Physical and chemical characteristics of renewable fuel obtained from pruning residues

Accepted Manuscript Physical and chemical characteristics of renewable fuel obtained from pruning residues

Gianni Picchi, Carolina Lombardini, Luigi Pari, Raffaele Spinelli PII:

S0959-6526(17)32316-8

DOI:

10.1016/j.jclepro.2017.10.025

Reference:

JCLP 10817

To appear in:

Journal of Cleaner Production

Received Date:

16 May 2017

Revised Date:

07 September 2017

Accepted Date:

03 October 2017

Please cite this article as: Gianni Picchi, Carolina Lombardini, Luigi Pari, Raffaele Spinelli, Physical and chemical characteristics of renewable fuel obtained from pruning residues, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2017.10.025

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

Physical and chemical characteristics of renewable fuel obtained from pruning residues

2 3 4

Gianni Picchi

5

CNR-IVALSA

6

Via Madonna del Piano 10

7

I-50019 Sesto Fiorentino (FI), Italy

8

[email protected]

9 10

Carolina Lombardini

11

CNR-IVALSA

12

As above

13

[email protected]

14 15

Luigi Pari

16

CRA-ING

17

Via della Pascolare 16

18

I-00015 Monterotondo Scalo (Roma), Italy

19

[email protected]

20 21

Raffaele Spinelli

22

CNR-IVALSA

23

As above

24

[email protected]

1

ACCEPTED MANUSCRIPT 26

Abstract

27

Wood residues generated from orchard maintenance operations represent a serious disposal

28

problem, as well as a valuable opportunity for the bioenergy sector. However, their widespread use

29

as renewable fuel is hindered by uncertainty about crucial quality issues, such as: ash content, ash

30

melting behavior and chemical composition. This paper investigates the main physical and chemical

31

characteristics of pruning residues generated by five of the most common European orchard crops:

32

vine, olive, apple, pear and hazelnut. The results of the analyses are contrasted with the quality

33

specifications set by EU standard UNI EN 14961-1 2010 for forest residues, in the absence of a

34

standard specifically designed for orchard pruning residues. All tested orchard residues biomasses

35

fulfill set specifications, and they also present similar characteristics in terms of ash content, size

36

distribution and heating value. However, the chemical composition of pear and vine residues may

37

raise some concern, due to the high content of nitrogen of the former, and to the high ash, sulfur and

38

chlorine content of the latter. Olive and hazelnut pruning residues seem the most suitable for direct

39

combustion, probably because the origin crops are cultivated less intensively and receive smaller

40

chemical inputs.

41 42

Keywords

43

Agricultural residues, biomass, fuel quality, heavy metals, pruning

44 45

Highlights

46



We compared the fuel quality of pruning residues of five agricultural crops.

47



Quality parameters were contrasted with the EU standard UNI EN 14961-1 2010.

48



Physical properties of all residues are similar to those of forest residues.

49



The tested biomasses are suitable for combustion in common wood chip facilities.

50



High content of N, Cl and heavy metals may require flue gases abatement systems. 2

ACCEPTED MANUSCRIPT 51

1. Introduction

52

Fruit orchards cover over 10 million hectares across the EU, and are mostly located in Southern and

53

Central European Countries, where they generate substantial wealth while contributing to shape a

54

typical cultural landscape often appreciated for its aesthetic quality. All orchards require regular

55

pruning, which is performed at 1 to 3 years intervals. This operation generates a substantial amount

56

of residues, estimated in the range of 1 to 5 tons per hectare (Magagnotti et al., 2013). Traditionally,

57

pruning residues are disposed through open-air burning, which releases a variety of pollutants

58

(Gonçalves et al., 2011) and represents one of the main sources of CO2 emissions and lead

59

deposition in orchard management (Avraamides and Fatta, 2008). While agricultural burning

60

generates much less air pollution than vehicular traffic (Darley et al., 1966), it produces localized

61

emissions, especially harmful to human health for their high particulate content (Keshtkar and

62

Ashbaugh, 2007). Besides, field burning is labour-intensive and incurs significant cost (Spinelli et

63

al., 2014). In short: the traditional methods for disposing of pruning residues offer very poor results

64

in terms of financial, environmental and social efficiency. Mulching represents a much cleaner

65

solution (Pergola et al., 2017), but it conflicts with the needs for orchard sanitation in the face of

66

increasingly aggressive pests (Jacometti et al., 2007). There is an urgent need to find better ways to

67

dispose of orchard pruning residues, and the biomass energy market seems to be offering a valuable

68

opportunity. However, orchard management includes spraying with a variety of pesticides, which

