are efficient, safe and cost-effective [15]. Due to the complicated lignite– water interactions, various aspects involving the forms of water present in low rank coals [16,17], physical–chemical structure of coal [18], migration of water during drying [19], coal structure changes during moisture loss [20], moisture re-adsorption [21], and effects of water removal on subsequent applications [22,23], were widely examined. Several characteristic techniques such as NMR [24], DSC [25] and FTIR [26] in determination and quantification of types of water and coal structures were also conducted. Moreover, a great variety of raw lignites, dried or dewatered lignites, and chemically treated lignites were extensively analyzed in most previous studies [27,28]. However, little information was available and probably could not be applied to the case of highash lignite considering characteristic differences among those moist materials. Study of the specific kinetics of drying process has also important academic and practical significances for the designing of a lignite drying system. Simultaneous heat and mass transfer behaviors, chemical and physical structure of coals, and the variation of heat supply method, all play a role in determining
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the kinetics of lignite dewatering process, which makes mathematical modeling of this complex drying process quite difficult [29]. There are several ways to describe the drying process. The methods used may be divided into three main groups: theoretical [30], semi-theoretical [31], and empirical models [32]. Rely on simultaneous heat and mass transfer, the theoretical models such as shrinking core model, the diffusion model, and multi-scale model were deemed an important method in literature [33]. With some theoretical background, semi-theoretical equations were similar to Newton’s law of cooling [31]. Based upon experimental results, empirical equations are widely used to describe the drying process, mainly due to the fact that these models need no assumptions in geometric, mass diffusivity and conductivity aspects [34]. Pickles et al. [35] using thin-layer empirical equations to examine the microwave drying kinetics of a low-rank sub-bituminous coal. Tahmasebi et al. [29] also gained the drying kinetics of a Chinese low rank coal in the superheated steam fluidized-bed and microwave. Zhao et al. [6] further obtained the drying kinetics of a Chinese low rank coal in a vibration-fluidized bed. Many researchers have revealed that thin-layer empirical equations are often used for description of drying kinetics of low-ash lignite, but little research is available to date on the potential impact of high-ash lignite. As mentioned above, examination on the lignite-water interactions and drying kinetics was limited to the low-ash lignite in most previous studies. However, the conclusions of these studies may be not suitable for the high-ash lignite. The presence of high amount of mineral matter not only could change the physical–chemical structures and inherent moisture content but also may affect the drying kinetics of lignite. Therefore, the physical–chemical structure, inherent moisture content and drying kinetics of high-ash lignite was re-determined in this work. A typical Chinese high-ash lignite was treated by several methods (screening, dry beneficiation, and flotation). The pore structures and functional groups of the de-ashing coal and parent coal were characterized. Then, the characteristics of inherent moisture and the drying kinetics were measured. All the results were comparatively used to demonstrate that the presence of high amount of mineral matter had a great influence on the physical– chemical structure, inherent moisture content and drying kinetics of Chinese lignite. This information can provide the theoretical guidelines for its industrial applications. 