Kinetic analysis of pyrolysis and combustion of the olive tree pruning by chemical fractionation

Accepted Manuscript Kinetic analysis of pyrolysis and combustion of the olive tree pruning by chemical fractionation A. Pérez, M.A. Martín-Lara, A. Gálvez-Pérez, M. Calero, A. Ronda PII: DOI: Reference:

S0960-8524(17)31864-3 https://doi.org/10.1016/j.biortech.2017.10.045 BITE 19086

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Bioresource Technology

Please cite this article as: Pérez, A., Martín-Lara, M.A., Gálvez-Pérez, A., Calero, M., Ronda, A., Kinetic analysis of pyrolysis and combustion of the olive tree pruning by chemical fractionation, Bioresource Technology (2017), doi: https://doi.org/10.1016/j.biortech.2017.10.045

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Kinetic analysis of pyrolysis and combustion of the olive tree pruning by chemical fractionation P´erez, A., Mart´ın-Lara, M.A., G´alvez-P´erez, A., Calero, M., Ronda, A.* Department of Chemical Engineering, Avenida Fuentenueva s/n. University of Granada 18071 , Granada (Spain)

Abstract This paper presents a kinetic analysis of thermal decomposition of olive tree pruning from its basic compounds in pyrolysis and combustion reactions. Experiments were performed by TGA under inert and oxidant conditions and results indicated that the decomposition of the olive tree pruning was related to the material composition. Pseudo-mechanistic models were proposed estimating the yield of pyrolysis on its basic compounds (hemicelluloses, cellulose and lignin). Validity and reliability of the proposed kinetic models were verified by the good fitting between the simulated and experimental curves (with values of R2 higher than 0.99 in most cases). Moreover, during the fractionation process, an acid fraction was obtained with great fuel properties, a high calorific value and a low residue after its combustion. Keywords: Chemical Fractionation, Combustion, Olive tree pruning, Pyrolysis, Thermogravimetric analysis, Valorization

∗

[email protected]

Preprint submitted to Bioresource Technology

October 13, 2017

1

1. Introduction

2

Nowadays, the biomass materials are being studied to be used in several

3

applications due to their characteristics. Such as, in energy generation pro-

4

cesses (combustion, gasification and pyrolysis), in the obtaining of derivative

5

products (ethanol, methane, bio-oil, and char), etc. (Li et al., 2015; Soria-

6

Verdugo et al., 2015; Madanayake et al., 2017). Vegetal biomass is mainly

7

composed by three organic polymers: hemicellulose, cellulose and lignin; as

8

well as low moisture, extractives, and mineral matter contents (P´erez et al.,

9

2002). The extractives may be inorganic material, non-structural sugars,

10

chlorophyll, waxes and minor components (Rueda-Ord´on ˜ez and Tannous,

11

2015). So, the characteristic of a specific biomass depends on relative pro-

12

portions of each organic polymers class present in it, as they have different

13

physical and thermochemical behaviors (Madanayake et al., 2017).

14

Alternative and clean energies are composed mainly by solar technology,

15

wind power, and lignocellulosic biomass processes (pyrolysis, combustion and

16

gasification). Therefore, the use of lignocellulosic biomass can be an interest-

17

ing process to obtain high quantities of energy in the form of heat (Rueda-

18

Ord´on ˜ez and Tannous, 2016; Morin et al., 2017). Authors as, Quan et al.

19

(2016) studied the pyrolysis of biomass components in a thermogravimetric

20

analyzer and a fixed-bed reactor, to characterize pyrolysis behavior of the

21

studied materials. Therefore, some researchers considered that pyrolysis of

22

biomass can be represented as a simple superposition of their main compo-

23

nents. Wu et al. (2015) studied the kinetic of pyrolysis and combustion of

24

tobacco waste and they related the obtained results with their composition.

25

Mart´ın-Lara et al. (2016) investigated the kinetic pyrolysis of the pine cone 2

26

shell using a three independent parallel reactions mechanistic model. Even,

27

authors obtained in a previous work a simpler model for the study of the

28

thermal decomposition of olive tree pruning by thermogravimetric analysis

29

(Almendros et al., 2017). However, chemical fractionation of the biomass

30

material for the formulation of the realistic kinetic models of pyrolysis and

31

combustion based on thermal decomposition of each obtained fraction are

32

still missing in the literature.

33

Spain is the world-leading of olive oil production. Only, Andalusia main-

34

tains an area of almost constant cultivation that reaches 1,500,000 hectares

35

of olive groves approximately. Besides, pruning of olive trees is made every

36

2 years with a production of around 6 ton per hectare, producing around

37

3,000,000 tons of olive tree pruning waste each two years (Lapuerta et al.,

38

2007). Therefore, utilization of the olive tree pruning for the waste-to-

39

bioenergy generation could be a sustainable choice since it is considered a

40

zero-cost feedstock (Soria-Verdugo et al., 2015; Negro et al., 2015; Almen-

41

dros et al., 2017). In addition, this crop and its derived industries generate

42

a series of by-products with an important energetic content. By means of

43

a suitable technology, it can obtain from them as much thermal energy as

44

electrical and even biofuels for the transport. The by-products susceptible to

45

energy recovery are pomace, orujillo, olive stone, olive leaf and olive pruning

46

(Almendros et al., 2017; Calero et al., 2013).