69

raises the question of chemical contamination (Spinelli et al., 2012). There is a growing concern

70

about the permanence of these chemicals, which may not be completely removed through natural

71

weathering. Recent studies seem to confirm the toxicity impact potential of bioenergy production

72

from pruning residues (Boschiero et al., 2016), and many stakeholders are wondering about how

73

cleaner the energy conversion alternative really is, when dealing with pruning residue disposal. In

74

fact, the energy conversion of orchard pruning residues may follow many different paths, each

75

producing different economic and environmental results. In many regions, concentrated orchard

76

farming offers a logistical advantage when developing a local network of bioenergy facilities 3

ACCEPTED MANUSCRIPT 77

(Delivand et al., 2015) and may result in a much better environmental performance compared with

78

any fossil alternatives (González-García et al., 2014). Eco-efficiency should be used as a main

79

criterion when selecting among different conversion options (Lozano and Lozano, 2017), but raw

80

material characteristics also play an important role because each option implies certain feedstock

81

quality specifications. Reliable information is needed about such crucial feedstock characteristics

82

as: ash content, ash melting behavior and chemical composition. Uncertainty about feedstock

83

quality represents a formidable constrain to actual use, due to the risk for boiler damage or pollutant

84

release (Werther et al., 2000). When dealing with orchard pruning residues it is important to

85

determine the possible presence of pesticides, and its consequences on ash composition and flue gas

86

emissions. Inorganic compounds bound in pesticides – especially heavy metals - may stick to the

87

surface of the residues and increase the content of noxious pollutants in the flue gas or ash,

88

regardless of conversion technology – i.e. direct combustion (Obernberger et al., 2006) or pyrolysis

89

(Stals et al., 2010).

90

Therefore, the goal of this study is to provide reliable information about the physical and chemical

91

characteristics of biomass fuel obtained from the mechanical processing of pruning residues

92

obtained from some of the main orchard crops of the Mediterranean region: olive, vine, apple, pear

93

and hazelnut. The study covered such crucial quality parameters as: water mass fraction, particle

94

size distribution, energy content, ash content, ash melting behavior, elemental composition and

95

heavy metal content. The results were compared with the commercial specification mandated by EN

96

Standard 14961-1 2010 (Solid Biofuels – Fuel Specifications and Classes), which is the official

97

reference for solid biomass fuel at the European level.

98

2. Materials and methods

99

2.1.

Biomass sampling

100

Pruning residues were collected during commercial residue harvesting operations conducted on the

101

selected crops in different areas of Italy. For all treatments, the time lapse between pruning and

102

collection was about 2 weeks. Apple, pear and vine residues were harvested in northern Italy during 4

ACCEPTED MANUSCRIPT 103

February, while hazelnut and olive residues were collected during late April, in Central and

104

Southern Italy.

105

The same machine was deployed in all cases, namely a heavy-duty FACMA TR 140 specifically

106

designed for pruning residue collection, comminution and extraction (figure 1). This machine

107

collected the residues from windrows using a mechanical pick-up device and moved them to a built-

108

in nine-hammer shredder. Shredded residues were thrown into a 3 m3 high-dumping bin lodged in

109

the rear end of the machine. A five cm-mesh screen was placed between the shredder and the

110

container, in order to stop oversize particles and sent them back to the shredder for refining. The

111

screen was installed during all harvests, except for the olive residue harvest, when it had been

112

removed on request of the farm owner. Once the bin was full, the machine drove to the field edge

113

and dumped the shredded residues into a roll-off container. During all harvesters the machine was

114

powered and towed by a special 3-wheeled hydrostatic tractor, with a 62 kW engine. The tractor

115

was specifically designed for orchard operations, and featured low profile, reduced width and

116

narrow turning radius.

117

For each orchard type, researchers visited a representative operation and collected five samples

118

from different bin loads. Because of the exploratory purpose of the present study, the possible effect

119

of variations in tending technique (e.g varietal, pruning type and intensity, soil type, etc.) were not

120

included as additional factors in the experiment. In any case, the sample orchards were chosen to

121

represent the dominant tending systems. Table 1 reports the main characteristics of the sampled

122

orchards, determined through farmers interviews. Orchard types were considered as the treatments

123

(n° 5), and individual samples as the replications (n° 5), so that the study yielded a total of 25

124

samples. Each sample had a fresh weight of 5-7 kg and was collected randomly from different parts

125

of the same load. Samples were sealed in plastic bags and transported to the laboratory for analysis.