2. Experiment 2.1. Lignite properties A typical Chinese lignite sample (Shengli coal in east of Internal Mongolia) is used in this study. Proximate analysis was performed according to the ASTM standards (ASTM E871, D1102-84, D3172-89). Meanwhile, ultimate analysis was using Leco type analyzers CHN-600 and S532-500 (ASTM D3176-93, D3177-33). The proximate analysis and ultimate analysis are listed in Table 1. The coal ash sample was prepared according to Chinese standard procedures (GB/T1574-2001). Thereafter, its chemical composition was tested by X-ray Fluorite Spectroscopy S8 Tiger. This coal was crushed and sieved to five size fractions (0.25, 0.25–0.5, 0.5–1, 1–3 and 3–6 mm). For the size of 1–3 mm, the
dry beneficiation method using a special vibration fluidized bed can be found in our previous studies [14,36]. After fluidization for a certain time, this bed was divided into five layers in the axial direction and the ash content of each layer was measured. For the size of 0.5 mm, the common flotation method using the organic gravity solution was described everywhere [37]. The low drying temperature (<50 °C) was selected to eliminate the unfavorable effect on the pore structure of lignite. These particles were separated into several segments (<1.3, 1.3–1.4, 1.4–1.5, 1.5–1.6, 1.6–1.7, >1.8 g/cm3) based on their densities and the ash content of each segment was analyzed. The lowest and highest density segments were received as low-ash sample (LAS) and high-ash sample (HAS), respectively. The other segments were labeled as middleash sample (MAS). To determine the total moisture and inherent moisture content, 2 g sample as received basis or air-dry basis was dried in an oven at 105 °C for 2 h using a digital balance (Sartorius BT 224 S, with a precision of 0.1 mg). 2.2. Characterization XRD measurements were carried out on a Rigaku RINT2000 wide-angle goniometer with a Cu cathode using recorded in the range between 10° and 90°. Fourier transform infrared–attenuated total reflectance (FTIR) spectrums were collected by a Vertex 80v Spectrometer. The morphologies of samples were observed form FEI QuantaTM 250 instrument. Nitrogen adsorption/desorption isotherms measurements were carried out with a TriStar 3020 system to determine surface area and pore size distribution. The thermo-gravimetric (TG/DTG) and differential thermal (DTA) analysis were obtained simultaneously using a thermal analyzer (Toledo 851) at a heating rate of 10 °C/min, atmospheric air and temperature range 25–600 °C. A Micromeritics AccuPyc 1331 gas pycnometer was used to infer the true density of samples. Three analyses were performed and the results represent the mean values of the measurements. A laser particle analyzer (Microtrac S3500) was used to measure particle size distribution. A Quick Thermal Conductivity Meter (QM-500) was used to obtain the thermal conductivity. 2.3. Drying kinetics The drying characteristics were determined using the Gravimetric Analyzer (AG MA150). Application of infrared heating technology in the drying processing was easy to eliminate the transport effect on the kinetic. During experiments, 3 g sample was carried out at 80 °C, 105 °C, 150 °C and 180 °C drying temperatures and 1–3 mm sample heights. The weight of sample was automatically recorded using a digital balance (with a precision of 1 mg) every 6 s. The moisture content values were calculated on a wet basis by means of the following equations, respectively.
MR ¼
W wet W dry g water g wet coal W wet
ð1Þ
where MR is moisture content, Wwet is initial sample mass, Wdry is the mass of the dry coal. The most common empirical thin layer drying equations (Table 3) were used to describe moisture transfer in the lignite.
Table 1 The proximate and ultimate analysis of Chinese lignite (in wt%). Moisture (ad)
Volatile matter (ad)
Ash (ad)
Fixed carbon (ad)
C (ad)
H (ad)
N (ad)
S (ad)
O (ad)
25.85
22.36
22.93
28.86
57.30
3.08
0.93
0.53
38.16
ad, air dried.
