Environmental assessment of different harvesting solutions for Short Rotation Coppice plantations

Science of the Total Environment 541 (2016) 210–217

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Environmental assessment of different harvesting solutions for Short Rotation Coppice plantations Jacopo Bacenetti ⁎, Domenico Pessina, Marco Fiala Department of Agricultural and Environmental Sciences, Production, Landscape, Agroenergy, Università degli Studi di Milano, via Giovanni Celoria 2, 20133 Milano, Italy

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Two different harvesting solutions for Short Rotation Coppice were evaluated. • There is a lack of information about the environmental impact of SRC harvesting. • A forager based solution was compared with a tractor-based solution. • Harvesting with self-propelled forager achieves better environmental performance. • These differences are mainly related to the different machine productivity.

a r t i c l e

i n f o

Article history: Received 2 June 2015 Received in revised form 16 September 2015 Accepted 17 September 2015 Available online 25 September 2015 Editor: D. Barcelo Keywords: Poplar Woody biomass Mechanization Northern Italy Short rotation forestry

a b s t r a c t Although several studies have been carried out on Short Rotation Coppice (SRC) plantations and on their environmental performances, there is a lack of information about the environmental impact of the harvesting operations. In this study, using LCA approach, the environmental performance of two different harvesting solutions for Short Rotation Coppice plantations was evaluated. In more details, for 2-years cutting time poplar plantations, harvesting with a self-propelled forager equipped with a specific header was compared in terms of environmental impact with a tractor-based solution. The LCI was built with experimental data collected during field tests carried out over about 70 ha of SRC plantation in Northern Italy. The following nine impact potentials were evaluated according to the selected method: climate change (CC), ozone depletion (OD), particulate matter (PM), photochemical ozone formation (POF), acidification (TA), freshwater eutrophication (FE), terrestrial eutrophication (TE), marine eutrophication (ME) and mineral, fossil and renewable resource depletion (MFRD). Although harvesting with self-propelled foragers requires higher power and higher diesel consumption, it achieves better environmental performances respect to the harvest with the tractor-based solution. The tractor-based option is characterized by lower operative field capacity (about – 70% for all the evaluated impact

⁎ Corresponding author. E-mail address: [email protected] (J. Bacenetti).

http://dx.doi.org/10.1016/j.scitotenv.2015.09.095 0048-9697/© 2015 Elsevier B.V. All rights reserved.

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categories except for MFRD, which is – 94% compared to the first option). The environmental differences are mainly related to the different machine productivity. From an environmental point of view, respect to the harvesting with self-propelled foragers, the tractor-based solution can achieve a lower environmental impact only in small SRC plantations (b1–2 ha). © 2015 Elsevier B.V. All rights reserved.

