Co-pyrolysis characteristics of microalgae Chlorella vulgaris and coal through TGA

Bioresource Technology 117 (2012) 264–273

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Co-pyrolysis characteristics of microalgae Chlorella vulgaris and coal through TGA Chunxiang Chen ⇑, Xiaoqian Ma, Yao He School of Electric Power, South China University of Technology, PR China

h i g h l i g h t s " Co-pyrolysis presented three stages. " Interaction between solid phases inhibited the thermal decomposition. " Kinetic triplets were obtained.

a r t i c l e

i n f o

Article history: Received 30 January 2012 Received in revised form 19 April 2012 Accepted 21 April 2012 Available online 30 April 2012 Keywords: Microalgae Chlorella vulgaris Co-pyrolysis Coal Thermogravimetric analysis (TGA)

a b s t r a c t To find out an alternative of coal saving, a kind of microalgae, Chlorella vulgaris (C. vulgaris) which is widespread in fresh water was introduced into coal pyrolysis process. In this work, the pyrolysis experiments of C. vulgaris and coal blend (CCB) were carried out by TGA, and those of C. vulgaris and coal were also taken respectively as control groups. It was found that: the TG and DTG profiles of CCB were similar to C. vulgaris, but different from coal under various blending ratios; DTG profiles of CCB were different at several heating rates; interaction was observed between the solid phases of CCB; kinetic triplets were determined by the Kissinger–Akahira–Sunose (KAS), Flynn–Wall–Ozawa (FWO), and master-plots method, respectively. The results provide a reference for further study on co-pyrolysis of microalgae and coal to a certain extent. Crown Copyright Ó 2012 Published by Elsevier Ltd. All rights reserved.

1. Introduction Biomass is the third largest energy resource in the world while coal is the first one, and followed by oil. In view of the increasing energy demand, the great costs of fossil fuels, as well as the eco-friendly concerns in terms of the level of CO2 release in the atmosphere, biomass utilization which provides a partial substitution of fossil fuels for power generation, has attracted increasingly interest over the world (Lou and Wu, 2011). Potential biomass fuels are in variety, which may include short-rotation woody crops and herbaceous species, forestry waste, municipal solid waste, as well as construction waste, etc. (Guo et al., 2010). Microalgae, a type of prokaryotic or eukaryotic photosynthetic microorganism, growing rapidly and naturally in abundance over water areas such as ponds, lakes, and rivers, etc., is considered as one of the most promissory renewable feedstock for bio-fuels production. Many relative advantages of microalgae are brought into sight, comparing with other energy crops, in terms of faster growth, shorter rotation, higher oil content, higher photosynthetic

⇑ Corresponding author. Tel.: +86 20 87110232; fax: +86 20 87110613. E-mail address: [email protected] (C. Chen).

efficiency, higher productivity, higher bio-chemical activity, as well as lower requirement of agricultural land (Amaro et al., 2011; Dragone et al., 2011; Huang et al., 2010; Lee et al., 2010a; Mata et al., 2010; Phukan et al., 2011). In addition, microalgae admits the direct generation of products desired such as bio-oil, hydrogen and by-products (e.g. starch) (Posten and Schaub, 2009). Although the huge cost of separating microalgae from water mixtures constrains their large-scale usage as an alternative fuels for energy supply, a research on valued and high quality fuels obtained from microalgae species is worthwhile for future achievements. Chlorella, a genus of unicellular green microalgae, with a spherical shape of 2.0–10.0 lm in diameter, living both in fresh and marine water, can generally be found in fresh water of ponds and ditches, moist soil or other damp situations such as the surface of tree trunks, water pots and damp walls (Phukan et al., 2011). Chlorella has eight species and Chlorella vulgaris (C. vulgaris) is one among them, growing in fresh water. Pyrolysis is a promising thermochemical conversion method, playing a vital role in biomass conversion to green energy. A pyrolysis process can be considered not only as an independent process to produce various chemical compounds and fuels, but also as the initial stage of thermal conversion process of carbonaceous materials, including combustion and gasification. Biomass pyrolysis

0960-8524/$ - see front matter Crown Copyright Ó 2012 Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2012.04.077