47

Biomass obtained by pruning of olive trees is an abundant and renew-

48

able agricultural residue in the areas where these groves exist (mainly in the

49

Mediterranean countries) (Calero et al., 2013). Despite the large amount

50

generated annually of these waste, they present a low level of utilization as

3

51

fuel. The main disadvantages to be used are the low bulk density, the high

52

dispersion over a large area and the lack of knowledge in its kinetic process

53

(Garc´ıa-Maraver et al., 2015). Therefore, no industrial applications were yet

54

consistently envisaged and they are usually eliminated by either burning or

55

grinding and scattering on fields, which cause economic cost and environ-

56

mental concerns. In this point, a deeply study concerning the kinetics and

57

the yield of the thermochemical processes of the biomass is important for the

58

design and efficient operation of combustion systems that are fully adapted

59

to the biomass of each region (Garc´ıa-Maraver et al., 2015; Niu and Liu,

60

2015).

61

In this work, the kinetics of the pyrolysis and the combustion of the olive

62

pruning and its fractions were studied, in order to obtain the most ade-

63

quately kinetic models that predict its potential for the production of bioen-

64

ergy. These models were developed from thermogravimetric experimental

65

data of each obtained fraction of the material. Therefore, a more reliable

66

model for each process (pyrolysis and combustion) was obtained based on

67

the fractionation of the waste.

68

2. Materials and Methods

69

2.1. Raw material

70

The olive tree pruning (OTP) is a waste from olive pruning, routinely

71

practiced for maintenance and reshaping of olive trees. The employed OTP

72

was collected from a local plantation in Jaen (Spain). It was cut into a

73

workable length and then, in laboratory it was milled with an analytical mill

74

(IKA MF-10) and the fraction with particle size below 1 mm was selected to 4

75

this study.

76

2.2. Characterization of the waste

77

It the laboratory, samples were prepared by means of homogenization,

78

grinding and drying. The selected materials were characterized according to

79

the standard methods presented at following:

80

1. Moisture content: ISO 18134-3:2015

81

2. Volatile matter: ISO 18123:2015

82

3. Ashes percentage: ISO 18122:2015

83

4. Fixed carbon: by difference

84

5. Calorific value: EN 14918:2009

85

2.3. Chemical fractionation of OTP to isolate its main compounds

86

The main compounds of the OTP were isolated in order to study the

87

kinetic of the pyrolysis and combustion of each component and to propose the

88

most adequate kinetic models that predict the potential for the production

89

from bioenergy of the solid. The chemical fractionation was performed by

90

several consecutive steps:

91

I. Extraction of hot water soluble compounds (TAPPI T 257). An amount

92

of 10 g of the sample was mixed with 500 mL of hot water at 80 ◦ C. It

93

was maintained in contact during 3 h, keeping a constant temperature

94

of 100 ◦ C, shaking periodically. Then, the sample was filtered in a

95

calibrated plate of number 2. Finally, the sample was dried during 24

96

h and weighed to obtain the yield of process.

5

97

II. Extraction of ethanol-benzene compounds (TAPPI T 204). An amount

98

of approximately 20 g of the hot water extracts free sample was placed

99

in a cartridge with filter paper and it was inserted in a Soxhlet extractor

100

with ground glass mouth Erlenmeyer flask. A mix of ethanol-benzene

101

(1:2) was added to perform extractions. This step process was finished

102

when any coloration was appreciated in the siphon. The flask (previ-

103

ously weighed) was dried and weighed and then, the difference in the

104

weigh was the extract content.

105

III. Extraction of lignin (TAPPI T 222). To obtain the lignin content an

106

acid hydrolysis with H2 SO4 was performed. An amount of 1 g of the

107

free extractive sample was placed in a beaker with 15 mL of concentrate

108

sulphuryc acid (72 %) during 2 hours. Later, sample was transferred to

109

a flask and a total volume of 600 mL was completed with water. It is

110

refluxed during 4 hours. Finally, the sample was filtered in a calibrated

111

plate of number 3, then, it was dried during 24 h and the obtained

112

sample was weighed.

113

IV. Extraction of holocellulose (Wise et al., 1946). Holocellulose content

114

was determined by an oxidant hydrolysis with Cl2 . An amount of 5

115

g approximately of the free extractive sample was placed in an Erlen-

116

meyer and 160 mL of water was added. It was heated to 75-80 ◦ C in a

117

bath and later, 1.5 g of sodium chlorite and 10 drops of concentrated

118

glacial ethical acid were added. Sample was stirred and each hour was

119

added a treatment until a total of three. Finally, it was cooled with

120

ice and filtered in a calibrated plate of number 2. It was dried during

121

24 h and obtained sample was weighed. Due to the holocellulose was

6

122

mainly composed of cellulose and hemicellulose, these fractions were

123

also determined.

124

• Cellulose (TAPPI T 203): An amount of 3 g of the holocellulose

125

sample was placed in a beaker heated to 20 ◦ C in a bath, and later

126

a total of 75 mL of NaOH at 17,5 % was added in eight steps: (1)

127

15 mL and 1 min. of stirring, (2) 10 mL and 45 sec. of stirring,

128

(3) 10 mL and 15 sec. of stirring, (4) 1 min. of letting rest, (5) 10

129

mL and 2.5 min. of stirring, (6) 10 mL and 2.5 min. of stirring,

130

(7) 10 mL and 2.5 min. of stirring and (8) 10 mL and 2.5 min.

131

of stirring. Then, 100 mL of water were added and the mix was

132

energetically stirred. Finally, after waiting 30 min., the solid was

133

filtered in a calibrated plate of number 2 and the obtained sample

134

was weighed.