1. Introduction In Europe, energy policies are increasingly promoting energy generation from renewable sources (i.e. EU target of 27% renewable energy by 2030 and 40% of GHG emission reduction) (European Commission, 2014). Among the different renewable sources, woody biomass is an interesting solution for energy generation in rural areas for both electricity (Negri et al., 2014) and heat production (Caserini et al., 2010; Cherubini et al., 2009). Woody biomass is produced from forestry management but also from dedicated plantations in which woody species are grown with energy purposes (Gasol et al., 2009; González-García et al., 2012a; Paris et al., 2010). In more details, with regard to this latter, Short Rotation Coppice (SRC) plantations are cultivations of woody crops (Poplar, Salix, Black locust, etc.) characterized by short cutting times (1–2 or 5–6 years), high plant density and a crop cycle ranging from 10 to 15 years during which several harvests take place (Paris et al., 2010; Bergante and Facciotto, 2011; Bergante et al., 2012; Fiala et al., 2010). Considering the different cutting time the SRC plantations can be divided in SRC (harvested each 1–2 years) and MRC (Medium Rotation Coppice, harvested each 5–6 years) (Bergante et al., 2012; Nielsen et al., 2014). Differently from Northern Europe, where large amounts of woody biofuel are also produced from forestry (Anerud and Jirjis, 2011; Nielsen et al., 2014), in Italy, SRC represents an important biomass source for energy purposes (Manzone et al., 2009; Bergante et al., 2012); nevertheless, for MRF above all, the produced biomass can be employed also in paper industry as well as in the furniture sectors as plywood. Mainly in Northern Regions (Lombardy and Veneto) of Italy, thanks to public subsidy frameworks, over the years about 7000 ha of SRC have been cultivated (Bergante and Facciotto, 2011; Fiala and Bacenetti, 2010; Bacenetti et al., 2012; González-García et al., 2012b; Manzone et al., 2009). Poplar clones are the most used for SRC, but experiences have been carried out also with Salix spp. and Robinia pseudoacacia L. (Bergante and Facciotto, 2011; Bergante et al., 2012; Manzone et al., 2009). Some studies highlighted that Salix clones biomass yield can be higher than that of poplar (Paris et al., 2010; Bergante et al., 2012; Nielsen et al., 2014; Rosso et al., 2013). Among the different options, 2 and 5 years cutting times are the most widespread. Although originally used, the annual one has no more been adopted due to issues related to survival and planting costs. In Italy, even if better economic performances and better biomass quality are related to SRC with a 5-years cutting time, the main share of SRC (about 75%) is cultivated with a 2-years cutting time (Barontini et al., 2014; Guidi et al., 2008; Nassi o di Nasso et al., 2010; Fiala and Bacenetti, 2012a,b; Testa et al., 2014). Harvesting operations in SRC include felling, chipping, and chips transporting to the collecting point, where biomass is temporarily stored before sale. In the plantations with 5-years cutting time, felling and chipping are separated because the stem basal diameters reach 0.20–0.25 m; thus, felling and chipping simultaneously would require very high power foragers. On the contrary, in biannual SRC, basal diameters at the harvest are not greater than 0.12–0.14 m, therefore, it is possible to fell and chip simultaneously the stems using different harvesting units: tractor-based (TB) or forager-based (FB) (Manzone et al., 2009; Spinelli et al., 2006; Spinelli et al., 2009). Foragers are equipped with headers specifically developed to harvest SRC plantations (Spinelli et al., 2006; Spinelli et al., 2009; Fiala and Bacenetti, 2012a,b).

Besides the economic aspects, also the environmental ones must be carefully evaluated in order to improve the sustainability of this renewable energy source. To this regard, studies carried out in the past years highlighted that among the field operations carried out over the whole crop cycle, the harvest is the one with the highest environmental impact (Gasol et al., 2009; Fiala et al., 2010; Bacenetti et al., 2012; González-García et al., 2012b; Fiala and Bacenetti, 2012a,b). This impact is mainly caused by high fuel consumption (Fiala and Bacenetti, 2012a, b; Spinelli et al., 2006; Spinelli et al., 2009). To deepen the knowledge concerning the SRC environmental sustainability, particular attention must be paid on assessing the environmental impact of harvest. In the last decade, in order to evaluate the environmental performances of agricultural processes, Life Cycle Assessment (LCA) has become more and more employed. LCA is a methodology that aims to analyze products, processes or services from an environmental perspective [ISO 14040, 2006] (ISO, 2006), providing a useful and valuable tool for agricultural systems evaluation (Fusi et al., 2014; Noya et al., 2015; Bacenetti et al., 2015b; Niero et al., 2015; Renzulli et al., 2015) as well as for renewable energy sources such as firewood (Pierobon et al., 2015), pellet (Fantozzi and Buratti, 2010) and biogas (Bacenetti et al., 2013; Lijó et al., 2014a; Lijó et al., 2014b; Lijó et al., 2015; Ingrao et al., 2015). In this context, the aim of this paper is to analyze the environmental performances of two different harvesting solutions for SRC poplar plantations harvested every 2-years. Besides, to highlight the environmental hotspots for this operation, the main purpose of the study is to analyze the effect of technical and operative parameters (e.g., field capacity, machine productivity) affecting the environmental impact of different technical solutions. 2. Materials and methods 2.1. Goal and scope definition The goal of this study is to assess the environmental impact of the harvest solution for SRC plantation with 2-years cutting time. The selected cutting time is the most widespread option for poplar SRC cultivation in Northern Italy where, at the end of the 2nd growing year, stems have a basal diameter lower than 0.14 m. The research questions can be summarized as follows: 1) What is the environmental impact of the harvesting operation in SRC poplar plantations? 2) What are the main environmental hotspots associated with this operation? 3) Which are the site-specific and operational parameters that mainly affect the environmental performances of harvesting operation? The study outcomes can be useful for farmers and farmer associations involved in SRC plantation, for agricultural contractors as well as for local policy makers involved in the woody-bioenergy process. Finally, the achieved results can be up-scaled either to SRC plantation with longer cutting time, but where lower temperatures (e.g., Central and Northern Europe) reduce the annual growth or to Salix plantations where the higher number of stems per stump reduces the basal diameter (Christersson and Sennerby-Forsse, 1994; Perttu, 1998; Bergante et al., 2012; Nielsen et al., 2014).