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

generally goes through a series of extremely complex reactions and is deeply influenced by a lot of factors such as heating rate, temperature, and feedstock composition (Lou and Wu, 2011). Pyrolysis characteristics of pure microalgae in nitrogen atmosphere have been studied by many researchers. For example, Grierson et al. (2009) studied the thermal characterization of six selected species of microalgae under slow pyrolysis conditions, and found that at 500 °C, the ratio, composition and calorific value of evolved liquid, gas and char products varied markedly across all species. Also, two kinds of autotrophic microalgae, spirulina (SP) and Chlorella protothecoides (CP), were studied by a thermogravimetric analyzer at the different heating rates, and found that SP and CP mainly devolatilized at 190–560 °C and 150–540 °C, respectively; the value of activation energy (E) for CP pyrolysis was 4.22–5.25  104, lower than that of SP (7.62–9.70  104), and the char in final residues of CP was 14.00–15.14%, less than that of SP by 2–3% (Peng et al., 2001). Further, an approach for increasing the yield of bio-oil production from fast pyrolysis after manipulating the metabolic pathway in microalgae through heterotrophic growth were proposed; the yield of bio-oil (57.9%) produced from heterotrophic C. protothecoides cells was 3.4 times higher than from autotrophic cells by fast pyrolysis. The bio-oil was characterized by a much lower oxygen content, with a higher heating value (41 MJ kg1), a lower density (0.92 kg L1), and lower viscosity (0.02 Pa s) compared to those of bio-oil from autotrophic cells and wood (Miao et al., 2004). In addition, Shuping et al. (2010) studied a genus of unicellular green marine microalgae, Dunaliella tertiolecta pyrolyzed in a thermogravimetric analyzer at different heating rates, and found that three stages appeared in its thermal degradation process, with increasing temperature, initial temperature, and peak temperature of pyrolysis shifting to a higher value as the heating rate increased; the increased heating rate also resulted in increased total volatile matter. The iso-conversional method indicated that the pyrolysis reaction should conform to a single reaction model with E of 145.713 kJ mol1 using Kissinger’s method and 146.421 kJ mol1 using Flynn–Wall–Ozawa’s (FWO) method, respectively. In terms of the combustion characteristics of C. vulgaris under different oxygen supply concentrations, there are also an investigation reported (Chen et al., 2011). However, the yield of conversion product from coal pyrolysis is constrained by its composition of low hydrogen to carbon molar ratio. To increase the product yield, it is necessary to supply hydrogen to coal pyrolysis process from other sources. Biomass inheriting high hydrogen to carbon molar ratio could act as hydrogen-donors in a co-pyrolysis process of biomass and coal. Furthermore, synergy between the two species which increases the amount of volatile matters is potentially existed, and causal to better thermal conversion performance. Therefore, it is desirable to co-processing the two species to achieve a high thermal conversion efficiency, to maintain a sustainable utilization level of coal and to minimize the impact of coal utilization on environment. It has been shown that many blends of biomass species and coal, such as hazelnut shell and coal (Haykiri-Acma and Yaman, 2010), legume straw and coal (Zhang et al., 2007), and sawdust and coal (Lee et al., 2010b), exhibit

synergetic effects during co-pyrolysis process. However, whether any interaction exists in the co-pyrolysis of microalgae and coal remains unknown. In this work, the pyrolysis behaviors of C. vulgaris and coal blend (CCB) were studied though a thermogravimetric analyzer. The aim is to investigate the characteristics referring to: interaction between the solid phases of CCB in co-pyrolysis process; effects of C. vulgaris to coal ratio (MCR) and heating rate (b) on the thermal decomposition of CCB; thermal decomposition kinetics of pure C. vulgaris and CCBs at several MCRs, obtained by the Kissinger– Akahira–Sunose (KAS), FWO and master-plots method, including E, reaction order (n) and pre-exponential factor (A). 2. Methods 2.1. Sample preparation The feedstock used in this study included powder of C. vulgaris provided by the Jiangmen Yue Jian Biotechnologies Co., Ltd. (Guangdong Province, China) and Semi-anthracite coal provided by Huangpu power plant in Guangzhou. The coal is difficult to fire and burn, and its C/H is about 13.32 which is much higher than biomass’. Thus, it was chosen to blend with C. vulgaris. The samples of C. vulgaris and coal were shredded into powder with small molecules and dried at 105 °C for 20 h, and then blended complying with the ratios of 3/7, 5/5, and 7/3 in weight by tumbling for 2 h to achieve proximate homogeneity (Zhang et al., 2007). Finally, the powder of CCB, pure C. vulgaris and pure coal were sieved to achieve a size-range less than 200 lm. The ultimate analysis, proximate analysis and lower heating values of samples were carried out through Vario EL-II chons elemental analyzer (Elementar Analysen systeme Gmbh, Germany), MA260S electronic balance (Shanghai Second Balance Instrument Factory, Shanghai, China) and Parr 6300 oxygen bomb calorimeter (PARR Instrument Company, America) correspondingly. The results are presented in Table 1. 2.2. Experiments The experiments were carried out on a thermogravimetry analyzer of NETZSCH STA 409 PC of which the balance and temperature control system can accurately record weight loss of 0.001 mg and temperature of 0.1 °C, respectively. In order to avoid heat and mass transfer limitations, small samples (6 mg) were loaded into an Al2O3 ceramic crucible with a pin-holed lid for each under non-isothermal conditions in N2 atmosphere. All of the samples were heated from ambient temperature to 105 °C at which they were held for 10 min to ensure a complete removal of free-water, and then were further heated up to 1000 °C at b = 10, 20 and 40 °C min1 under a nitrogen flow rate of 100 ml min1 to ensure an inert atmosphere. Three iterations of each round are needed to carry out, in order to guarantee the error of experimental results within ±5%.