135

136

137

• Hemicellulose: the hemicellulose content was obtained by difference between the holocellulose and the cellulose fractions. 2.4. Thermochemical experiments and model formulation

138

Runs for the pyrolysis and the combustion were carried out into a Perkin

139

Elmer thermobalance model STA 6000. Dynamic experiments were carried

140

out under heating rate of 10 ◦ C·min−1 , from 140 ◦ C (413 K) up to 800 ◦ C

141

(1073 K). The flow rate of the carrier gas was 20 mL·min−1 (high-purity N2 for

142

the pyrolysis tests and a mix of 79 % of N2 and 21 % of O2 for combustion

143

tests). The weight of all samples was approximately 40 mg. Experiments

144

were performed in TGA by triple and the average value was used directly for

145

the performance of the experimental data in the respective curves. Therefore, 7

146

for the modeling of these curves, the average value was used. In this study

147

only one heating rate was selected. Since previous study showed that the

148

heating rate slightly affected to the obtained curves, without significative

149

variations (Soria-Verdugo et al., 2015; Aboulkas et al., 2009). Moreover, the

150

kinetic model selected can be adjusted using one heating rate value and the

151

aim of this study was not the study of the effect of heating rates onto the

152

thermal model. Therefore, an average value of heating rate according to

153

literature was chosen for all tests (Font et al., 2009b,a; Kim et al., 2010;

154

White et al., 2011; Gai et al., 2013; Quan et al., 2016).

155

2.4.1. Pyrolysis model

156

The kinetic model for pyrolysis rate was related to the olive tree pruning

157

biomass composition, in order to set up a model useful for this material.

158

Hence, it was considered that the biomass was formed by three independent

159

fractions (hemicellulose, cellulose and lignin), which exhibit great differences

160

due to their chemical structure. Therefore, it can be considered that they

161

follow independent reactions, which can be expressed as following:

s1 · solid1 −→ v1 · volatile1 + c1 · carbonaceous solid1

(1)

s2 · solid2 −→ v2 · volatile2 + c2 · carbonaceous solid2

(2)

s3 · solid3 −→ v3 · volatile3 + c3 · carbonaceous solid3

(3)

162

where solidi is referred to each fraction of the OTP (hemicellulose, cellu-

163

lose and lignin), volatilei is referred to gases and volatile compounds formed, 8

164

carbonaceous solidi is referred to the carbon residue which remains after the

165

reaction (it is mainly formed by char and ashes), si is referred to the mass

166

of solidi in the OTP, vi is referred to the yield coefficient of volatile (the

167

maximum amount of volatiles that can be obtained by means of the corre-

168

sponding reaction when the reagent reacts completely) and ci is referred to

169

the maximum amount of obtained carbon residue. Besides, coefficients vi

170

and ci are related by the following equation:

ci = 1 − vi

(4)

171

Then, conversion degree is introduced to facilitate the model description,

172

as the ratio between the mass fraction of volatiles obtained at any time and

173

the corresponding yield coefficient:

αi =

176

177

(5)

where Vi is the mass fraction of volatiles obtained at any time by reaction

174

175

Vi vi

i. The kinetic equation for each independent reaction is defined as a nth order reaction as follows: dαi = ki · (1 − αi )ni dt

(6)

178

It is observed that the kinetic constants are independent of the composi-

179

tion of each fraction in the original solid. Moreover, they follow the Arrhenius

180

equation: Ei

ki = ki0 · e− R·T 9

(7)

181

182

The Vtotal (total volatile fraction) and the wcal (total solid fraction) are related to other variables by the following equations: Vtotal = v1 · α1 + v2 · α2 + v3 · α3

(8)

wcalc = 1 − Vtotal = 1 − (v1 · α1 + v2 · α2 + v3 · α3)

(9)

183

The model variables were obtained using the Solver function of Microsoft

184

Excel by minimizing the difference between experimental values for total solid

185

fraction (wexp ) and calculated ones (wcalc ).

186

2.4.2. Combustion model

187

The proposed kinetic model for the combustion process was based on the

188

pyrolysis one, in which new reactions between the oxygen and each fraction

189

were introduced. Therefore, oxygen was included in the decomposition law.

190

The new reactions can be expressed as following:

s1 · solid1 + O2 −→ v4 · volatile4 + c4 · carbonaceous solid4

(10)

s2 · solid2 + O2 −→ v5 · volatile5 + c5 · carbonaceous solid5

(11)

s3 · solid3 + O2 −→ v6 · volatile6 + c6 · carbonaceous solid6

(12)

191

During these reactions (10 to 12) a carbonaceous solid was produced,

192

which was composed by char and ashes. Therefore, the combustion reactions

193

of the obtained carbonaceous solid had to be considered, but only the char

10

194

fraction of the solid reacted to volatiles compounds. For that, it was supposed

195

that this char decomposed according the same kinetic law.

ci · carbonaceous solidi + O2 −→ vci · volatileci 196

197

(13)

where i = 1, 2, 3, 4, 5 and 6 and vci is referred to the mass fraction obtained from combustion reactions of corresponding carbon residues.

198

Due to that only the char of the carbonaceous solid fraction reacted to

199

volatiles in the reaction 13, the values of conversion degree were lower than

200

1 during modeling (ash fraction remained as solid and did not convert to

201

volatiles) for this reaction.

202

203

Now, the considered conversion degree for the combustion of the carbon residue (αci ) can be expressed as following:

αci =

Vci vci

(14)

204

where Vci is the mass fraction of volatiles obtained at any time from the

205

carbonaceous solidi and vci is the maximum amount of volatile compounds

206

obtained with the competitive reaction. As the reactions 1 and 4, 2 and 5

207

and 3 and 6 are competitive respect to their corresponding solids.