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Fig. 1. Forage based harvesting solution. Particular of the steel finger crop collectors (A), the two circular saws (B) and the infeed rollers (C) that send the stems to the forager chopper.

2.2. Functional unit The functional unit is an important step of any life cycle assessment since it provides the reference to which all other data in the assessment are normalized. With LCA's application to agricultural processes, different functional units (FUs) can be selected. Usually, in studies of agricultural production systems, the FU is the area (e.g., 1 ha). However, the mass-based functional unit is prevalent in LCA studies of agricultural systems and therefore, in this study, 1 t of fresh matter harvested was considered as FU.

2.3. System description SRC poplar plantations were grown in Lombardy (Po Valley – Northern Italy) in the district of Cremona (45°13′00″N 10°15′00″E). In more details, tests to detect technical and operational parameters related to the forager harvester were performed in 5 plantations for a global agricultural area of about 70 ha. Felling and chipping were performed simultaneously by means of a self-propelled combine forager harvester (Claas Jaguar 880, engine power 343 kW, mass 11,500 kg) equipped with the header GBE2 developed by the Italian company “Gruppo Biomasse Europa” (GBE2). The GBE2 header was built to fell and chip shoots with a basal diameter of

about 0.12–0.14 m, it is 2.5 m wide, 2.7 m long, and 1.4 m high with a mass of 2050 kg (Fig. 1). As alternative scenario, a different harvesting tractor-based unit was evaluated. In more details, this second solution involved a chipping header coupled with a tractor. This header (Fig. 2) had a mass of 1800 kg, was coupled with a 140 kW tractor (8320 kg) from which received the motion by a cardan shaft; it was provided with two circular blades, a steel bar Y-shaped to facilitate the stem entry and a couple of rollers for the feeding of the cutting system (a disk cutting system with two radial knives). During the working time the tractor in reversing and the equipment is supported by two wheels. They are free on their axle, placed on hydraulic jacks and allow for the adjustment of the stem cut height. The chips produced are unloaded through a revolving outlet pipe, in a tractor trailer. With regard to the system boundaries, the assessment was carried out only considering the harvest operation in which felling and chipping were performed simultaneously. Therefore, raw materials extraction (e.g., fossil fuels and minerals), manufacture (e.g., tractors, foragers and agricultural machines), use (diesel fuel consumption and derived combustion and tire abrasion emissions), maintenance, and final disposal of machines were considered. The transport of the harvested biomass from the field to the storage point was excluded by the system boundary because this operation is equal for the two evaluated scenarios.

Fig. 2. Tractor based harvesting solution. On the left, sideways (the arrow indicate the driving direction); on right, frontally.

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Table 1 Technical and operative parameters recorded during the field tests for forage based (FB) scenario. Parameter

Unit of measure

Effective field capacity (EFC) Effective machine productivity (EMP) Diesel fuel consumption Lubricant oil consumption Average basal diameter of stem

ha·h−1 t·h−1 of fresh matter kg·t−1 of fresh matter kg·t−1 of fresh matter cm

SRC plantation

Average

A

B

C

D

E

0.77 42.2 1.632 0.049 7.24

1.08 64.2 1.069 0.0321 10.40

1.67 61.8 1.113 0.0334 8.56

0.83 52.4 1.189 0.0357 9.90

0.94 56.5 1.208 0.0362 5.16

Table 2 Different Ecoinvent unit processes involved in the inventory. Process and input