Table 1 Ultimate and proximate analysis and lower heating values on dry basis. Samples

C. vulgaris Coal a b c d

Ultimate analysis (wt.%)

b

C

H

O

N

S

V

47.84 63.15

6.41 4.74

25.00 8.84

9.01 0.78

1.46 0.92

55.37 33.12

Qnet,d, lower heating value on dry basis. V, volatile matters. A, ash. FC, fixed carbon.

Qnet,da (MJ kg1)

Proximate analysis (wt.%) A

c

10.28 21.57

FC

d

34.35 45.31

21.88 26.32

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

2.3. Kinetic model

In addition, the integrated form of Eq. (7) can be expressed by a master-plots method (Shuping et al., 2010)

The kinetic equation of common type can be generally shown as follows:

da ¼ kðTÞf ðaÞ dt

ð1Þ

where a is conversion degree, t is time, T is the absolute temperature, k(T)is temperature dependent rate constant, f(a) is function relating to reaction mechanism, a is expressed as (Xiao et al., 2009; Zuru et al., 2004):

m  mt a¼ i mi  m1

ð2Þ

where mi is the initial mass of sample, mt is the mass of the sample at time t, m1 is the final mass of the sample in the reaction. According to Arrhenius equation, k(T)is usually expressed as follows:

  E k ¼ A exp  RT

ð3Þ

  da E f ðaÞ ¼ A exp  RT dt

ð4Þ 1

When heating rate b (K s

)

dT b¼ dt

ð5Þ

is introduced, Eq. (4) is transformed to

  da A E f ðaÞ ¼ exp  RT dT b

ð6Þ

An integration function of Eq. (6) is shown as below

Z

a

0

da A ¼ f ðaÞ b

Z

T

T0

  E dT exp  RT

T ¼ T 0 þ bt

ð7Þ ð8Þ

where T0 (K) is initial temperature of experiments (Cai and Liu, 2008). It is well known that the iso-conversional method can easily give an estimation of E in spite of the reaction mechanism, and thus two iso-conversional methods, Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) methods are applied for E determination in this work. Although a great number of the other kinetics analysis methods of non-isothermal solid state reactions have been proposed and used, here only the mentioned two isoconversional ones will be taken into concern due to the relative higher reliability themselves (Tanaka, 1995). The FWO method (Shuping et al., 2010) can be expressed as the following equation:

ln b ¼ ln



 0:0048AEa Ea  1:0516 RgðaÞ Rt

ð9Þ

When a = constant, the values of ln b versus 1/T, obtained at several bs, could be correlated by a straight line of which the slope allows E determination. The KAS method can be expressed as the following equation (Boonchom and Puttawong, 2010; Shuping et al., 2010):

ln

b T 2a

! ¼ ln



AE PðuÞ bR

 AR Ea  Ea gðaÞ RT a

ð10Þ

Ea can be determinedfrom  the slope of line generated through a linear correlation of ln Tb2 versus 1/T as well. a

ð11Þ

Ru where the temperature integral, PðuÞ ¼ 1 ðeu =u2 Þdu (u = E/RT), has no analytical solution and can be expressed by an approximation. The rational approximation of Doyle (1962) gives sufficiently accurate results:

PðuÞ ¼ 0:00484 expð1:0516uÞ

ð12Þ

For a single-step process with an invariant g(a) expression, an analysis using the master plots delivers an unambiguous choice of the appropriate kinetic model. Taking account into a single-step process, the A and E are invariable. Using a reference at point a = 0.5 and according to Eq. (11), one gets

gð0:5Þ ¼

where A (s1) is the pre-exponential or frequency factor, E (J mol1) is the activation energy, R (J mol1 K1) is the universal gas constant. The combination of Eqs. (1) and (3) gives

gðaÞ ¼

gðaÞ ¼

  AE Pðu0:5 Þ bR

ð13Þ

where u0.5 = E/RT(0.5). The following equation is obtained by dividing Eq. (11) by Eq. (13)