208

Therefore, the kinetic equation for each reaction was as follows: dαci = kci · (αi − αci )nc dt

(15)

209

Besides, to take into account the effect of the oxygen partial pressure in

210

reactions with oxygen, a new term had been added inside the pre-exponential

211

factor. In this way, the pre-exponential factor was constituted by two terms

212

and it can be expressed as follows: 11

0 ki0 = ki0 · (PO2 )bi 213

214

(16)

Finally, the Vtotal (total volatile fraction) and the wcal (total solid fraction) were related to other variables by the following equations: Vtotal = α1 · v1 + α2 · v2 + α3 · v3 + α4 · v4 + α5 · v5 + α6 · v6 +

215

αc1 · vc1 + αc2 · vc2 + αc3 · vc3 + αc4 · vc4 + αc5 · vc5 + αc6 · vc6

(17)

wcalc = 1 − Vtotal

(18)

wcalc = 1 − (α1 · v1 + α2 · v2 + α3 · v3 + α4 · v4 + α5 · v5 + α6 · v6 + 216

αc1 · vc1 + αc2 · vc2 + αc3 · vc3 + αc4 · vc4 + αc5 · vc5 + αc6 · vc6 )

(19)

217

In the same way that for pyrolysis model, the model variables were ob-

218

tained using the Solver function of Microsoft Excel by minimizing the differ-

219

ence between experimental values for total solid fraction (wexp ) and calculated

220

ones (wcalc ).

221

3. Results and Discussions

222

3.1. Characterization

223

Moisture content of the sample was determined and a dried waste sample

224

was obtained for the following analysis. The obtained value (5.78 %) was

225

in the range of similar agricultural waste (Mart´ın-Lara et al., 2013; Campoy

226

et al., 2014). Other important aspect for the characterization of a fuel solid

227

is the ash content (it determines the residue after the combustion process). 12

228

The OTP had a 4.01 % of ashes, indicating a low amount of the residue after

229

the process. Moreover it was also in the same range that obtained by similar

230

waste (Chen et al., 2015; Chen-Jianbiao et al., 2015).

231

The structural composition was obtained by the methodology defined

232

above (section 2.3). The high content in soluble compounds (21.48 % of hot

233

water soluble compounds and 9.72 % of ethanol-benzene soluble compounds)

234

indicated the most negative effect of the landfill disposal of the waste for the

235

environment, which has been taken into account during the manipulation of

236

the solid in contact with water. Besides, it also indicates that the current

237

landfill accumulation has negative effect for the environment. During extrac-

238

tion in hot water, a hydrolysis of polysaccharides into sugars was performed,

239

causing that the minerals, proteins, starchs, tannins, hemicelluloses, etc of

240

the OTP were dissolved. During the extraction with ethanol-benzene, the

241

organic compounds were separated. Hence, the free extractive waste was

242

formed by a 47.23 % of lignin and a 52.77 % of holocellulose compounds. Fi-

243

nally, the holocellulose fraction was composed by 30.45 % of hemicelluloses

244

and 69.55 % of celluloses.

245

Calorific values were obtained and the raw OTP showed a high calorific

246

value of 4081 kcal·kg−1 , an intermediate value between the value obtained for

247

the holocellulose fraction (3244 kcal·kg−1 ) and the lignin one (4998 kcal·kg−1 ).

248

The obtained values are consistent with fractions of the solid and indicated

249

that the OTP presents good properties as fuel.

250

3.2. Pyrolysis and combustion experiments

251

The TG curves represented the weight solid fraction (w) versus the tem-

252

perature. Where the parameter w was defined as the weight fraction of solid 13

253

(including both the carbonaceous solid formed and the unreacted solid) and

254

it represented the ratio between the total mass of solid at any moment with

255

respect to the initial mass of solid. Besides, in these figures, the first stage

256

(until 410 K approximately) had not been considered for the model pro-

257

posed, due to it is corresponding to the moisture of the sample and very

258

light volatiles compounds (Huang et al., 2016; Ronda et al., 2016).

259

The TG curves obtained at a heating rate of 10 ◦ C·min−1 are showed in

260

Figure 1 for the pyrolysis (a-b) and the combustion (c-d) of the OTP. This

261

figure showed that the thermal decomposition of the OTP could be divided

262

into three stages, which may be caused by the pyrolysis and combustion of

263

the hemicellulose, cellulose and lignin.

264

Hence, it was considered that the reactions (pyrolysis and combustion) of

265

the OTP biomass was formed by the reactions of three independent fractions,

266

which can be related with the reaction of their main compounds (hemicel-

267

lulose, cellulose and lignin). Three decomposition steps exhibited great dif-

268

ferences, which were related to the chemical structure of each compounds.

269

Lignin was the component most difficult to decompose and it decomposed

270

slightly over a wide temperature range, with a very low mass loss (a final

271

residue around 41 %, the highest one). However, during its combustion, this

272

fraction was burned completely. It was attributed to its structure, which

273

consists of a complex network of cross-linked aromatic molecules (difficult

274

to decompose and with a high thermal stability (Quan et al., 2016)). How-

275

ever, the holocellulose decomposed mainly between 500 to 673 K and it left

276

a residue around 40 % of the initial mass. Holocellulose was composed by

277

hemicellulose and cellulose. They are complex polymers with a high thermal

14

278

stability. Its degradation consisted of two steps, the first one, around 534

279

K, was representative of the hemicellulose decomposition (which occurred at

280

lower temperature range due to its amorphous and random structure, that

281

had low activation energy) (Quan et al., 2016; Yang et al., 2007; Stefanidis

282

et al., 2014). The second stage, around 598 K, was attributed to cellulose,

283

which was consisted of a long polymer of glucose with a stronger structure.

284

Finally, it was observed that the shape of TG curves for OTP extracts free

285

were very similar to OTP ones, but slightly move up, indicating an unessen-

286

tial the effect of this kind of compounds. Figure 1b showed that the shoulder

287

obtained for the raw OTP around 500-550 K (due to the hemicellulose com-

288

pounds) was higher that obtained by the OTP extracts free, indicating that

289

during the extractions steps some hemicellulose compounds were removed.