Ecoinvent process

Diesel fuel Lubricant oil Tractor Operative machine Self-propelled forager

Diesel, at regional storage/RER Lubricating oil, at plant/RER Tractor, production/CH Agricultural machinery, general, production/CH Harvester, production/CH

1.06 55.4 1.079 0.0324 8.24

regard to maintenance, the substitution of lubricant, tire sets and filters was considered. Background data for the production of diesel fuel, tractors, equipment and self-propelled foragers were obtained from the Ecoinvent database v.3 (Ecoinvent Database, 2015). Table 2 reports the Ecoinvent processes involved in the inventory. 2.5. Life cycle impact assessment (LCIA)

2.4. Life cycle inventory Data concerning harvesting operation in baseline scenario (self-propelled forager equipped with GBE2 header) were directly measured on SRC plantations through field tests. Diesel fuel consumption was measured by quantifying the volume of fuel to fill up fuel tanks to the brim; biomass yields were assessed using a farm weighbridge, while the working time, useful to calculate the effective field capacity (EFC, ha·h−1), was directly measured on fields. Table 1 reports the main technical and operational parameters obtained through tests in the 5 SRC plantations for the harvest with selfpropelled forager harvester. Biomass yields in the different plantations were 54.6, 59.4, 36.9, 69.5 and 60.4, t·ha−1 of fresh matter for plantations A, B, C, D and E, respectively. More details about the calculations of effective field capacity and machine productivity (EMP, t·h−1) can be found in Fiala and Bacenetti (2012a, b). For the alternative scenario (tractor-based or TB scenario), diesel consumption was quantified according to the model SEA (Fiala and Bacenetti, 2012a,b) considering a proper coupling among tractor and implement and an effective field capacity equal to 0.25 ha·h−1. For both scenarios, lubricant oil consumption was calculated according to the Ecoinvent Report 15 (Nemecek and Kägi, 2007). According to Frischknecht et al. (2007), the impact of capital goods was considered when maintenance and depreciation costs of capital equipment formed a substantial part of the product price. Therefore, for both scenarios, the indirect environmental burdens of capital goods (machines such as tractors, equipment, and self-propelled foragers) were included too. With regard to the amount of tractors and implements, the necessary amount1 was accounted considering, beside mass, specific parameters such as economical (ELS, years) and physical (PLS, h) life span2 and annual working time (AWT, h·year−1). In more details, economical and physical life span were taken from Bodria et al. (2006), while the annual working time for the equipment was directly obtained from farmers interviews3 (Bacenetti et al., 2014). As 1 AM = m / (AWT · ELS) where: AM = mass of the equipment (virtually) consumed expressed in (kg·h−1); M = mass of the equipment (kg); when (AWT · ELS) N PLS → AM = m / PLS. 2 Physical life span (PLS, h) was considered equal to 12,000 h for tractor and equal to 2500 h for the two different headers and the forager while economical life span (ELS, years) was 12, 10 and 8 years for tractor, forager and headers, respectively. 3 For self-propelled forager the annual working time (AWT, h·year−1) was accounted considering its use to harvest cereals for silage production (maize 450 h·year−1 and winter cereals such as triticale, wheat, barley and oat 250 h·year−1) and the harvesting of 400 ha of SRC.

The characterization factors reported by the ILCD method were used (Wolf et al., 2012). The following nine impact categories were evaluated according to the selected method: climate change (CC), ozone depletion (OD), particulate matter (PM), photochemical ozone formation (POF), acidification (TA), freshwater eutrophication (FE), terrestrial eutrophication (TE), marine eutrophication (ME) and mineral, fossil and renewable resource depletion (MFRD). 2.6. Life cycle interpretation The LCIA results were analyzed in order to identify the environmental hotspots. The environmental hotspots (or key processes) are the processes that, over the whole production system, are most responsible for the environmental impact. For the two harvesting solutions under study, a sensitivity analysis was carried out in order to test the robustness of the results and to investigate the influence of the effective field capacity on the environmental analysis. For FB scenario minimum and maximum EFC recorded in the field test were considered while, for TB scenario a variation of ±20% was considered. Furthermore, a sensitivity analysis was carried out also considering a second LCIA method. In more detail, the Recipe Midpoint LCIA method with European normalization was used (Goedkopp et al., 2009). 3. Results and discussion 3.1. Harvesting with self-propelled forager and GBE2 header (FB scenario) Table 3 reports the environmental impact of the harvesting with the self-propelled forager equipped with the GBE2 header considering the average values recorded in the field tests (FB scenario “average”4); hotspots are shown in Fig. 3. For six (CC, PM, POF, TA, TE, ME) of the nine evaluated impact categories, emissions from fuel combustion (diesel and lubricant oil combustion) are the main hotspot with a share of the environmental impact ranging from 77% to 94%. Diesel fuel production is the main responsible for OD (93%) and it is important also for CC (14.7%), PM (15.5%), and TA (12.3%); on the contrary, lubricant oil production plays a minor role on all the evaluated impact categories (b1% except for OD — 3.2% and FE — 1.3%). Machines production is the main hotspot for two impact categories: FE (66.7% is due to forager and

