Electronic Supplementary Information

Influence of agricultural residues interpretation and allocation procedures on the

environmental performance of bioelectricity production – A case study on woodchips from

apple orchardsMartina Boschiero, Markus Kelderer, Armin O. Schmitt, Carlo Andreotti, Stefan Zerbe

Table of Contents

1. Site location and description............................................................................................................2

2. Woody residues quantification........................................................................................................3

3. Partitioning allocation......................................................................................................................4

4. Uncertainty analysis.........................................................................................................................5

5. Contribution analysis description of the impact categories assessed (excluded GWP and CED)...5

5.1 Upstream emissions.................................................................................................................5

5.2 Downstream emissions............................................................................................................6

6. Foreground process inventory.........................................................................................................7

6.1 Biomass process.......................................................................................................................7

6.2 Bioenergy process..................................................................................................................15

6.3 Reference processes...............................................................................................................18

7. Acronyms and abbreviations used.................................................................................................19

References..............................................................................................................................................20

1. Site location and description

The Autonomous Province of Bozen-Bolzano is located in the southern part of the Alps, in the north-

eastern part of Italy (Fig.S1). This area dominates the national apple production, with about 19,000 ha

dedicated to apple (Malus domestica) cultivation [1]. Apple orchards mainly stretch along the banks

of the Adige river for a length of about 110 km and within an altitudinal range of 220 m to 1,000 m

a.s.l.. The object of our case study is an ordinary integrated managed apple orchard in the

Autonomous Province of Bolzano. It lies in the land-tenure of the Laimburg Research Centre for

Agriculture and Forestry (46° 22' 59"N, 11° 17' 18"E), in the intensively cultivated bottom Valley of

the Adige river (Fig.S1). Laimburg is situated at 243 m a.s.l., with an average annual temperature of

11.5°C, an average precipitation of 818.3 mm, and 1,904 sunny-hours per year (average data from

1965 to 2013) [2]. The site is characterized by a fertile alluvial sandy loam soil, with an amount of

soil organic matter of about 2.5%. The Laimburg farm extents over 60 ha, cultivating mainly the

cultivars Golden Delicious, Gala, Fuji and Braeburn , grafted on M9 rootstocks [1]. On average, the

fruit production reaches 69.8 tha-1 [1].The studied orchard has a density of about 3500 plants per

hectare, with a planting distance of 3 x 0.7 m, and it is managed according to the guidelines of the

provincial program of integrated pome management [3].

Currently, pruning residues are grinded and left on the field, whereas the trunks are used to feed

house-stoves or boilers in the farmers´ houses, which usually are located in the proximity of the fields.

They are mainly used as logs. Generally, rootstocks are sent to compost plants or to the landfill. In

this study we assume that all these woody residues are harvested and chipped to be used as bioenergy

feedstock, and, specifically, to produce bioelectricity in a ORC-CHP plant.

Figure S1: Apple orchards distribution in South Tyrol, summing up to 18,700 ha.

2. Woody residues quantification

Pruning residues, trunks and rootstocks were weighted during the pruning operations in January 2013

at the Laimburg land-tenure. Results are given in Table S1.

We adapted the procedure described by [4] to apple orchards. We assessed the four main cultivars

cultivated in Laimburg farm (which correspond to Golden Delicious, Gala, Red Delicious and

Braeburn) and we selected trees of two different category age: older than 10 years old and younger

than 10 years old, in order to obtain a good average result. For each combination “cultivar*age class”,

four sampling plots were chosen randomly in the farm. The plots consist of an imaginary rectangle

between two tree rows, delimited by four cement poles of the training system. The plot´s surface was

about 17 m2 (2.8m large and 6m long). To reduce the edge effects, a margin of 6m along all the

perimeter of the orchard field was excluded by the assessment. The number of the trees standing at the

margin of the plot area ranged from 6 to 8. The pruned branches felt in the plot were manually

collected and weighted with a digital dynamometer with an accuracy of 0.02kg. The weighting was

carried out at the same day of the pruning. Totally, the pruned brunches of 222 apple trees were

weighted.

In order to determine the quantity of wood available with the orchards replacement process, we

weighted trunks and rootstocks of 10 trees for each cultivar assessed.

Wood subsamples were then collected for further analysis. The determination of the moisture content

was done following the European standard CEN/TS 14774-2. Elemental analysis (C, N) was

accomplished according to UNI EN 15104:2011, whereas phosphorous content (P) was measured

following the EPA 3052 and EPA 6010C regulations. The heating value of the biomass was measured

in agreement with the UNI EN 14918:2010.