126

Among the sampled species olive was the only evergreen tree, while all the others shed their leaves

127

during wintertime, when pruning and residues harvest occurs. Therefore, olive orchard samples

5

ACCEPTED MANUSCRIPT 128

contained a substantial proportion of leaf material, which was generally absent from the other

129

samples.

130

2.2.

Biomass analysis

131

Once in the laboratory, each sample bag was opened, thoroughly mixed and evenly spread on a tray.

132

Subsamples were collected at different parts on the tray. A 500 g subsample was used for water

133

mass fraction determination, conducted according to UNI CEN/TS 15414-2:2010. A second 500 g

134

subsample was used for determining particle-size distribution, according to EN 15149-1:2010. In

135

this instance, researchers used a certified automatic screening device with six sieves, in order to

136

separate the following seven chip length classes: >100 mm, 100–63 mm, 63–45 mm, 45–16 mm,

137

16–8 mm, 8-3.15 mm, <3.15 mm. Sorted particles were weighed with a precision scale. Eventually,

138

particles were grouped in three main fractions: coarse, main and fines. The commercial P63 class

139

for logging residues was used as a reference, and therefore particle size breakdown had to fulfill the

140

following requirements: a) “main fraction” (all particles between 63 and 3.15 mm) should represent

141

at least 75% of sample weight (SW), b) “coarse fraction” (particles longer than 100 mm) should

142

account for no more than 6 % of SW, and c) “fine fraction” (particles smaller than 3.15 mm) should

143

not exceed 25 % of SW.

144

All of the remaining analyses were realized on a subsample of about 200 g for each replication. This

145

was extracted through grab-sampling from different parts of the trays, then thoroughly mixed and

146

finely ground with a Retsch SM 200 metal-free laboratory mill. Sample preparation followed the

147

prescriptions of the “General analysis test sample preparation” standard EN 14780:2011. Biomass

148

ash content was determined in a ventilated furnace oven at 550±10 °C, according to EN ISO

149

18122:2015 standard. Ash melting behavior was determined in a muffle furnace, according to

150

CEN/TS 15370-1:2006 standard. Gross and net calorific values were determined according to EN

151

14918:2009, while elemental analysis (C, H, N) was conducted according to UNI EN 15104:2011.

152

Cl and S concentration was determined with a Metrohm ProfIC Ion chromatographer, according to

153

EN 15289:2011 standard, while the concentration of the remaining elements (K, Na, Cr, Cu, Ni, Pb, 6

ACCEPTED MANUSCRIPT 154

Zn, Mn, Hg, As) was determined on 0.5 g samples according to Method 3052, based on microwave-

155

assisted nitric-perchloric acid digestion of organic matrices (EPA, 1996). The total concentration of

156

heavy metal was determined through inductively-coupled plasma-atomic emissions spectrometry

157

(EPA, 2000), while Na and K concentrations were determined according to the standard method

158

prescribed by ASA-SSSA (Sparks, 1996).

159

Data were analyzed with the free statistic software R (version 2.14.0). The statistical significance of

160

the eventual differences between treatments was checked through ANOVA techniques. Post-hoc

161

tests were conducted with Scheffe’s method, which estimates narrow confidence limits and is most

162

robust against possible violations of the normality assumption.

163

3. Results

164

Table 2 shows the results obtained for water mass fraction and particle size distribution. Water mass

165

fraction is potentially affected by many factors, such as: crop type, time elapsed between pruning

166

and collection, time of the year and weather conditions. The water mass fraction of apple, pear and

167

vine residues was about 45%, instead for hazelnut and olive was about 35%. This difference was

168

due to the different harvesting period. Water mass fraction is reported in this study as a general

169

reference only: differences found for the selected samples may be largely related to harvest time

170

and location, rather than to inherent crop differences.

171

Concerning particle size distribution, significant differences between orchard types were only found

172

in the extreme classes: olive pruning residues contained the highest proportion of coarse particles

173

(11.6%), whereas pear and apple pruning residues presented the largest shares of fines particles

174

(16.8% and 13.8%, respectively). No orchard type differences could be found for the main fraction,

175

with values always around 70-80% (Table 2).

176

Ash content reached a maximum value of 6% in vine residues, and an average of about 4% for the

177

remaining treatments (Figure 2). Statistical analysis confirmed the significance of difference

178

between vine residues and the rest. Melting tests showed that ash from pear residues reached the

179

shrinkage phase at temperatures lower than 900 °C. After that, pear ash maintained a stable 7

ACCEPTED MANUSCRIPT 180

structure until temperatures exceeded 1500 °C, much like hazelnut and olive residue ashes. Apple

181

and vine residues ashes followed a similar pattern, but the shrinkage phase started at higher

182

temperatures (> 1000 °C) than recorded for pear ash and shape alteration was more rapid, leading to

183

the ash flow phase just above 1300 °C (Figure 3).