290

Nevertheless, they did not affect to the holocellulose content, which was the

291

total polysaccharide fraction (cellulose and hemicellulose) that was obtained

292

by removing the extractives and the lignin from the original natural mate-

293

rial. Obtained curves agree with obtained by other authors for the thermal

294

decomposition of biomass components at the same heating rate (Quan et al.,

295

2016).

296

Then, two models, one for pyrolysis and another for combustion were

297

obtained from modelling data of each fraction. The used methodology was

298

the following:

299

300

301

302

1. The pyrolysis and combustion of the experimental obtained lignin fraction and the modelling data. 2. The pyrolysis and combustion of the experimental obtained holocellulose fraction (hemicellulose and cellulose) and the modelling data. 15

303

304

3. The pyrolysis and combustion of free extractive solid and the modelling data.

305

4. Finally, kinetic parameters of the OTP were obtained from previous

306

obtained data (steps 1 to 3) for pyrolysis and combustion respectively.

307

After each test, data were adjusted and the following parameters were

308

obtained: the pre-exponential constant (k0 , s−1 ), the activation energy (E,

309

kJ/mol), the reaction order (n) and the remaining fraction after the degra-

310

dation process (c). Besides, experimental and calculated model were repre-

311

sented to compare results. Data are showed from a temperature around 410

312

K, due to the previous data correspond to moisture and volatile compounds

313

and they can intervene in the model.

314

To study the combustion, the same methodology that for the pyrolysis

315

was followed, but in this case, also the residue fraction from pyrolysis and

316

combustion were considered in the modelling. For a better understanding,

317

the following remarked have been taken into account:

318

• From the pyrolysis of each studied fraction remained a carbonaceous

319

solid (CS), named CSLP , CSHP and CSCP for residue from the lignin,

320

hemicellulose and cellulose pyrolysis, respectively.

321

322

• The value of CSHP was 0, therefore, none additional reaction was produced from it.

323

• From the combustion of each studied fraction remained a carbonaceous

324

solid, named CSLC , CSHC and CSCC for solid fraction from the lignin,

325

hemicellulose and cellulose combustion, respectively.

16

326

327

• In the same way that for pyrolysis, the value of CSHC was 0, therefore, none additional reaction was produced from it.

328

• The remaining waste (CS) were burned by a combustion reaction.

329

To a better comparison, each fraction reactions has been analyzed in

330

detail in the following sections:

331

3.2.1. Lignin reactions

332

Figure 2 shows the obtained model for the pyrolysis (a) and the combus-

333

tion of the lignin (b). The corresponding kinetic parameters were indicated

334

in Table 1. It was observed that the model fitted the experimental data with

335

a R2 value of 0.9984 and 0.9999 for pyrolysis and combustion, respectively.

336

Small differences in the pyrolysis test from 500 to 600 K, were due to the

337

impurities of the material. The lignin fraction was experimentally obtained

338

in the laboratory by acid digestion (see section 2.3), and this process was

339

not completely effective at 100 %. However, calculated and experimental

340

data were mainly overlap in the combustion test. It was observed that the

341

combustion (Fig. 2b) took place in two step, whereas the pyrolysis (Fig. 2a)

342

in only one.

343

Fig. 2b) showed two peaks differentiated between them around 100 de-

344

grees, which are referred to the combustion of the lignin and the combustion

345

of the formed char respectively. Hence, during the process, a residue form

346

lignin combustion was formed and it was burned mainly from 773 to 973

347

K (the range of the second peak). It was also observed in the Figure 2d),

348

where both peaks were related with the conversion steps for the lignin and

349

the CSLC from combustion, respectively. These results are characteristic of 17

350

waste of pruning forests, and they have been also studied by other authors

351

(Conesa and Domene, 2011; Wu et al., 2015).

352

Besides, the conversion degree of the lignin versus the temperature is

353

showed in Figure 2 (c-d). It indicated that a residue fraction remained after

354

the pyrolytic process. The decomposition zone of lignin could be divided

355

into three stages, where the main decomposition step took place around 634

356

K approximately. The presence of pollutants in the sample caused that the

357

conversion branched off before maximum degradation. Therefore, maximum

358

degradation occurred at lower temperature that the maximum degradation

359

obtained experimentally. It is also observed that the degradation rate was

360

low at the beginning of the reaction and it increased with the temperature.

361

Results agree with obtained for decomposition of the lignin fraction of others

362

similar waste (Rueda-Ord´on ˜ez and Tannous, 2016; Huang et al., 2016). Dur-

363

ing the decomposition in air atmosphere, pyrolysis of lignin took also place,

364

but the combustion reaction was predominant. Moreover, the residues from

365

the lignin pyrolysis (CSLP ) and lignin combustion (CSLC ) were also burned.

366

It is observed that the pyrolysis of this char took place jointly to the lignin,

367

whereas it is combusted at higher temperatures. It is observed a remarkable

368

effect on the reactivity of char during its combustion reaction from the TGA

369

curves, where a fast weight loss occurs in the temperature range (673-1000

370

K), with a Tmax obtained from the DTG curve, of 868 K. The reactivity of

371

char was also observed by other authors (Daood et al., 2010; Tushar et al.,

372

2012).

18

373

3.2.2. Holocellulose reactions

374

During the reactions of thermal degradation of holocellulose, two inde-

375

pendent fractions were decomposed: hemicellulose and cellulose. It was ob-

376

served that cellulose badly fitted to one solid mechanism. Thus, some authors

377

proved that the cellulose followed a degradation in two stages: a fast first one

378

and another slow which occurred at higher temperature (Font et al., 2009b;

379

Chatterjee and Conrad, 1966). Therefore, this fraction was analyzed un-

380

til 673 K, where the hemicellulose degradation occurred completely and the

381

degradation of the cellulose took place only in its fast step. Each one present

382

its kinetic parameters (see Table 2). It was observed that the reaction order

383

for cellulose was higher than for hemicellulose, as well as, the pre-exponential

384

constant and activation energy values. Finally, the remaining hemicellulose

385

fraction was zero, indicating that this fraction was fully decomposed, while

386

for the cellulose, a 0.571 remained after pyrolysis process (until 673 K).