P. Zhao et al. / Energy Conversion and Management 93 (2015) 197–204 Table 2 Chemical composition analysis of lignite ash (in wt%). SiO2
Al2O3
Fe2O3
CaO
TiO2
MgO
K2O
Na2O
SO3
P2O5
51.24
31.47
3.62
2.11
1.97
1.42
1.26
1.23
0.89
0.15
The correlation coefficient (R2) and chi-square (v2) were used for selecting the best equation expressing the drying curves of samples. The higher values of R2 as well as the lower values of v2 were the better model fitting [38]. These parameters were calculated from this statistical package based on the following equations: 2
v
2 PN i¼1 MR exp i MRpre i ¼ Np
ð2Þ
where MRexp and MRpre are experimental and predicted moisture ratio values, respectively, N is the number of observations and p is the number of constants in each set. 3. Results and discussion 3.1. Competitive characterizations Lignites have commonly a high ash content (Table 1) and probably a high mineral concentration. The chemical compositions using XRF for high-temperature coal ash are presented in Table 2. Minerals in this kind of lignite were enriched in SiO2, A12O3, Fe2O3, CaO, TiO2, K2O, and Na2O. These similar chemical compositions were also observed in other Chinese lignites [39]. Then the comparisons of physical and chemical structures between LAS and HAS are further analyzed combing measurements using XRD, SEM, N2 adsorption, and TGA. XRD patterns of LAS and HAS were conducted for individual minerals identified. As seen in Fig. 1, LAS exhibited a broad diffused peak in the 2h range 20–30°, which clearly indicated that this
sample was composed of an amorphous material (maybe porous carbon) as the major component. Only a slightly amount of crystalline impurities of quartz was presented. While, the peaks of other minerals were not visible, which indicated that the amounts could be lower than that of XRD detection limits. Conversely, HAS displayed a totally different XRD patterns with largely consisting of minerals. The major minerals in HAS were identified as quartz, kaolinite, gypsum, pyrite, muscovite, foshagite, and magnetite. Compared with organic matters, most of these minerals presented a relatively heavier manner, which are supported by the true density tests (2.848 g/cm3 showing in Table 3). Moreover, owing to the existence of high contents of these miners and their low ash melting-point, the lignite-boiler inevitably suffered troublesome slag. These distinct characteristics suggested that the floatation process could abandon some of crystalline impurities and thereby resulting in relatively clean and low-density (1.897 g/cm3) lignite. The number of O-containing functional groups is thought to play an important role in the lignite–water interactions by providing binding sites for the water molecules. The FTIR analysis reflecting characteristics of O-containing functional groups was then examined. Fig. 2 illustrates the comparative FTIR spectra of LAS and HAS. The spectral of LAS displayed a typical spectral feature of organic structure: OH groups in water and organic matter (3387 cm1), the aliphatic structures (2920 and 2850 cm1), and humic acids structures (carboxylic group, 1700 cm1; C@C in aromatic compounds, 1620 cm1). Comparatively, the spectral registered for HAS was mainly in the region of 500–1200 cm1. Specifically, the peaks at 1106, 1034 cm1 and 1009 cm1 were commonly owing to the vibrations of (SiAO) in silicates or aluminosilicates while the band at 900–700 cm1 was attributed to hydrogen in aromatic structure. Furthermore, the faint band at 3600–3800 cm1 was also observed, which was connected with the vibrations of free OH groups resulting from silicates or oxyhydroxides. These features could be associated to absorptions caused mainly by mineral matter of the coals (seen XRD analysis). The chemical composition and O-containing functional groups is important whereas insufficient characteristic for a reliable explanation of coal–water interactions. Some important are physical characteristics, especially the special pore structures, which also largely determine the moisture holding capacity of lignites [15]. Consequently, the microstructural pore properties were conducted comparatively by SEM and N2 adsorption. The surface of LAS appeared the almost pure carbonaceous material (Fig. 3a). Furthermore, at 150,000 magnification, several mesopores/microspores were distributed in the carbonaceous material (Fig. 3b). This
Fig. 1. Comparison of XRD patterns of HAS and LAS. A: Quartz (SiO2); B: Kaolinite (Al2O32SiO22H2O); C: Gypsum (CaSO42H2O); D: Pyrite (FeS2); E: Muscovite (KAl2Si3AlO10(OH)2); F: Foshagite, syn (Ca4 (SiO3)3 (OH)2); G: Magnetite (Fe3O4).
Table 3 Physical and chemical properties of lignite (in wt%). Sample
Ash content (wt%)
True density (g/cm3)
Mean diameter (mm)
Thermal conductivity (W/(m k))
LAS HAS
19.76 60.49
1.897 2.848
0.362 0.268
0.1106 0.1475
199
Fig. 2. Comparison of FTIR characteristics of HAS and LAS.