184

Calorific values ranged from 16,951 kJ kg-1 for vine residues to over 17,300 kJ kg-1 for the

185

remaining treatments (Figure 4). The difference between vine residues and the other materials was

186

statistically significant. Energy content was inversely proportional to ash content. Logically, a high

187

concentration of non-combustible elements must result in a reduction of heating value.

188

Table 3 shows the result of the elemental analysis, highlighting the concentration of nutrient

189

elements that can be regarded as polluting and/or potentially corrosive during combustion. With the

190

exception of sulfur, significant differences among the treatments can be found for all elements.

191

Nitrogen was found at concentrations higher than 0.60 %. The highest nitrogen concentration was

192

found in pear pruning residues, and this difference was statistically significant. Olive pruning

193

residues had very high concentrations of Na and K, probably due to the fact that they contained a

194

significant leaf portion. Chlorine concentration varied widely, from a minimum of 0.02% in pear

195

and apple pruning residues, to a maximum 0.06 % in vine residues.

196

Heavy metals such as Cr, Hg and As were below detection limits. All the remaining metals were

197

present is significantly different concentrations depending on orchard type (Table 4). Pear residues

198

presented the highest concentration of Cu and Zn, while vine residues showed the highest

199

concentrations of Ni and Pb. Hazelnut residues contained a significantly higher Mn concentration

200

compared with the others.

201

4. Discussion

202

In order to define the suitability of the analyzed biomass to possible market uses, the quality

203

parameters recorded in the study where checked against the fuel specifications issued by standard

204

EN ISO 17225-1:2014. However, this standard does not include ad-hoc specifications for fuel

205

derived from agricultural wood residues. Therefore, the specifications for “Logging Residue Chips 8

ACCEPTED MANUSCRIPT 206

from Broad-Leaf Wood” of the same standard were adopted as the reference. In fact, this forest

207

feedstock is the closest approximation to pruning residues, containing a high proportion of twigs,

208

bark and leaves.

209

Comminuted olive, vine and hazelnut residues fulfilled the requirements set for P63 industrial wood

210

chips obtained from logging residues. In contrast, pear and apple residues failed to fulfill such

211

specifications, due to the high content of fine particles. This was probably caused by the machine

212

pick-up collecting part of the dead leaves on the ground, which was particularly abundant in these

213

orchards. In that case, fuel quality could be easily improved by adjusting the machine work settings,

214

in order to increase pick-up height and reduce leaf collection. On a similar note, it could be possible

215

to improve the quality of fuel obtained from olive pruning residues by installing the standard 5 cm

216

mesh screen, which during the tests was removed on demand by the orchard owner. Use of a screen

217

would reduce the proportion of coarse particles, which was especially high in olive pruning fuel.

218

The water mass fraction of pruning residues at the time of harvest was already below the 45%

219

threshold set by industrial users (Spinelli et al., 2011). Under favorable conditions, water mass

220

fraction could be further reduced by interposing additional delay between pruning and harvesting.

221

That would increase the actual heating value of the fuel, and reduce the severity of storage losses.

222

Ash content for all the tested fuels was relatively high when compared to the values reported for

223

forest wood chips (Avelin et al., 2014; Dibdiakova et al., 2015; Olanders and Steenari, 1995), and

224

for biomass from dedicated wood energy crops (Eisenbies et al., 2015; Straker et al., 2015). Yet,

225

recorded values were within the range of variation already found for olive pruning residues and

226

Mediterranean forest species (Zamorano et al., 2011). It is known that the use of different

227

harvesting techniques and equipment may have a strong effect on ash content, as the result of

228

different levels of soil contamination (Bonner et al., 2014). In the present study both the three wheel

229

prime mover (a specialized orchard tractor) and possibly the aggressive setting of the pickup system

230

could be the reason for a relatively high soil contamination. Fortunately, the ash found in all tested

231

biomass were quite stable during combustion, with a melting point well above expected grate 9

ACCEPTED MANUSCRIPT 232

temperatures. Therefore, their relatively high ash concentration represents a mere problem of

233

efficient removal from under the grate, but it poses no risk of slagging and/or fouling.

234

The lower heating value of all tested fuels was smaller than reported for typical forest fuels obtained

235

from conifer trees (Nurmi and Hillebrand, 2007; Suadicani and Gamborg, 1999), but similar to the

236

figures reported for broadleaved trees (Kauter et al., 2003; Klasnja et al., 2002). In fact, vine

237

residues presented a higher energy content than reported by Telmo and Lousada (2011) for some

238

southern European forest species such as eucalyptus and chestnut, which are commonly used for

239

large scale energy production.