387

Figure 3 showed that obtained model fitted adequately experimental data

388

for both, pyrolysis (a) and combustion (b). It was also observed from the

389

corresponding kinetic parameters (Table 2). Curves for fraction weight were

390

almost completely overlap (with a R2 value of 0.9992), whereas the derivatives

391

curves showed a worse fitting (mainly in the tail of the curve), with a R2 value

392

of 0.9643. The pyrolysis tests showed that the devolatilization process started

393

around 473 K and the maximum weight loss occurred in the range 523-623 K.

394

These intervals agreed with obtained by other authors (Carrier et al., 2011).

395

However, combustion occurred in two steps: the first between 473-650 K

396

and the second one between 670-780 K. At equal that for lignin, during the

397

combustion of hemicellulose and cellulose, pyrolysis of them took also place. 19

398

Moreover, it was observed that the hemicellulose was decomposed completely

399

during the pyrolysis reaction, therefore, the hemicellulose combustion did

400

not occurred, neither any char from it was formed. However, the cellulose

401

reaction was more heterogeneous. It was also observed in the representation

402

of conversion degree (Figure 3 (c-d)).

403

From Figure 3 (c-d) the conversion degrees were analyzed. It was observed

404

that the pyrolytic kinetic of hemicellulose was faster than the cellulose one.

405

Besides, the hemicellulose fraction was completely degraded around 534 K,

406

while a residue fraction remained after cellulose degradation. The lower de-

407

composition temperature range of hemicellulose was attributed to its struc-

408

ture, which was amorphous and random with many branched units. This

409

structure presented weak chemical bonds and therefore, the minimum en-

410

ergy needed to start the decomposition reaction was low. Consequently, this

411

fraction required a lower activation energy value. These values agree with

412

obtained by other authors (Quan et al., 2016; Yang et al., 2007; Stefanidis

413

et al., 2014). During combustion, hemicellulose was also combusted rapidly,

414

whereas the kinetic conversion of cellulose was more complex and four reac-

415

tions happened together. They can be divided in two groups: the combustion

416

and pyrolysis of the main fraction (cellulose), in the same temperature range

417

that hemicellulose pyrolysis, being these three reactions responsible of the

418

first peak observed in the Fig 3d; and combustion of formed carbonaceous

419

solid (CSCP and CSCC ), responsible of the second peak.

420

3.2.3. Reactions of the free extractive compounds sample

421

According to kinetic parameters obtained from previous analysis, the free

422

extractive fraction was fitted. Experimental and calculated data were showed 20

423

in Figure 4 and the corresponding kinetic parameters were indicated in Ta-

424

ble 3. The peaks of each fraction (maximum degradation) were obtained

425

from derivatives curves of Figure 4 a and b for pyrolysis and combustion,

426

respectively. It was observed that both processes follow the trend of the

427

solids separately. During pyrolysis, three solids reacted together, while dur-

428

ing combustion, it was due to the combustion of lignin and cellulose fractions

429

at higher temperature (between 700 and 773 K), also by the combustion of

430

the char of cellulose.

431

Hence, from conversion degrees figures (Figure 4 c to d) it was observed

432

that the peak for hemicellulose was moved rom 534 to 559 K, the peak

433

for cellulose from 598 to 624 K and the peak for lignin from 658 to 757

434

K. It indicated that obtained activation energies were higher than obtained

435

before. Therefore, the fitted was tackled taking into account that kinetics

436

constants would modify and activation energies would be higher for each

437

fraction. Besides, it was considered that the reaction orders and formed waste

438

would be similar (except to cellulose, due to it was analyzed individually only

439

for the fast stage (until 673 K)).

440

Taking into account the above considerations, the proposed model had a

441

R2 value of 0.9994 and a R2 value for the derivative of 0.9687 (see Table 3). It

442

was checked that activation energies increased in all cases: from 77.61 to 118.9

443

kJ·mol−1 for the hemicellulose, from 161.8 to 172.8 kJ·mol−1 for the cellulose

444

and from 83.96 to 86.62 kJ·mol−1 for the lignin. It should be highlighted

445

that degradation for lignin was slower than when it was studied individually.

446

It was related with results obtained by other authors (Beal and Eickner,

447

1970; White et al., 2011), who noted that the lignin began to decompose at

21

448

temperatures that were equivalent to those seen for hemicellulose degradation

449

and it continued to degrade slowly over a very broad temperature range, and

450

consequently, both curves could superimposed.

451

3.2.4. Reactions of the olive tree pruning

452

Finally, based on kinetic parameters obtained from the free extractive

453

sample model, the model for the raw solid (OTP) was obtained. Figure 5

454

showed the experimental and calculated data for the OTP pyrolysis (a) and

455

combustion (b). The small disparities between experimental and calculated

456

model can be due to the highly disparate chemical composition of the studied

457

biomass. Therefore, some authors (White et al., 2011; M¨ uller-Hagedorn et al.,

458

2003) had identified heterogeneity of the biomass coupled with the presence

459

of unrecognized secondary reaction, as main sources of the scatter present

460

in the obtained kinetic values. Values from these fitting were showed in

461

Table 4. Data agreed with the assignment of structural feature of material,

462

a solid make up mainly to holocellulose compounds. In this point, previous

463

studies (White et al., 2011) showed that the pyrolysis and combustion rate

464

was related to the biomass composition.