4

With “average” the analysis refers to the average values reported in Table 1.

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Table 3 Environmental impact for FB (forage based) scenario considering the average value reported in Table 1. Impact category

Unit

Total for FB scenario “average”

Fuel combustion emissions

Forager, production

Header, production

Diesel fuel, production

Lubricating oil, production

CC OD PM POF TA TE FE ME MFRD

kg CO2 eq kg CFC-11 eq kg PM2.5 eq kg NMVOC eq molc H+ eq molc N eq kg P eq kg N eq kg Sb eq

4.395 6.64 · 10−7 2.79 · 10−3 6.69 · 10−2 5.04 · 10−2 2.49 · 10−1 2.59 · 10−5 2.27 · 10−2 4.60 · 10−5

3.380 0.000 2.16 · 10−3 5.99 · 10−2 4.23 · 10−2 2.35 · 10−1 0.000 2.14 · 10−2 0.000

0.273 2.24 · 10−8 1.47 · 10−4 1.23 · 10−3 1.40 · 10−3 2.37 · 10−3 1.73 · 10−5 2.02 · 10−4 3.92 · 10−5

0.062 4.47 · 10−9 3.14 · 10−5 2.74 · 10−4 2.63 · 10−4 5.26 · 10−4 5.11 · 10−6 4.57 · 10−5 3.91 · 10−6

0.646 6.16 · 10−7 4.32 · 10−4 5.05 · 10−3 6.12 · 10−3 1.05 · 10−2 3.19 · 10−6 9.57 · 10−4 2.67 · 10−6

0.035 2.10 · 10−8 2.57 · 10−5 4.99 · 10−4 3.54 · 10−4 4.12 · 10−4 3.25 · 10−7 3.71 · 10−5 1.98 · 10−7

Fig. 3. Environmental hotspots identification for FB scenario “average”.

19.7% to the GBE2 header) and MFRD (85.3% is due to forager and 8.5% to GBE2 header). Fig. 4 shows the comparison among the environmental impacts of harvesting in the five SRC plantations. There are considerable variations

among the different SRC plantations, which are mainly related to the different EFC and, even more, to the different EMP detected during the field tests. Compared to the average results reported in Table 3, the harvesting in plantation A shows the highest environmental load for all the

Fig. 4. FB scenario, comparison among the environmental impact of harvesting in the five SRC plantations.

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Table 4 Harvesting operation with “tractor-based” (TB) unit: environmental impact and hotspot identification for the FU and variation respect to FB (forage based) scenario. Impact category

Score for TB scenario

Fuel combustion emissions

Tractor, production

Header, production

Diesel fuel, production

Lubricating oil, production

CC OD PM POF TA TE FE ME MFRD

7.517 kg CO2 eq 1.15E−06 kg CFC-11 eq 0.0048 kg PM2.5 eq 0.1153 kg NMVOC eq 0.0864 molc H+ eq 0.4288 molc N eq 3.87E−05 kg P eq 0.0391 kg N eq 9.00E−05 kg Sb eq

5.838 0.000 3.72 · 10−3 1.03 · 10−1 7.30 · 10−2 4.06 · 10−1 0.000 3.70 · 10−2 0.000