240

The concentration of main structural elements was consistent with the results of other studies

241

conducted on wood chips (Vassilev et al., 2010). However, the concentration of N, Cl and S was

242

above the critical values (respectively 0.6, 0.3 and 0.2 wt %) for unproblematic combustion, which

243

raised concern about corrosion and emissions (Obernberger et al., 2006) and require the adoption of

244

appropriate technical solutions such as dry and activated carbon sorption, air/fuel staging and

245

automatic heat exchanger cleaning. Vine pruning residues are especially worrying, because they

246

exceed the thresholds for all three elements. A range of technical solutions are available for boilers

247

that use fuels with high N, Cl and S contents, namely: dry and activated carbon sorption, air/fuel

248

staging and automatic heat exchanger cleaning. The latter solution is especially desirable if the fuel

249

shows high concentration of Na and K, as well.

250

The concentration of heavy metal in the fuel was always within the values reported in standard EN

251

14961-1:2012 Annex B.3 “Typical values for virgin wood materials: logging residues”. Cu

252

concentration is particularly high in pear residues, which may be related to the intensive cropping

253

techniques, together with high share of dead leaf material in the fuel. Nevertheless, Cu

254

concentration is still below dangerous limits, particularly if the low volatility of this metal is

255

considered. Furthermore, a previous study on vine biomass combustion showed that even small

256

scale electrostatic filters (for domestic boilers) can effectively abate the human toxicity potential of

257

heavy metals in the flue gas (Picchi et al., 2013). Thus, it can be assumed that the distribution of 10

ACCEPTED MANUSCRIPT 258

agrochemicals on the crop surface does not alter the residual biomass characteristics to the point of

259

constituting a constrain to its use for energy generation.

260

5. Conclusions

261

All the tested orchard residues can be regarded as a fuel with similar characteristics to those of air-

262

dried forest residues, for what concerns water mass fraction, ash content, particle size distribution

263

and heating value. Chemical composition is within the range of variation reported for forest

264

biomass, especially if such biomass is sourced from hardwood trees. Nevertheless, agrochemical

265

inputs during the cultivation push N, Cl and heavy metal content towards the high end of the range.

266

Furthermore, significant differences can be found among different orchard types, which may affect

267

fuel quality. In particular, pear and vine residues should be used with some caution due to high

268

nitrogen content (pear) or high ash, sulfur and chlorine content (vine). Olive and hazelnut residues

269

are the most suited for direct combustion, because they come from less intensively managed crops

270

and contain lower concentrations of critical compounds.

271

In general, it is safest to feed agricultural residues to high-efficiency large-scale industrial boilers

272

equipped with flue gas filtering systems, in order to control NOx and particulate emissions. It is

273

also advisable to blend agricultural residues with other biomass fuels, such as sawmill or forest

274

residues. The resulting mix would benefit from the low water mass fraction of agricultural residues,

275

while reducing some of its drawbacks, such as the high content of ash and undesired elements.

11

ACCEPTED MANUSCRIPT 277

ACKNOWLEDGEMENTS

278

The study was carried out within the PIBASEM project, funded by the Post-doc Program of the

279

Province of Trento (Italy). The authors also gratefully acknowledge Dr. Beatrice Pezzarossa and

280

Mrs. Irene Rossellini of CNR-ISE for their valuable support in biomass analysis.

281

12

ACCEPTED MANUSCRIPT 283

References

284

Avelin, A., Skvaril, J., Aulin, R., Odlare, M., Dahlquist, E., 2014. Forest biomass for energy

285 286

production - comparison of different forest species. Energy Procedia 61, 1820-1823. Avraamides, M., Fatta, D., 2008. Resource consumption and emissions from olive oil production: a

287

life cycle inventory case study in Cyprus. Journal of Cleaner Production 16, 809–821.

288

doi:10.1016/j.jclepro.2007.04.002

289

Bonner, I.J., Smith, W.A., Einerson, J.J., Kenney, K.L., 2014. Impact of Harvest Equipment on Ash

290

Variability of Baled Corn Stover Biomass for Bioenergy. Bioenergy Research 7, 845–855.

291

doi:10.1007/s12155-014-9432-x

292

Boschiero, M., Cherubini, F., Nati, C., Zerbe, S., 2016. Life cycle assessment of bioenergy

293

production from orchards woody residues in Northern Italy. Journal of Cleaner Production

294

112, 2569–2580. doi:10.1016/j.jclepro.2015.09.094

295

Darley, E., Burleson, F., Mateer, E., Middleton, J., Osterli, V., 1966. Contribution of Burning of

296

Agricultural Wastes to Photochemical Air Pollution. Journal of the Air Pollution Control

297

Association 16, 685–690.