465

Comparing the degradation degree of the three fractions together (Figure

466

5c-Figure 5d), it was observed that the cellulose had the fastest degrada-

467

tion. The cellulose pyrolysis was focused on a higher temperature and with a

468

lower weight loss rate than hemicellulose (but similar to lignin). Main differ-

469

ence between hemicellulose and cellulose was the structure. Therefore, the

470

cellulose was a long polymer of glucose without branches and a good order

471

and very strong structure and the thermal stability of cellulose was higher.

472

Among these three components, lignin was the most difficult one to decom22

473

pose and its conversion started later than the other fractions. The structure

474

of lignin consisted of a complex network of cross-linked aromatic molecules

475

that were difficult to decompose and therefore have high thermal stability.

476

During combustion, the behavior and reactions observed were the same that

477

for the free extractive compounds sample, indicating the good modeling of

478

data.

479

The kinetic parameters obtained from OTP pyrolysis showed that the

480

highest energy value was obtained for cellulose fraction. Gai et al. (2013)

481

pointed out that the activation energy was related to the minimum energy

482

needed to start a reaction. Therefore, the rupture of chemical bonds present

483

in the cellulose was more difficult, and higher activation energy was required.

484

However, the lignin was the fraction with a higher percentage of waste after

485

pyrolysis process.

486

It was observed that the kinetic model obtained from kinetic parameters

487

for each fraction fitted very well the experimental data. Hence, the rela-

488

tionships among material properties, TGA data and pyrolysis kinetics for

489

the thermal decomposition of the olive tree pruning was significant. Thus,

490

curves obtained of wcal and wexp versus the temperature for the OTP py-

491

rolysis were mainly overlap. Besides, the kinetic analysis and the activation

492

energy depend on the basic compounds which formed the biomass. Conse-

493

quently, the values of activation energy calculated were be closely related to

494

the material properties. The proposed model adjusted better the experimen-

495

tal results than that obtained by other authors for similar materials (Huang

496

et al., 2016). Moreover, the proposed model improved the results obtained

497

in previous works with simpler models in the study of the thermal decompo-

23

498

sition of olive tree pruning via thermogravimetric analysis (Almendros et al.,

499

2017). Finally, obtained results indicated that the studied waste (OTP) was

500

useful as fuel source, due to it presented a high conversion degree.

501

4. Conclusions

502

TGA experiments indicated that the decomposition of the OTP was re-

503

lated to the material composition. Its thermochemical conversion was fitted

504

by estimating the yield on its basic compounds and R2 values were higher

505

than 0.99 in most cases, verifying the validity and reliability of the pro-

506

posed models. For the hemicellulose fraction, only the pyrolysis reaction

507

took placed and the combustion did not occurred. The cellulose followed a

508

double pyrolysis-combustion model, where both reactions competed. Finally,

509

the combustion of lignin and its char, occurred when this fraction was alone,

510

but in the presence of other fractions, the combustion of formed char was

511

weak.

512

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513

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514

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632

Tables

Table 1: Kinetic parameters obtained from the adjustments of the pyrolysis and the combustion of lignin. Process

E, kJ·mol−1

k0 , min−1

n

c

4.000

0.411

R2

R2 der.

0.9984

0.9164

0.9999

0.9856

b

Pyrolysis Lignin pyrolysis

4

2.770 · 10

83.96

Combustion 4

83.96

4.000

0.411

4

61.05

2.146

0.711

CSLP combustion

6

2.675 · 10

40.53

1.003

6.30

CSLC combustion

7.488 · 103

42.53

1.003

5.96

Lignin pyrolysis Lignin combustion

2.770 · 10 2.742 · 10

2.47

Table 2: Kinetic parameters obtained from the adjustments of the pyrolysis and the combustion of holocellulose. Process

k0 , min−1

E, kJ·mol−1

n

c

b

R2

R2 der.

0.9992

0.9643

0.9994

0.9557

Pyrolysis Hemicellulose pyrolysis Cellulose pyrolysis

5

77.61

1.388

0.000

12

161.80

1.500

0.571

1.828 · 10 1.125 · 10

Combustion Hemicellulose pyrolysis

5

1.828 · 10

77.61

1.380

0.000

Cellulose pyrolysis

1.125 · 1012

161.8

1.5

0.571

10

89.58

2.011

0.534

28

172.2

1.783

11.331

1

<1

1.783

7.298

Cellulose combustion CSCP combustion CSCC combustion

1.599 · 10 2.000 · 10

1.665 · 10

31

6.349

Table 3: Kinetic parameters obtained from the adjustments of the pyrolysis and the combustion of extractive free sample. Process

k0 , min−1

E, kJ·mol−1

n

c

b

R2

R2 der.

0.9991

0.9914

0.9997

0.9315

Pyrolysis Hemicellulose pyrolysis Cellulose pyrolysis Lignin pyrolysis

5

81.62

1.388

0.000

12

169.30

0.973

0.028

5

99.57

4.000

0.411

1.827 · 10 1.125 · 10

2.428 · 10

Combustion Hemicellulose pyrolysis

5

1.837 · 10

84.90

1.328

0.000

Cellulose pyrolysis

1.125 · 1012

162.8

0.542

0.022

10

90.28

2.011

0.534

18

172.1

1.697

11.331

18

175.4

1.697

11.339

Lignin pyrolysis

4

2.780 · 10

83.22

4.047

0.409

Lignin combustion

2.664 · 104

64.60

2.146

0.710

6

40.22

1.003

6.30

2

77.00

1.003

5.20

Cellulose combustion CSCP combustion CSCC combustion

CSLP combustion CSLC combustion

1.599 · 10 2.000 · 10

1.000 · 10

2.675 · 10 4.010 · 10

32

6.355

2.46

Table 4: Kinetic parameters obtained from the adjustments of the pyrolysis and the combustion of OTP. Process

E, kJ·mol−1

k0 , min−1

n

c

b

R2

R2 der.