0.272 3.20 · 10−8 1.40 · 10−4 1.31 · 10−3 1.30 · 10−3 2.13 · 10−3 1.36 · 10−5 1.83 · 10−4 7.05 · 10−5

0.231 1.67 · 10−8 1.17 · 10−4 1.02 · 10−3 9.81 · 10−4 1.96 · 10−3 1.90 · 10−5 1.70 · 10−4 1.45 · 10−5

1.116 1.06 · 10−6 7.47 · 10−4 8.72 · 10−3 1.06 · 10−2 1.82 · 10−2 5.51 · 10−6 1.65 · 10−3 4.61 · 10−6

0.273 3.20 · 10−8 1.40 · 10−4 1.31 · 10−3 1.30 · 10−3 2.13 · 10−3 1.36 · 10−5 1.83 · 10−4 7.05 · 10−5

evaluated impact categories (about + 51%) and, at the same time, is characterized by the lowest effective field capacity (− 27%) and machine productivity (−24%) and the higher fuel consumption (+50%). 3.2. Harvesting with tractor-based unit (TB scenario) Table 4 reports the environmental performance for the harvesting carried out by the header coupled with tractor (TB scenario) and the variation of environmental impact for the same operation performed with the self-propelled forager equipped with GBE2 header (FB scenario “average”). For all the nine evaluated impact categories, TB scenario involves a higher environmental impact. In more details, the score is almost doubled for MFRD (+ 96%), it increases of 71–74% for CC, OD, PM, POF, TA, TE and ME and of 49% for FE. As regard to hotspots identification (Fig. 5), the results are similar to FB scenario. The only noticeable difference is related to MFRD, where a higher share is related to the header production. 3.3. Sensitivity analysis results As explained in Section 2.6, the sensitivity analysis was carried out concerning the effective field capacity and the LCIA method. The sensitivity analysis carried out on the effective field capacity shows that: i) for FB scenario, the environmental impact grows of 50.9%–51.3% when the minimum value is considered and reduces of 0.8%–1.0% when the highest EFC is taken into account. This asymmetry is due to the fact that the minimum EFC case (see. Table 1 — Plantation

A) shows both EMP (effective machine productivity) and diesel fuel consumption are characterized by high deviations respect to the average values, while in the maximum EFC case (see. Table 1 — Plantation C), values are more closed to averages ii) for the TB scenario, when EFC increases to 0.3 ha·h−1, the environmental load decreases of about 16.7%–17.5% while when EFC decreases to 0.2 ha·h− 1, the environmental impact increases of 23.8%–24.8%. Table 5 reports the environmental results when the Recipe LCIA method (Goedkopp et al., 2009) is applied. The results cannot be compared for all the evaluated impact categories because of the different unit of measure. A direct comparison can be performed for: i) CC, where the impact computed with Recipe LCIA method is lower (−2.4%) than the one assessed with the ILCD one; ii) OD, there are no differences between the Recipe and ILCD methods; iii) POF, the results are very similar, the Recipe's one is slightly (+1.0%) higher; iv) FE, the impact computed with the Recipe is higher (+6.7%) than the one evaluated with ILCD; v) ME, where a large difference is observed; the environmental load assessed with Recipe is considerably lower (−89%) than the one computed considering the ILCD method. To this regard, it should be underlined that the Recipe LCIA method, considers only ME and FE as eutrophication impact potentials, while ILCD method computes also TE.

Fig. 5. Environmental hotspots identification for TB scenario.

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Table 5 Environmental results for the Recipe Midpoint method (results are referred to the FU). Impact category

Unit

Score

Climate change Ozone depletion Terrestrial acidification Freshwater eutrophication Marine eutrophication Human toxicity Photochemical oxidant formation Particulate matter formation Freshwater ecotoxicity Metal depletion Fossil depletion

kg CO2 eq kg CFC-11 eq kg SO2 eq kg P eq kg N eq kg 1,4-dB eq kg NMVOC kg PM10 eq kg 1,4-dB eq kg Fe eq kg oil eq