gðaÞ PðuÞ ¼ gð0:5Þ Pðu0:5 Þ

ð14Þ

Plotting g(a)/g(0.5) against a corresponds to theoretical master plots of various g(a) functions (Table 2). To draw the experimental master plots of P(u)/P(u0.5) against a from experimental data obtained under any heating rates, the experimental master plot is independent of the heating schedule. Eq. (14) indicates that, for a given a, the experimental value of P(u)/P(u0.5) and theoretically calculated values of g(a)/g(0.5) are equivalent when an appropriate kinetic model is used. This integral master-plots method can be used to determine the reaction kinetic models of decomposition reactions. 3. Results and discussion 3.1. Pyrolysis process Description and explanation of the pyrolysis process of C. vulgaris, coal, and CCBs with several MCRs (3/7, 5/5 and 7/3 in weight) at b = 20 °C min1 are given in this section with thermogravimetry (TG) and differential thermogravimetry (DTG) plot. As shown in Fig. 1a, the TG plot, the profiles of pure C. vulgaris and CCB are alike, yet that of pure coal varies from either of them. The thermal decomposition process of CCB can be divided into three stages: the first stage is from the ambient temperature (25 °C) and to168–178 °C (depending on MCRs), where the loss of both water and light volatile compounds occurs; the second stage is from the end of the first stage to 555–600 °C (depending on MCRs), where most organic species are decomposed – the main pyrolysis process; the third stage is from the end of the second stage to 1000 °C, where carbonaceous residue is decomposed slowly. However the thermal decomposition of coal is initialized at around 320 °C and proceeds at a relatively low reaction rate until the terminated temperature of experiment, without any clear demarcations. Further, the lowest residue mass (MR) is the case of C. vulgaris pyrolysis alone and the next lowest one is coal pyrolysis alone, both of which occur at the terminated temperature (1000 °C) of the experiments. Any MCR increases the value of weight loss and the largest value achieves 53 wt.% at MCR = 3/7. However, at low temperature (especially within the second stage), the value of either MCR is stuck between that of pure C. vulgaris and pure coal.

267

C. Chen et al. / Bioresource Technology 117 (2012) 264–273 Table 2 Most frequently used mechanisms of solid state processes. Mechanisms

Symbol

F(a)

g(a)

Order of reaction First-order Second-order Third-order

F1 F2 F3

1a (1  a)2 (1  a)3

ln(1  a) (1  a)1  1 [(1  a)2  1]/2

Diffusion One-way transport Two-way transport Three-way transport Ginstling-Brounshtein equation

D1 D2 D3 D4

0.5a [ln(1  a)]1 1.5(1  a)2/3[1  (1  a)1/3]1 1.5(1  a)1/3]1

a2 a+(1  a)ln(1  a) [1  (1  a)1/3]2 (1–2a/3)  (1  a)2/3

Limiting surface reaction between both phases One dimension Two dimensions Three dimensions

R1 R2 R3

1 2(1  a)1/2 3(1  a)2/3

a

Random nucleation and nuclei growth Two-dimensional Three-dimensional

A2 A3

2(1  a)[ln(1  a)]1/2 3(1  a)[ln(1  a)]2/3

[ln(1  a)]1/2 [ln(1  a)]1/3

Exponential nucleation Power law, n = ½ Power law, n = 1/3 Power law, n = 1/4

P2 P3 P4

2a1/2 3a2/3 4a3/4

a1/2 a1/3 a1/4

MCR=3/7 MCR=5/5

TG (wt.%)

90 80

MCR=7/3

70

C.vulgaris Coal

60 50 40

b 0 -1 -1

100

DTG( wt%·min )

a

1  (1  a)1/2 1  (1  a)1/3

-2 -3 -4

MCR=3/7 MCR=5/5 MCR=7/3 C. vulgaris Coal

-5 -6 -7

30

-8 20 100

200

300

400

500

600

700

800

900 1000

Temperature( ℃)

-9 100

200

300

400

500 600

700

800

900 1000

Temperature( ℃)

Fig. 1. (a) TG profiles for C. vulgaris, coal and CCB of several MCRs at b = 20 °C min1; (b) DTG profiles for C. vulgaris, coal and CCB of several MCRs at b = 20 °C min1.

This phenomenon may result from the inhibitive effect for thermal decomposition between the solid phases of C. vulgaris and coal when co-pyrolysis and a detailed discussion of this characteristic is held in the next section (Section 3.2). In Fig. 1b, the DTG plot, the profiles of pure C. vulgaris and CCB are alike with one clear peak each, which present different shapes from that of pure coal with several vague ones. Thus, pure coal pyrolysis process indicates a multi-stage characteristic. Further, the weight loss rate of either MCR of CCB is stuck between the value of C. vulgaris and coal at a fixed temperature especially within the second stage. Besides, the thermal decomposition of CCB generally proceeds at lower temperature (below 550 °C), and even that of pure C. vulgaris completes at 545 °C which is much lower than the coal’s completion temperature (above 1000 °C). The phenomenon probably results from the greater amount of volatile content in C. vulgaris and such amount is about to bring an easier pyrolysis initiation as well as shorter duration. Thus CCB and pure C. vulgaris could be assumed as more active than pure coal at low temperature, leading to a fast completion. In a DTG plot, vertical coordinates also equivalent to reaction rate. Thus, several parameters about the pyrolysis can be valued, including (1) initial temperature of decomposition(TIn), (2) terminated temperature of the second stage (TF), (3) temperature of the maximum reaction rate (Tmax), (4) maximum reaction rate (Dmax), (5) temperature of DTG peaks (T1, T2), (6) reaction rate of