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Fig. 3. Comparison of SEM pictures of LAS and HAS. (a), (b) LAS at different magnifications; (c), (d) HAS at different magnifications.
cohesive structure could prevent the water movement through the lignite mass, which play an important role in the coal–water interactions. In contrast, HAS presented a different morphology. As seen, the surface of HAS obviously reveled heterogeneity due to different kinds of miners remained, which compose the matrix mass (Fig. 3c). This observation confirms the results of the XRD and FTIR results, in which the typical peaks of clay minerals are largely detectable. Moreover, these abundant minerals were ready to deposit/fill on the matrix of carbonaceous material during coalification process. It is not surprising to observe the only presence of large pores in HAS (Fig. 3d). The N2 adsorption/desorption isotherms and pore size distributions of analysis (Fig. 4) confirmed the morphological differences observed by SEM. According to the IUPAC classification, the isotherms obtained in LAS sample (Fig. 4a) displayed a higher hysteresis process, which strongly suggest the formation of mesoporous texture. Pore size distributions of LAS sample (Fig. 4b) showed that the pore size was mainly located in 2–50 nm, which also indicated the mesoporous texture. Previous studies also point out that the mesopore volume was relatively high for some Spanish lignite coals [40]. However, the isotherms of HAS exhibited isotherms of type III with a very narrow H3 type hysteresis loop. Pore size distributions of HAS sample was mainly in the range of 50–70 nm. Both results indicated the composition of macroporous materials. These texture differences could also be seen from the SEM results.
Meanwhile, LAS displayed higher surface areas and a more porosity structure in comparisons to the case of HAS, which is also supported by the presence of porous microstructures (Fig. 3b). The TG/DTA curves of both samples are illustrated in Fig. 5. Both of the thermograms appeared to show similar behavior. For temperature between 100 °C and 300 °C, it could be inferred that inherent water was the major product that was released. As temperature further increased, both TG curves revealed continuous weight loss during heating up to 600 °C, which was mainly due to burning of the organic compounds (FTIR results) [41]. Furthermore, the TG observations were corroborated by the DTA analyses. In the DTA curves, the first endothermic peak occurred at approximately 110 °C, which was obviously attributed by inherent moisture evaporation. An exothermic peak in the range 350–450 °C for both samples in DTA curve was ascribed to the combustion of organic compounds. However, in comparison with the case of LAS, TG and DAT curve in HAS exhibited less drastic destruction behaviors and mild peaks. For temperature between 100 °C and 300 °C, The TG curve obtained a lower weight loss, which indicated smaller amount of inherent moisture. In the temperature range 300–600 °C, this cure also presented a lower weight loss. This behavior was mainly due to less number of O-containing functional groups, which was caused by the presence of abundant minerals in HAS. Apparently, as an increase in minerals content, the inherent moisture content exhibited a decrease trend. The relationship
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3.2. The relationship between minerals content and inherent moisture content
Fig. 4. Comparison of N2 sorption characteristics and pore size distributions of LAS and HAS (a): N2 sorption characteristics; (b) pore size distributions.