4.290 6.64 · 10−5 0.047 2.76 · 10−5 0.002 12.655 0.068 0.019 0.005 0.265 1.490

3.4. Comparison between the two harvesting solutions In Fig. 6 the comparison between the environmental impact of the two harvesting solutions is reported: the self-propelled forager equipped with GBE2 header (FB scenario) and the header coupled with tractor (TB scenario). Columns height represents the impact obtained considering, for FB scenario, the average values recorded in the field tests (see. Table 2) and, for TB scenario, an effective field capacity of 0.25 ha·h−1. The error bars represent the variation in impacts related to (i) different EFC of field tests (for FB scenario) and (ii) minimum and maximum effective field capacity for TB scenario (0.2 and 0.3 ha·h−1). However, for both harvesting solutions there is wide variability regarding the environmental impact; nevertheless, in general terms, FB scenario shows better environmental performances. For eight of the evaluated impact categories, the environmental impact between the two scenarios is similar only when EFC is high for TB scenario and low for FB scenario. However, for MFRD, FB scenario has always a lower impact compared to TB scenario.

3.5. Discussion Few studies were previously carried out for SRC in order to highlight the environmental impact of harvesting operations. Nevertheless they highlighted that this operation is an important, but often overlooked,

potential source of optimization in the whole wood-to-energy bioenergy process. Fiala and Bacenetti (2012a,b) evaluated the harvest of SRC plantation with forager and, taking into account also the transport to the storage point, found an emission of GHG ranging from 15.7 to 18.2 kg CO2 eq·t−1 of dry matter. Considering an average moisture content of 50%, these values correspond to 7.8 to 9.1 kg CO2 eq·t−1 of fresh matter: higher than those assessed in this study but a direct comparison cannot be draft due to the different system boundary. Manzone et al. (2009) evaluated, without using a strictly LCA approach, the energetic cost of SRC plantation and highlighted the harvesting operation represent about the 19% of the total energetic cost. Always from an energetic point of view, a lower share for harvesting (about 11%) was assessed by Nassi o di Nasso et al. (2010). As regard to the scalability of the achieved results in other European regions where SRC plantations are grown, the main parameter that must be considered is the stem basal diameter. Considering that stems with basal diameter larger than 0.12 m cannot be managed by the forager equipped with the GBE2 header, it is clear that this is the parameter that determines the possibility to use this harvesting solution. The results of this study can be useful also for SRC plantations with a 3-years cutting time that are cultivated in cold climates (e.g., Northern Europe). In fact, in these climatic conditions, stems at the end of the 3rd growing season achieve basal stem diameters similar to those of 2-years poplar in South Europe. Finally, when no experimental data are available, the effective field capacity and machine productivity are the mechanical parameters most useful to define not only the mechanical aspects of the harvest but also its environmental performance. 4. Conclusions This study evaluated the environmental impact of harvesting operation in SRC plantations with a 2-years cutting time. Several studies have been carried out on SRC plantations. However, although harvesting has resulted being one of the main environmental hotspots of the whole crop cycle, there is still a lack of information about the environmental impact of this operation. Using experimental data collected during field tests in 5 SRC plantations, the environmental impact of the harvesting with a self-propelled forager equipped with a specific header (FB scenario) was compared to the same operation performed with a tractor-based solution (TB scenario). For FB scenario, a wide variation in environmental load was assessed

Fig. 6. Environmental impact of the two harvesting solutions (EFC = effective field capacity; EMP = effective machine productivity).