DTG peaks (D1 and D2), (7) reaction rate average of the second stage (DA), (8) mass loss of the maximum reaction rate (Mmax), and (9) MR, which are listed in Table 3. It is found that the thermal decomposition initial temperature (320 °C) of coal is higher than those of C. vulgaris (168 °C) and CCBs (172–178 °C).The reaction rates of CCB with the MCRs of 3/7, 5/5 and 7/3 in weight, attain Dmax at the temperatures of 336, 337.3 and 335.6 °C accordingly. Dmax of pure C. vulgaris is 334 °C close to either of the Dmax temperatures (336, 337.3 and 335.6 °C) of CCB and much lower than that of coal (613.5 °C). 3.2. Characterization of interaction between the solid phases of CCB In this section, comparisons between weight loss values practical (Wpractical) and calculated (Wcalculated) are made under fixed temperature for investigating whether there is any interaction between the solid phases of CCB; if any, how they influence on thermal decomposition – accelerative (synergistic) or inhibitive; then, to what degree the influence functions and how it varies with temperature. Wcalculated is calculated by an additive model that a blend’s total weight at certain temperature is the sum of the weight of each pure component by its fraction at that temperature, which serves as a baseline for the comparison. It is expressed as follows (Aboulkas et al., 2008a,b; Lee et al., 2010a):

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

Table 3 Results from TGA at b = 20 °C min1.

a b c d e f g h i j k

Sample

TIna (°C)

T1b (°C)

D1c (wt.% min1)

T2d (°C)

D2e (wt.% min1)

Dmaxf (wt.% min1)

Tmaxg (°C)

Mmaxh (wt.%)

DAi (wt.% min)

TFj (°C)

MRk (wt.%)

Coal C. vulgaris/ coal = 3/7 C. vulgaris/ coal = 5/5 C. vulgaris/ coal = 7/3 C. vulgaris

320 178

613.5 336

2.23 2.66

– 444.4

– 2.26

2.23 2.66

613.5 336

31.84 16.4

1.76 1.838

– 600

– 53

175

337.3

4.3

386

2.58

4.3

337.3

21.11

2.544

580

46.09

172

308.4

5.53

335.6

6.15

6.15

335.6

28.95

3.097

565

35.26

168

295.3

7.61

334

8.52

8.52

334

38

4.16

555

21.04

TIn, initial decomposition temperature. T1, temperature of the higher DTG peak. D1, reaction rate of the higher DTG peak. T2, temperatures for the lower DTG peak. D2, reaction rate for the lower peak. Dmax, the maximum reaction rate. Tmax, temperature of the maximum reaction rate. Mmax, mass loss of the maximum rate. DA, reaction rate average of the second stage. TF, terminated temperature of the second stage. MR, pyrolysis residue mass.

W calculated ¼ X 1 W 1 þ X 2 W 2

ð15Þ

where Xi is the mass fraction coefficient and Wi (wt.%) is the weight loss. The values of Wcalculated and Wpractical at b = 20 °C min1 with several MCRs are presented by curves in Fig. 2a–c, in each of which their curves are different from one and another. Clearly, Wpractical is less than Wcalculated at any MCR. As a result, the interaction between the solid phases of CCB does exist, and their effect on thermal decomposition is inhibitive rather than accelerative. At either MCR, the two curves do not possess a clear deviation below 320 °C; they begin to diverge at about 320 °C and the divergence tends bigger with a relatively slow pace until 550 °C – the deviation between them does not grow as fast as it is under the temperature above 550 °C. In terms of variations in relation to MCR, with its increase, the Wcalculated increases and achieves 69.883, 72.407, and 74.932 wt.% corresponding to MCR = 3/7, 5/5, and 7/3 at the terminated temperature (1000 °C); additionally, in 320–550 °C the deviation becomes smaller, which can be associated to the faster decomposition rate of C. vulgaris compared to coal in this temperature interval (as shown in Fig. 1b). To investigate the degree and variation of the influence of the interaction on thermal decomposition directly, DW is introduced as follows (Zhou et al., 2006):