Fig. 6a–c shows the variations between ash content and moisture content in lignite after different treatments (screening, dry beneficiation, and flotation). For the lignite treated by screening (Fig. 6a), the obtaining ash content gradually increased with the reduction of grain size, which was opposite to the case of the high rank coals. Previous researchers [42] observed that the ash content in high rank coals increased with the increase of grain size. This unusual trend can be explained as follows: the clay miners (XRD results) in lignite were prone to fragile during crushing process and thereby leading to more ash-forming mineral matters enriched in small particles. While, the contents of total moisture and inherent moisture both decreased with the reduction of grain size. Moreover, as the ash content increased, the content of moisture decreased. Tahmasebi et al. [20] also noticed similar behaviors. However, they could not further identify the relationship between minerals and inherent moisture, which can be of significance in anticipating their use, characterization of combustion wastes and for minimizing some environmental problems. For the lignite treated by dry beneficiation and flotation (Fig. 6band c), increasing the layer number or the density of gravity solution, the obtaining ash content gradually increased. This trend was the nature of treating process. Some distinct variations in the ash content were also observed between these two treatments, which were induced by their different separation efficiencies. To eliminate interference effect of particle size, the lignite samples in both dry beneficiation and flotation tests were in the same particle range (1–3 mm and 0.5 mm). However, the particle size distribution was still different. For the particles size lower than 0.5 mm, the laser particle analysis showed that the mean diameter of highest-ash sample (0.268 mm showing in Table 3) was smaller than the case of lowest-ash sample (0.362 mm). These extra experiments were consistent with the trend observed in Fig. 6a, and proved that as the reduction of grain size the obtaining ash content gradually increased whereas the inherent moisture content decreased. In fact, the particular relationship between minerals and inherent moisture was also confirmed by the sequent tests. As displayed in Fig. 6b and c, it was clearly obtained that the content of inherent moisture exhibited a decreased trend in both cases when an increase in ash content. However, several researchers also argued that the presence of some authigenic minerals, especially (alkali and alkaline earth metals) could improve the moisture holding capacity of coals [15]. While, our results here seemed to suggest that the magnanimous other clay minerals may counteract the improvement of alkali and alkaline earth metals. This decreased trend in the moisture content was mainly caused by the presence of other clay miners. With abundant heterogeneous crystalline minerals, the high-ash lignite sample obtained a small quantity of O-containing functional groups, small surface area and low pore volumes, which largely determined the moisture holding capacity of coals. Therefore, the inherent moisture content of high-ash lignite declined significantly.
Fig. 5. Comparison of TG-DTA characteristics of LAS and HAS.
3.3. Effect of minerals on the drying kinetics between minerals and inherent moisture was rarely reported, which will be described in the following section. Based on these above characterizations, it was concluded that the presence of minerals could potentially play important roles in the phase composition, O-containing functional groups, microstructure, surface areas and pore volumes of lignite. With abundant minerals, HAS thus revealed the heterogeneous crystalline impurities, a smaller quantity of O-containing functional groups, smaller surface area and lower pore volumes.
Temperature is one of most important variables while attempting to achieve high performance of dying process [30]. Thus, in the section, the effects of inlet air temperature and minerals content on the moisture ratio are firstly conducted. The drying curve equations of the mathematical models and drying kinetics are then presented. For the size of 1–3 mm, the variation of MR reduction of different lignites (with different ash contents) with drying time
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Fig. 6. The variations between ash content and moisture content in lignite after different treatments (a): screening; and (b) dry beneficiation; (c) flotation.
Fig. 7. Drying characteristics for different samples (1–3 mm) at different temperatures (a) 80 °C; (b) 105 °C; (c) 150 °C; (d) 180 °C.