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for the 5 SRC plantations; these differences were mainly related to the effective machine productivity. Consequently, the lower environmental impact to harvest SRC plantations occurs when biomass yield and effective field capacity are high (e.g., biomass yield N 55 t·ha−1 of fresh matter; EFC N 0.95 ha·h−1). Although TB scenario requires lower engine power compared to selfpropelled foragers, it is characterized by lower operative field capacity; thus, it entails higher environmental impact for the nine evaluated impact categories, if compared to FB scenario. From an environmental point of view, this solution could be better than TB only in small SRC plantations (b 1-2 ha); in this case, however, the use of self-propelled foragers will involve a duration growth of accessory working times (e.g., maintenance, setting, and relocation) that becomes predominant respect to the chipping time. Acknowledgments The authors thank Regione Lombardia which financed a Postdoctoral Research Fellowship (“Progetto Dote Ricerca” financed by FSE — Regione Lombardia). Any opinions, findings, conclusions or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the Department involved in this study. References Anerud, E., Jirjis, R., 2011. Fuel quality of Norway spruce stumps — influence of harvesting technique and storage method. Scand. J. For. Res. 26 (3–3), 257–266. Bacenetti, J., González-García, S., Mena, A., Fiala, M., 2012. Life cycle assessment: an application to poplar for energy cultivated in Italy. J. Agr. Eng. 43, 72–78. Bacenetti, J., Negri, M., Fiala, M., Gonzalez, G.S., 2013. Anaerobic digestion of different feedstock: impact on energetic and environmental balances of biogas process. Sci. Total Environ. 463-464, 541–551. Bacenetti, J., Fusi, A., Negri, M., Guidetti, R., Fiala, M., 2014. Environmental assessment of two different crop systems in terms of biomethane potential production. Sci. Total Environ. 466-467, 1066–1077. Bacenetti, J., Duca, D., Fusi, A., Negri, M., Fiala, M., 2015b. Mitigation strategies in the agrofood sector: the anaerobic digestion of tomato puree by-products. An Italian case study. Sci. Total Environ. 526, 88–97. Barontini, M., Scarfone, A., Spinelli, R., Gallucci, F., Santangelo, E., Acampora, A., Jirjis, R., Civitarese, V., Pari, L., 2014. Storage dynamics and fuel quality of poplar chips. Biomass Bioenergy 62, 17–25. Bergante S, Facciotto G. Nine years of measurements in Italian SRC trial with 14 poplar and six willow clones. In: ETA, editor. Proceedings of the 19th European biomass conference and exhibition, Berlin, Germany. 6–10 June 2011. p. 178–82. Bergante, S., Facciotto, G., Minotta, G., 2012. Identification of the main site factors and management intensity affecting the establishment of short-rotation coppices (SRC) in Northern Italy through stepwise regression analysis. Cent. Eur. J. Biol. 5, 522–530. Bodria, L., Pellizzi, G., Piccarolo, P., 2006. Il trattore e le macchine operatrici. Ed. Edagricole. Caserini, S., Livio, S., Giugliano, M., Grosso, M., Rigamonti, L., 2010. LCA of domestic and centralized biomass combustion: the case of Lombardy (Italy). Biomass Bioenerg. 34, 474–482. Cherubini, F., Bird, N.D., Cowie, A., Jungmeier, G., 2009. Energy-and greenhouse gas-based LCA of biofuel and bioenergy systems: key issues, ranges and recommendations. Resour. Conserv. Recycl. 53 (8), 434–447. Christersson, L., Sennerby-Forsse, L., 1994. The Swedish programme for intensive short rotation forests. Biomass Bioenerg. 6 (1–2), 145–149. Ecoinvent Database, 2015. www.ecoinvent.org. European Commission, 2014. COM/2014/015 Final, A Policy Framework for Climate and Energy in the Period From 2020 to 2030, 1–18. Fantozzi, F., Buratti, C., 2010. Life cycle assessment of biomass chains: wood pellet from short rotation coppice using data measured on a real plant. Biomass Bioenerg. 34 (12), 1796–1804. Fiala, M., Bacenetti, J., 2010. Pioppo da biomassa in rotazione biennale. Sherwood 165, 43–47. Fiala, M., Bacenetti, J., 2012a. Economic, energetic and environmental impact in short rotation coppice harvesting operations. Biomass Bioenergy 42, 107–113. Fiala, M., Bacenetti, J., 2012b. Model for the economic, energetic and environmental evaluation in biomass productions. J. Agr. Eng. 42, 26–35. Fiala, M., Bacenetti, J., Scaravonati, A., Bergonzi, A., 2010. Short rotation coppice in Northern Italy: comprehensive sustainability. 18th European Biomass Conference and Exhibition (Lyon, France). Frischknecht, R., Jungbluth, N., Althaus, H.J., Doka, G., Heck, T., Hellweg, S., Hischier, R., Nemecek, T., Rebitzer, G., Spielmann, M., Wernet, G., 2007. Overview and Methodology. Ecoinvent Report No. 1. Swiss Centre for Life Cycle Inventories, Dübendorf.

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