298

Delivand, M.K., Cammerino, A.R.B., Garofalo, P., Monteleone, M., 2015. Optimal locations of

299

bioenergy facilities, biomass spatial availability, logistics costs and GHG (greenhouse gas)

300

emissions: A case study on electricity productions in South Italy. Journal of Cleaner

301

Production. doi:10.1016/j.jclepro.2015.03.018

302 303 304

Dibdiakova, J., Wang, L., Hailong, L., 2015. Characterization of ashes from Pinus sylvestris forest biomass. Energy Procedia 75: 186-191. Eisenbies, M.H., Volk, T.A., Posselius, J., Shi, S., Patel, A., 2015. Quality and Variability of

305

Commercial-Scale Short Rotation Willow Biomass Harvested Using a Single-Pass Cut-and-

306

Chip Forage Harvester. Bioenergy Research 8, 546–559. doi:10.1007/s12155-014-9540-7

307

EPA, 2000. SW-846, Method 6010 C. Trace elements in solution by inductively Coupled Plasma -

308

Atomic Emission Spectroscopy (ICP-AES). 13

ACCEPTED MANUSCRIPT 309 310 311

EPA, 1996. METHOD 3052 MICROWAVEMicrowave assisted acid digestion of siliceous and organically based matrices. Gonçalves, C., Evtyugina, M., Alves, C., Monteiro, C., Pio, C., Tomé, M., 2011. Organic

312

particulate emissions from field burning of garden and agriculture residues. Atmospheric

313

Research 101, 666–680. doi:10.1016/j.atmosres.2011.04.017

314

González-García, S., Dias, A.C., Clermidy, S., Benoist, A., Bellon Maurel, V., Gasol, C.M.,

315

Gabarrell, X., Arroja, L., 2014. Comparative environmental and energy profiles of potential

316

bioenergy production chains in Southern Europe. Journal of Cleaner Production.

317

doi:10.1016/j.jclepro.2014.04.022

318

Jacometti, M.A., Wratten, S.D., Walter, M., 2007. Management of understorey to reduce the

319

primary inoculum of Botrytis cinerea: Enhancing ecosystem services in vineyards. Biological

320

Control 40, 57–64.

321

Kauter, D., Lewandowski, I., Claupein, W., 2003. Quantity and quality of harvestable biomass from

322

Populus short rotation coppice for solid fuel use — a review of the physiological basis and

323

management in uences. Biomass and Bioenergy 24, 411–427.

324

Keshtkar, H., Ashbaugh, L.L., 2007. Size distribution of polycyclic aromatic hydrocarbon

325

particulate emission factors from agricultural burning. Atmospheric Environment 41, 2729–

326

2739. doi:10.1016/j.atmosenv.2006.11.043

327 328 329

Klasnja, B., Kopitovic, S., Orlovic, S., 2002. Wood and bark of some poplar and willow clones as fuelwood. Biomass and Bioenergy 23, 427–432. Lozano, F.J., Lozano, R., 2017. Assessing the potential sustainability benefits of agricultural

330

residues: Biomass conversion to syngas for energy generation or to chemicals production.

331

Journal of Cleaner Production. doi:10.1016/j.jclepro.2017.01.037

332

Magagnotti, N., Pari, L., Picchi, G., Spinelli, R., 2013. Technology alternatives for tapping the

333

pruning residue resource. Bioresource Technology 128, 697–702.

334

doi:10.1016/j.biortech.2012.10.149 14

ACCEPTED MANUSCRIPT 335 336 337 338 339 340 341

Nurmi, J., Hillebrand, K., 2007. The characteristics of whole-tree fuel stocks from silvicultural cleanings and thinnings. Biomass and Bioenergy 31, 381–392. Obernberger, I., Brunner, T., Barnthaler, G., 2006. Chemical properties of solid biofuels— significance and impact. Biomass and Bioenergy 30, 973–982. Olanders, B., Steenari, B., 1995. Characterization of ashes from wood and straw. Biomass and Bioenergy 8, 105–115. Pergola, M., Persiani, A., Pastore, V., Palese, A.M., Arous, A., Celano, G., 2017. A comprehensive

342

Life Cycle Assessment (LCA) of three apricot orchard systems located in Metapontino area

343

(Southern Italy). Journal of Cleaner Production journal. doi:10.1016/j.jclepro.2016.10.030

344

Picchi, G., Silvestri, S., Cristoforetti, A., 2013. Vineyard residues as a fuel for domestic boilers in

345

Trento Province (Italy): Comparison to wood chips and means of polluting emissions control.