DW ¼ W practical  W calculated

ð16Þ

where DW is the weight difference that can be assumed as an indicator of the degree of interaction existing between solid phases. The relationship of DW and temperature is presented in Fig. 2d. It can be found that for either MCR, DW is less than 3 wt.% below 320 °C, which is not big enough to indicate the occurrence of interaction between the solid phases of CCB and suggests that the thermal decomposition of coal does not occur within this temperature interval; however, it has never been equal to zero in all sets of experiment, which most likely roots in experimental errors introduced by initial weight and thermal conductivity, etc. (Zhou et al., 2006). From 320 to 550 °C, DW is less than 5 wt.% and rises with temperature increasing; above 550 °C, it continuously rises but undergo an abrupt variation along the temperature coordinate. Eventually (at 1000 °C), DW reaches at 22.948, 18.587 and 10.329 wt.% corresponding to the MCR of 3/7, 5/5, and 7/3. Obviously, a larger MCR is about to bring a smaller deviation (DW)

between Wpractical and Wcalculated. Besides, at any MCR, it can be properly deemed that the inhibition effect of interaction on thermal decomposition is intensified with the temperature increasing, especially above 550 °C. The inhibitive effect and variation of DW can be explained by the following reaction mechanism: around 550 °C, the C. vulgaris component in CCB is generally decomposed and leaves a great quantity of residue when few coal decomposes, which can be learned from the pure material curves in Fig. 1a; the residues are easy to accumulate on the molecules’ surface of coal, and then they are about to undergo several polymerization and condensation reactions; finally they transform into carbonaceous deposits which block the pores of coal molecule through which the volatile matters generated by coal pyrolizing (especially occurs above 550 °C) are driven out, and thus hamper the thermal decomposition of coal. A same reaction mechanism was reported for the co-pyrolysis of sugar cane bagasse and petroleum residue (Darmstadt et al., 2001). As mentioned before, DW generally decreases with increased MCR at b = 20 °C min1, and among the selected MCRs, 7/3 presents the smallest DW. This result can be generalized towards the other heating rates (b = 10 °C min1 and b = 40 °C min1) because of the faster decomposition rate of C. vulgaris and the reaction mechanism expressed at last paragraph. Thus, MCR = 7/3 is taken into investigation to find out if any interaction still exists at other heating rates. The values of Wcalculated and Wpractical at b = 10 or 40 °C min1can be found in Fig. 2e or f, in either of which their TG curves are also different from one and another. In this case, Wpractical is also less than Wcalculated at either b. Though, below 340 °C when b = 10 °C min1 (Fig. 2e) or 270 °C when b = 40 °C min1 (Fig. 2f), the values of Wpractical are close to those of Wcalculated, the deviation between them becomes clear and increases with increased temperature. At around 990 °C, the Wpractical is less by 12.79% and 11.62% than Wcalculated at b = 10 and 40 °C min1. So the interaction between the solid phases of CCB still presents an inhibitive effect on thermal decomposition. 3.3. Effect of blending ratio At a fixed temperature, as shown in Fig. 1a, the increasing MCR decreases the MR of CCB. At the terminated temperature of pyrolysis

C. Chen et al. / Bioresource Technology 117 (2012) 264–273

a

b

c

d

e

f

269

Fig. 2. (a–c) Comparison between TG profiles practical and calculated at b = 20 °C min1; (d) variation of DW versus temperature at b = 20 °C min1; (e and f) Comparison between TG profiles practical and calculated at b = 10, 40 °C min1with MCR = 7/3.

process (1000 °C), the mass achieves 53 wt.% at MCR = 3/7; it is smaller (46.09 and 35.26 wt.%) at higher MCR (5/5 and 7/3); for pure C. vulgaris, the amount can even achieve 21.04 wt.%. The phenomenon indicates that the decomposition of fixed carbon of CCB gets harder as the MCR decreases. In other words, an increasing MR would be observed when MCR gets lower in this co-pyrolysis process (Vuthaluru, 2004). For the weight loss rate, as shown by the vertical coordinate in Fig. 1b, the increasing MCR increases the maximum value (Dmax) over the experiment temperature interval. The phenomenon is probably resulted from the enhancement of volatile matters release, which complies with the research reported by Kastanaki et al. (2002). Comparing the DTG profiles of CCB, a higher peak and a lower peak are presented in each with similar shape, and the lower one is about to disappear with the increasing MCR. Furthermore, the profiles of CCB and pure C. vulgaris become increasingly similar as the MCR increases. As shown in Table 3, TIn, Tmax

and TF of CCB tend to decline as MCR gets larger and the weight loss amount at the DTG peak (the maximum rate) gets bigger with

Fig. 3. DTG profiles for MCR = 5/5 at several bs.

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

the increasing MCR. Besides, the relationship between DA and the mass fraction of C. vulgaris in CCB is almost linear (correlation coefficient R2 = 0.99797). 3.4. Effect of heating rate The DTG profile of MCR = 5/5 at several bs (10, 20 and 40 °C min1) shown in Fig. 3 is taken into consideration for investigation. When the b increases from 10 to 40 °C min1, a considerable variation of the profiles could be observed: a lateral translation of the peaks towards the positive side of the horizontal (temperature) coordinate axis, which occurs commonly for many fuels (Haykiri-Acma et al., 2006; Peng et al., 2001; Scott et al., 2006; Shuping et al., 2010). From the observation, it can be assumed that an increasing b tends to slightly postpone the thermal decomposition process of CCB. In addition, from Fig. 3, it is found that Dmax increases with the increasing b, which is probably resulted from a mechanism: to achieve certain ambient temperature, the higher b takes a shorter time, which leads a relative larger temperature difference between the ambient (or surface) and the core of a particle due to the uninstantaneous thermal conduction physical property of the samples, and thus it definitely facilitates the heat transfer from the ambient (or surface) to the core (Maiti et al., 2007; Park et al., 2009). 3.5. Kinetics analysis For kinetics investigation, the second stage pyrolysis process of CCB is taken into concern, and that of pure C. vulgaris is also investigated as control group in this section.