0.9999

0.9933

0.9998

0.9754

Pyrolysis Hemicellulose pyrolysis

5

81.24

1.388

0.000

12

1.827 · 10

Cellulose pyrolysis

1.125 · 10

169.50

0.973

0.028

Lignin pyrolysis

2.428 · 105

99.57

4.000

0.411

Combustion 5

80.93

1.588

0.000

12

165.4

0.542

0.000

Cellulose combustion

10

1.599 · 10

89.85

1.964

0.489

CSCP combustion

2.000 · 1018

171.9

1.697

11.331

CSCC combustion

1.000 · 1018

172.7

1.697

11.339

4

86.92

4.047

0.409

4

64.02

2.146

0.710

6

40.22

1.003

6.30

2

77.00

1.003

5.20

Hemicellulose pyrolysis Cellulose pyrolysis

Lignin pyrolysis Lignin combustion

1.838 · 10 1.125 · 10

2.813 · 10 2.797 · 10

CSLP combustion

2.675 · 10

CSLC combustion

4.009 · 10

33

6.299

2.47

633

Figures

634

Figure Captions

635

Figure 1: Pyrolysis experiments for each fraction: a) w versus temper-

636

ature, b) - dw/dt versus temperature and combustion ones: c) w versus

637

temperature, d) - dw/dt versus temperature.

638

Figure 2: Obtained model for lignin pyrolysis (a) and for lignin com-

639

bustion (b) and the corresponding conversion degree for pyrolysis (c) and

640

combustion (d)

641

Figure 3: Obtained model for holocellulose pyrolysis (a) and for holocel-

642

lulose combustion (b) and the corresponding conversion degree for pyrolysis

643

(c) and combustion (d).

644

Figure 4: Obtained model for free extractive compounds sample pyrol-

645

ysis (a) and for free extractive compounds sample combustion (b) and the

646

corresponding conversion degree for pyrolysis (c) and combustion (d).

647

Figure 5: Obtained model for the OTP pyrolysis (a) and for the OTP

648

combustion (b) and the corresponding conversion degree for pyrolysis (c) and

649

combustion (d).

34

650

Figures

Figure 1: Pyrolysis experiments for each fraction: a) w versus temperature, b) - dw/dt versus temperature and combustion ones: c) w versus temperature, d) - dw/dt versus temperature.

35

a)

b) a)

1.0

0.9

experimental calculated model

W

0.8

0.7

0.6

2D Graph 1

0.5

0.4 473

573

673

773

873

973

b)

- dW/dt min. -1

0.025 experimental calculated model

0.02 0.015 0.01 0.005 0.0 473

573

673

773

873

973

Temperature K

d)a)

1.0

c)

0.9 0.8

Conversion

0.7 0.6

Lignin

0.5 0.4 0.3

2D Graph 3

0.2 0.1 0.0 473

573

673

773

873

b)

973

7.0

- d /dt x 10-4 s -1

6.0 Lignin 5.0 4.0 3.0 2.0 1.0 0.0 473

573

673

773

873

973

Temperature K

Figure 2: Obtained model for lignin pyrolysis (a) and for lignin combustion (b) and the corresponding conversion degree for pyrolysis (c) and combustion (d).

36

a)

b) a)

1.0 0.9

Experimental Calculated model

0.8

W

0.7 0.6 0.5

2D Graph 2

0.4 0.3 423

473

523

573

623

523

573

623

b)

0.06

-dW/dt min.-1

0.05

Experimental Calculated model

0.04 0.03 0.02 0.01 0.0 423

473

673

Temperature K 1.0

c)

d)

0.9 0.8 0.7

Conversion

a)

Hemicellulose Cellulose

0.6 0.5 0.4 0.3

2D Graph 1

0.2 0.1 0.0 423

473

523

573

623

523

573

623

b)

3.0 Hemicellulose Cellulose

d dt x 10-3 s-1

2.5 2.0 1.5 1.0 0.5 0.0 423

473

673

Temperature K

Figure 3: Obtained model for holocellulose pyrolysis (a) and for holocellulose combustion (b) and the corresponding conversion degree for pyrolysis (c) and combustion (d).

37

b)

a)

a)

b)

d)

c)

a)

b)

Figure 4: Obtained model for free extractive compounds sample pyrolysis (a) and for free extractive compounds sample combustion (b) and the corresponding conversion degree for pyrolysis (c) and combustion (d).

38

b)

a)

a)

b)

d)

c)

a)

b)

Figure 5: Obtained model for the OTP pyrolysis (a) and for the OTP combustion (b) and the corresponding conversion degree for pyrolysis (c) and combustion (d).

39

Siguiendo las reglas TAPPI y el método Wise, obtenemos la siguiente composición para la corteza de pino, expresada en porcentaje en la figura 5.18.

TGA

Fitting data of pyrolysis and combustion

Figura 5.18: Composición en Base Seca.

Lignin

Las cenizas terminan en un 3,5% del pino inicial. En la figura 5.19 se

a)

1muestran la lignina, celulosa y cenizas procedentes de la corteza de pino. 38

Figura 5.18: Composición en Base Seca.

Las cenizas terminan en un 3,5% del pino inicial. En la figura 5.19 se

TGA

1muestran la lignina, celulosa y cenizas procedentes de la corteza de pino.

b)

Holocellulose Milled OTP

38

Extractive free OTP

TGA

Kinetic models

Highlights • • • • •

Study of the olive tree pruning pyrolysis and combustion The composition of the solid is the key to model its thermochemical conversion The degradation and combustion of each fraction was related with its structure Lignin was the hardest fraction to decompose and its conversion started later The experimental and modelled data were in good agreement