346

Fuel 113, 43–49. doi:10.1016/j.fuel.2013.05.058

347 348 349

Sparks, D., 1996. Methods of Soil Analysis. Part. 3. Chemical Methods. SSSA Book Series No 5, Madison, USA. Spinelli, R., Ivorra, L., Magagnotti, N., Picchi, G., 2011. Performance of a mobile mechanical

350

screen to improve the commercial quality of wood chips for energy. Bioresource Technology

351

102, 7366–7370. doi:10.1016/j.biortech.2011.05.002

352

Spinelli, R., Lombardini, C., Pari, L., Sadauskiene, L., 2014. An alternative to field burning of

353

pruning residues in mountain vineyards. Ecological Engineering 70, 212–216.

354

doi:10.1016/j.ecoleng.2014.05.023

355

Spinelli, R., Nati, C., Pari, L., Mescalchin, E., Magagnotti, N., 2012. Production and quality of

356

biomass fuels from mechanized collection and processing of vineyard pruning residues.

357

Applied Energy 89, 374–379. doi:10.1016/j.apenergy.2011.07.049

358

Stals, M., Thijssen, E., Vangronsveld, J., Carleer, R., Schreurs, S., Yperman, J., 2010. Flash

359

pyrolysis of heavy metal contaminated biomass from phytoremediation: Influence of

360

temperature, entrained flow and wood/leaves blended pyrolysis on the behaviour of heavy 15

ACCEPTED MANUSCRIPT 361 362

metals. Journal of Analytical and Applied Pyrolysis 87, 1–7. Straker, K.C., Quinn, L.D., Voigt, T.B., Lee, D.K., Kling, G.J., 2015. Black Locust as a Bioenergy

363

Feedstock: a Review. Bioenergy Research 8, 1117–1135. doi:10.1007/s12155-015-9597-y

364

Suadicani, K., Gamborg, C., 1999. Fuel quality of whole-tree chips from freshly felled and summer

365

dried norway spruce on a poor sandy soil and a rich loamy soil. Biomass and Bioenergy 17,

366

199–208. doi:10.1016/S0961-9534(99)00039-2

367 368 369 370 371 372 373

Telmo, C., Lousada, J., 2011. Heating values of wood pellets from different species. Biomass and Bioenergy 35, 2634–2639. doi:10.1016/j.biombioe.2011.02.043 Vassilev, S. V, Baxter, D., Andersen, L.K., Vassileva, C.G., 2010. An overview of the chemical composition of biomass. Fuel 89, 913–933. Werther, J., Saenger, M., Hartge, E.U., Ogada, T., Siagi, Z., 2000. Combustion of agricultural residues. Progress in Energy and Combustion Science 26, 1–27. Zamorano, M., Popov, V., Rodríguez, M.L., García-maraver, A., 2011. A comparative study of

374

quality properties of pelletized agricultural and forestry lopping residues. Renewable Energy

375

36, 3133–3140. doi:10.1016/j.renene.2011.03.020

376 377

16

378

Table 1. Number and type of treatments for the selected crops as declared by the farmers

379 Olive

Pear

Vine

Hazelnut

Apple

Variety

Coratina

William

Cabernet

Tonda Gentile Golden Delicius

Pruning frequency (years)

2

1

1

1

1

Fertilization intensity (N-P-K units ha-1 year-1) 70/50/60 80/40/90 100/40/110 70/30/80

80/40/90

Insecticide treatments (n year-1)

6

11

1

0

11

Fungicide treatments* (n year-1)

5

24

23

1

26

380 381

* Mostly copper and/or sulphur treatments, alone or mixed with other substances such as penconazole, dithiocarbamates, etc.

17

382

Table 2. Water mass fraction (% over green weight) and particle size distribution (% over total sample) according to UNI EN 14961-1 2010 for P63

383

Industrial wood chips commercial classes (Logging residues)

384 Water mass fraction

385

Size distribution Coarse fraction Main fraction Fines fraction

Olive 34.8 b

SD 1.15

Pear 45.4 a

SD 1.97

Vine 45.2 a

SD 1.50

11.57 a 75.12 a 10.50 bc

2.51 6.07 2.20

6.32 b 71.67 a 16.80 a

2.29 4.97 1.61

4.82 b 80.62 a 8.97 c

3.24 8.37 2.12

Hazelnut 34.4 b 5.95 ab 80.15 a 11.30 bc

SD 4.48

Apple 44.5 a

SD 1.53

P value 0.000

1.46 3.48 2.99

6.65 b 71.62 a 13.80 ab

4.52 7.43 4.49

0.049 0.156 0.012

386

Notes: SD = Standard Deviation; p-Value = probability that the difference between ranks is casual. Values on the same row followed by different letters are significantly different

387

(P ≤ 0.05, Scheffé’s method). Coarse fraction (> 100 mm), Main fraction (3.15 - 63 mm), Fines fraction (< 3.15 mm).