According to Eqs. (9) and (10), these E values calculated at b = 10, 20, and 40 °C min1 with selected values of a (0.2 6 a 6 0.8) are listed in Table 4. As shown in Fig. 4, it can be observed that: the R2 of all curves are within the narrow interval of 0.92039–0.99999, which means that the points are fitted well; most of the E value deviations between the two methods are within 5% of the lower value. So, it is properly assumed that the results are acceptable. Relationship between E and a summarized from Table 4 is presented by curves in Fig. 5. It is found that within a = 0.2–0.8, the values of E exhibit a great dispersion without any clear trends. For different MCR, the E averages are from 320.77 to 416.01 kJ mol1 by KAS and from 312.89 to 421.19 kJ mol1 by FWO, as shown in Table 4. The increasing MCR leads the E a decrease at first and an increase followed on. In general, a reaction with higher E needs a higher reaction temperature or longer reaction duration; either of them could give the reaction adequate energy as needed. It might suggest that the E of CCB is influenced by MCR and reaction temperature interval. The E average of pure C. vulgaris is 335.69 kJ mol1 by KAS and 329.51 kJ mol1 by FWO, and the mean (332.60 kJ mol1) of them, is close to the mean (316.83 kJ mol1) of two methods at MCR = 5/5 but much higher than that of C. protothecoides (42.2–52.5 kJ mol1) (Peng et al., 2001). The differences might caused by the influence of composition of biomass species on thermal behaviors and the difference of b unit for E determination – K s1 here and K min1 in (Peng et al., 2001). Furthermore, among similar species of biomass, a great difference of pyrolysis kinetics also occurs in certain research (Shuping et al., 2010). At MCR = 5/5, E attains the minimum (316.83 kJ mol1of the mean). Therefore, MCR = 5/5 is potentially an optimal option in co-pyrolysis. With respect to the co-pyrolysis of wheat straw and

Table 4 The E values at b = 10, 20, 40 °C min1 by KAS and FWO. Samples

a

KAS method

FWO method

E (kJ mol1)

R2

E (kJ mol1)

R2

C. vulgaris/coal = 3/7

0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

280.16 360.5 360.84 361.23 562.7 422.24 564.37 416.01

0.99999 0.96411 0.96403 0.96394 0.99999 0.94868 0.99999 –

295.1 347.3 318.01 371.6 516.62 513.73 586 421.19

0.99791 0.96948 0.99024 0.93781 0.99894 0.99529 0.99196 –

C. vulgaris/coal = 5/5

0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

256.30 278.21 278.38 357.74 357.97 358.23 358.53 320.77

0.92039 0.99997 0.99997 0.96201 0.96185 0.96166 0.96146 –

240.95 273.74 297.70 323.93 351.62 378.68 323.61 312.89

0.95321 0.99999 0.99735 0.98716 0.96503 0.92459 0.98734 –

C. vulgaris/coal = 7/3

0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

280.36 360.75 361.07 361.42 361.8 563.45 564.17 407.57

0.99999 0.96429 0.96427 0.96431 0.96433 0.99999 0.99999 –

274.02 352.31 352.31 352.31 352.31 548.04 548.04 397.05

0.99999 0.96429 0.96429 0.96429 0.96429 0.99999 0.99999 –

C. vulgaris

0.2 0.3 0.4 0.5 0.6 0.7 0.8 Average

256.61 256.82 278.83 279.1 358.92 359.34 560.19 335.69

0.92072 0.92071 0.99998 0.99998 0.9626 0.96259 0.99998 –

252.94 252.94 274.02 274.02 352.31 352.31 548.04 329.51

0.92308 0.92308 0.99999 0.99999 0.96429 0.96429 0.99999 –

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

a

b

c

d

Fig. 4. (a) Linear correlation for ln (b/T2) and 1/T at MCR = 5/5 with several a; (b) linear correlation for ln b and 1/T at MCR = 5/5 with several a; (c) linear correlation for ln (b/ T2) and 1/T of pure C. vulgaris with several a; and (d) Linear correlation for ln b and 1/T of pure C. vulgaris with several a.

a

600

500

MCR=3/7 MCR=5/5 MCR=7/3 pure Chlorella vulgaris

600 550

E( kJ· mol -1)