P. Zhao et al. / Energy Conversion and Management 93 (2015) 197–204
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Table 4 Mathematical thin layer drying models used in this study. No. 1 2
Model name Page Logarithmic
Model
Reference n
X = exp(k(t )) X = a exp(kt) + c
Zhang and Litchfield [46] Yagcioglu et al. [47]
Table 5 Statistical results for mathematical modeling of drying curves for all cases. Drying temperature (°C)
R2 (LAS)
Page
80 105 150 180
Logarithmic
80 105 150 180
Model
v2
R2 (HAS)
v2
(LAS) 0.99801 0.99794 0.99738 0.99837
0.12214 0.08687 0.05147 0.06668
0.99901 0.99705 0.99500 0.99785
0.05623 0.10075 0.51668 0.21644
0.99706 0.99611 0.99679 0.99773
0.20142 0.04684 0.13298 0.08594
0.99833 0.99434 0.99527 0.99751
0.11318 0.29440 0.34734 0.12520
(HAS)
at different air temperatures is shown in Fig. 7a–d. Under all experimental conditions, the drying process showed some similar patterns. During drying, there were commonly two periods: an initial rapid constant rate period followed by the slow falling rate stage [43]. Meanwhile, the moisture was gradually evaporated until the moisture approached to the critical moisture content. These similar drying processes were also reported in both the drying of coal and of other solids [44,45]. Moreover, as increasing the inlet temperature, the evaporation process was accelerated and the drying times reduced. These above observations indicated that higher temperature was favorable for the drying characteristics in both periods. It was interesting to note that the increasing of minerals content had also significant effect on the drying rate although the effect was not as pronounced as with the increased temperature. Previous studies demonstrated that both of constant rate period and falling rate period were enhanced when the lignite surface temperature increased [7]. However, they rarely noticed the effect of minerals content on the drying process. It was inferred that some imprecise results could be obtained when ignored the effect of minerals content. For concision purpose, only the highest-ash sample and lowest-ash sample were analyzed in the further study. To describe moisture transfer in the lignite at different conditions, two thin layer-drying models (Table 4) were examined. Both statistical parameters (R2 and v2) were adopted to evaluate the fitness with the comparison results showed in Table 5. As seen, the Page model obtained the highest value of R2 the lowest values of v2, which suggested that this model provided the best fitness. The parameters (k and n) were then obtained from the Page model with their results listed in Table 6. For the same temperature and
Table 6 Fitting results of drying equation at different operational parameters. Drying temperature (°C)
Sample
k
n
80
LAS HAS
0.07199 0.09238
1.3032 1.3357
105
LAS HAS
0.12989 0.16833
1.3542 1.4216
150
LAS HAS
0.27469 0.30472
1.5593 1.7586
180
LAS HAS
0.35263 0.36256
1.8292 2.0859
Fig. 8. Plots of ln k versus 1/T for drying processes of HAS and LSA.
ash content, the value of n was approximately a factor of 10 greater than the value of k. Similar values were also found in fluidized bed dryers [38]. It was observed that the values of parameters (k and n) were both increased when temperature and ash content increased. These similar trends may result from the semblable impacts of temperature and ash content. In addition, using this model, the mean of standard deviation between the experimental data and fitting results was approximate 8%. To analyze quantitatively these results, we obtained the activation energies by the Arrhenius equation:
k ¼ k0 expðE=RTÞ
ð3Þ
where k (s1) is the reaction rate constant, k0 (s1) is the pre-exponential factor, E (J mol1) is the activation energy, R is the gas constant, and T (K) is absolute temperature. As seen in Fig. 8, the plots of ln k versus 1/T can be fitted well, and then the activation energy was obtained. The calculated activation energy in this study was consistent with those reported in literature. Moreover, the activation energy of high-ash sample was a bit smaller than that of low-ash sample, which highlighted the important role of minerals. On one hand, additional thermal conductivity experiments (Table 3) indicated that high content minerals resulted in high values of coefficient of thermal conductivity and lower heat transfer resistance, which sped the moisture transfer from inside the particle to the surface. On the other hand, the characterization results also demonstrated that high content minerals led to a poor cohesive structure of holding moisture, which also facilitated the moisture migration. As a consequence of these double effects, the moisture transfer is improved in HSA. 4. Conclusion XRD results indicated prevalence of quartz, kaolinite, gypsum, pyrite, muscovite, foshagite, and magnetite in HAS as compared with LAS obtaining almost homogeneous woody material with minor amounts of quartz. Chemical compositional differences of the examined lignite materials were also revealed by FTIR spectroscopy. HAS exhibited the abundance of minerals in the matrix whereas LAS displayed a typical spectral feature of organic structure containing high contents of O-containing functional groups. SEM imagines combined with the N2 physisorption and TG/DTA results were, in fact, supported XRD and FTIR analyses. HAS revealed few macroporous materials, however, tremendous mesoporous were dispersed in LAS. These completely distinct crystalline patterns, O-containing functional groups and pore structures
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