388

18

390

Table 3. Concentration of structural elements and macronutrients in the test biomass types

391

Olive

392

SD

Pear

SD

Vine

0.449 0.049 0.046 0.004 0.006

43.83 6.22 0.70 0.034 0.064

3,680.5 254.8

Element % on dry weight. C 45.90 H 6.63 N 0.64 S 0.027 Cl 0.044

a a b a b

0.786 0.073 0.049 0.004 0.001

44.51 6.29 0.86 0.026 0.023

ab b a a c

mg kg-1 K Na

a a

766.7 86.94

3,804.7 232.1

a 242.9 bc 67.71

4,709.1 603.1

SD

Hazelnut

b b b a a

0.901 0.115 0.043 0.001 0.005

44.65 6.19 0.66 0.026 0.031

ab bc

389.9 71.52

4,335.5 401.0

SD

Apple

ab b b a c

0.432 0.180 0.085 0.002 0.001

44.00 6.32 0.68 0.030 0.025

a b

920.7 70.63

2,526.1 190.9

SD

P value

b b b a c

0.700 0.151 0.087 0.003 0.004

0.001 0.001 0.003 0.071 0.000

b c

362.6 104.47

0.000 0.000

393

Notes: SD = Standard Deviation; p-Value = probability that the difference between ranks is casual. Values on the same row followed by different letters are significantly different

394

(P ≤ 0.05, Scheffé’s method).

395

19

396

Table 4. Concentration of heavy metals in the test biomass (mg kg-1)

397 398 399

Olive

SD

Pear

SD

405

Element Cr nd Cu 22.4 Ni 3.4 Pb 7.7 Zn 9.5 Mn 86.2 Hg nd As nd Notes: SD = Standard

406

different (P ≤ 0.05, Scheffé’s method), nd = not detected

400 401 402 403 404

nd 72.2 a 4.130 4.4 b 0.443 9.4 b 0.479 78.1 a 3.213 116.6 c 4.424 nd nd Deviation; p-Value = probability that the c b c d c

3.103 0.702 0.702 0.925 6.709

Vine

SD

nd 21.6 c 6.073 9.1 a 2.281 11.6 a 0.967 31.5 b 4.965 365.9 b 124.50 nd nd difference between ranks is

407

20

Hazelnut

SD

nd 12.2 c 1.404 4.8 b 0.993 10.7 ab 0.602 14.5 cd 1.786 555.1 a 72.86 nd nd casual. Values on the same

Apple nd 35.6 b 4.7 b 11.4 a 20.6 c 101.9 c nd nd row followed by

SD

P value

10.150 10.230 0.813 5.464 16.21

0.000 0.000 0.000 0.000 0.000

different letters are significantly

408

Figure 1. The machine used for the collection of residues is constituted by a heavy-duty harvester towed by a special orchard-tractor. The ensemble

409

may be regarded as an industrial system for biomass production.

410

411 21

412

Figure 2. Ash content of the test biomass

413

414 415

Grey bars represent the average value (n=5), also shown in numerical figures at the top of each bar. Values followed by different letters are significantly different (P ≤ 0.05,

416

Scheffé’s method), black bars report the standard deviation (SD).

417

22

418

Figure 3. Ash melting behaviour of the tested biomasses.

419

Shrinkage

Deformation

Hemisphere

Flow

1500 1400

Temperature (° C)

1300 1200 1100 1000 900 800 1

2

3

4

5

420 421

The bars report the temperature at which occurs each stage of ash modification (Shrinkage, Deformation, Hemisphere and Flor). The maximum temperature reached in the test is

422

1500 °C, thus the bars reporting such value should be intended as “stage occurring at temperature of 1500 °C or above”. The grey double line represents the reference value of

423

1200 °C, the maximum combustion temperature at grate level for common biomass boilers.

23

425

Figure 4. Gross calorific value on dry basis of the test biomass

426

427 428

Grey bars represent the average value (n=5), in numerical figures at the top of each bar. Values followed by different letters are significantly different (P ≤ 0.05, Scheffé’s

429

method), black bars report the standard deviation (SD).

24