E( kJ· mol-1)

b

MCR=3/7 MCR=5/5 MCR=7/3 pure Chlorella vulgaris

550

450 400 350 300

500 450 400 350 300

250

250 0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.2

0.3

0.4

0.5

0.6

0.7

0.8

¢

α

Fig. 5. Variation profiles of E versus a at several MCRs; (a) by KAS (b) by FWO.

coal, 50 wt.% of each has already proven to be the optimum by Vuthaluru (2004). Using the average value of E calculated by KAS and FWO method, along with the temperature measured as a function of selected a, P(u) can be obtained directly by calculation according to Eq. (12). Fig. 6a and b are the experimental master-plots of P(u)/P(u0.5) against a at b = 10, 20, and 40 °C min1 for C. vulgaris and MCR = 5/5. It is found that the experimental master-plots of different heating rates are practically identical, which may suggest that the kinetic degradation process of C. vulgaris and CCB could be described by a single kinetic model. Plots of g(a)/g(0.5) against a according to theoretical masterplots for several kinetic functions (Table 2) and P(u)/P(u0.5) against a according to experimental data (C. vulgaris and MCR = 5/5) obtained at b = 10 °C min1 are presented in Fig. 6c. The comparison between the theoretical and experimental results indicates that current theoretical master-plots could not match the experimental ones. However, the experimental master-plots are close the

theoretical master-plots F2 and F3. In order to determine whether the Fn model match the experimental data, Plots of g(a)/g(0.5) against a at n = 4, 5 10 and 15 using Fn model and P(u)/P(u0.5) against a according to experimental data (C. vulgaris and MCR = 5/5) are figured out in Fig. 6d. It is found that the experimental master-plots lay between the theoretical master plots F5 and F10. The results can be assumed that Fn model, g(a) = [(1  a)1n  1]/(n  1) describes the kinetic process for thermal decomposition of C. vulgaris and CCB. The accommodated Fn model with a non-integral exponent n was used for estimating the n and A. The expression of Fn is introduced into Eq. (11), and then Eq. (17) is obtained as follows:

gðaÞ ¼

AE ð1  aÞ1n  1 PðuÞ ¼ bR n1

ð17Þ

To obtain a relatively optimal value of n, it is investigated from 0.1 to 15 with the increment of 0.1 and a plot [(1  a)1n  1]/ (n  1) versus EP(u)/bR by linear least-square fitting procedure is

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C. Chen et al. / Bioresource Technology 117 (2012) 264–273

a

b

d

c

Fig. 6. Plots of P(u)/P(u0.5) versus a for (a) pure C. vulgaris and (b) MCR = 5/5; (c) theoretical master-plots of g(a)/g(0.5) against a and experimental master-plots of P(u)/P(u0.5) against a (pure C. vulgaris and MCR = 5/5) at b = 10 °C min1; (d) theoretical Fn model of g(a)/g(0.5) against a and experimental master-plots of P(u)/P(u0.5) against a (pure C. vulgaris and MCR = 5/5) at b = 10 °C min1.

Samples

b

R2

n

A (s1)

A (s1) Average value

C. vulgaris

10 20 40 10 20 40 10 20 40 10 20 40

0.999998 0.999997 0.999997 0.999999 0.999998 0.999997 0.999976 0.999959 0.999959 0.999995 0.999988 0.999982

9

9.30  1027 1.20  1028 9.69  1027 5.81  1033 1.02  1034 8.93  1033 5.50  1026 7.25  1026 6.11  1026 6.76  1033 8.20  1033 7.95  1033

1.03  1028

its thermal decomposition; The increasing MCR decreases WR, TIn, T1, T2 and TF, but increases DA and Mmax; E values at several MCRs are 320.77–416.01 kJ mol1 by KAS and 312.89–421.19 kJ mol1 by FWO, attaining the minimum at MCR = 5/5, and n = 9–11 and A = 6.29  1026–8.30  1033 by master-plots method.

8.30  1033

Acknowledgements

Table 5 n and A obtained at b = 10, 20, 40 °C min1 by master-plots method.

C. vulgaris/coal = 3/7

C. vulgaris/coal = 5/5

C. vulgaris/coal = 7/3

11

9

10

6.29  1026

7.64  1033

This work is supported by the National Basic Research Program of China (973 Program): 2011CB201500, Guangdong Key Laboratory of Clean Energy Technology (2008A060301002) and the Fundamental Research Funds for the Central Universities, SCUT (No. x2dl-D2105280). References

utilized. The most preferable n is the value for which the intercept is closest to zero and R2 is the highest. The highest R2 at different bs, the most probable value of n and corresponding A is shown in Table 5. Results are n = 9, 11, 9, 10 and A = 1.03  1028, 8.30  1033, 6.29  1026, 7.64  1033 for pure C. vulgar and CCBs at MCR = 3/7, 5/5, 7/3, respectively.

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