Table S1: Average values of biomass yields (dry weight), composition and energy content used in the

assessment.

Biomass typeYields C N P moisture HHV LHV

kg/tree t/ha % % % % MJ/kg MJ/kg

Pruning residues* 0.31 1.0948.06 a 0.87 a 56 a 19.03 a 17.66 aTrunks* 5.96 20.86 0.11 a

Rootstocks* 4.50 15.74Apples 3.2 b 11.2 b 40 c 0.25 d 0.06 d 84 d - -

* biomass weighted and analyzed at the Laimburg research center land-tenure, in January 2013.a we assume the same values for all the different woody biomasses.b apple´s dry weight is calculated from the average fresh yields reported in [1].c from [5]d from [6]

3. Partitioning allocation

The bioenergy chain investigated in this study is a multi-functional process. In fact, heat and power

are co-produced in the ORC-CHP plant, and AWRs are used as biomass feedstock, which are co-

products (or by-products) of apple cultivation them self.

Different methods exist to deal with allocation. In this study we apply the partitioning method,

investigating which activities are caused by the main product, by the co-products and which are

caused by both of them (called joint-processes). The partitioning methods is explained in detail by

Cherubini et al. [7] and we follow the equations reported in their paper.

We allocate the up-stream joint-processes according to mass and economic values, which are the most

common features used in partitioning [7]. We decided to not apply allocation based on energy or

exergy content here, since apples are not used for energy purposes. The mass allocation (“M_Aup”) is

based on the dry mass of the products which is for the apple yield 11.2 t dwha-1y-1 (79.3%) and for the

AWR yield 2.93 tdwha-1y-1 (20.7%). The economic allocation (“E_Aup”) is based on delivered prices.

AWR chips are appraised at 40€ per green ton [8], whereas the average price that the farmer receive

for 1kg of apple is 0.36€ (average prize calculated for the main variety of apple for the year 2013[9]).

Thus, the impacts are allocated for 99.7% to apples and for 0.3% to AWR (see Table 3 in the paper).

The down-stream emissions have been distributed among heat and electricity on an energy, exergy

and economic base. Concerning the exergy-based allocation, we calculate the exergy partitioning

factors using the Carnot principle, as described in [10]. The economic allocation we carry out is based

on the subsidies that the CHP plant gains from the electricity and heat selling. In Italy, bioelectricity

and bioheat are subsidized according to the Directive 2004/8/EC [11]. In this case, the bioelectricity is

subsidized by the feed-in-tariff of 0.209€ per kWhel of net electricity delivered to the grid. In order to

support the use of cogenerated heat, the European regulation [11] provides a further incentive, but

based on the cogenerated electricity. In this specific case the incentive is 0.04 €/kWh el. The Italian

Regulatory Authority for Electricity and Gas (AEEG), gives a further heat valorization bonus of 0.057

€/kWhth [12]. Thus, we attribute a specific partitioning value of 0.065 €/kWhth to the heat.

4. Uncertainty analysis

Table S2: Summary of uncertain parameter used in the Monte Carlo simulation, added to those given

by default by Ecoinvent database [13].

Input parameter Used value Unit Distributio

n Data sources and notes

Pruning residues yields 0.3 kgdwtree-

1y-1triangle

(0.1; 0.9)field measurement carried out

in Laimburg tenurePruning residues losses

during harvesting operations

8 % uniform (3; 12) [8]

Distances between farm and the CHP plant 50 km uniform

(20; 100) estimation according to [14]

Fraction of AI on air 5 % uniform (1; 10) [15,16]

Fraction of AI on ground water 2 % Uniform

(0.5; 2) [15,16]

Fraction of AI on surface water 1 % Uniform

(0.01; 1) [15,16]

Fraction of AI on soil 33 % uniform (15; 85) [15,16]

Fraction of AI on biomass 59 % uniform

(2; 69) calculated according to [16]

Amount of soil eroded in South Tyrol 250 Kgha-1y-1 uniform

(0; 1000) [17]

5. Contribution analysis description of the impact categories

assessed (excluded GWP and CED)

5.1 Upstream emissions

More than 31% of the PCOP derives from the pest control phase, largely due to sulphur dioxide (SO2)

air emissions (49%), which mainly occur during insecticides production, and CO2 (about 18%)

derived from pesticide application. The second main contributor to PCOP is the frame system

installation (28%). Also in this case the main stressors to this impact category are SO 2 (49%) and CO2

(47%), which are emitted during the production of the frame system components.

The largest part of ODP impact (about 69%) originates from two stressors, i.e. bromotrifluoro-

methane (halon 1301) and bromochlorodifluoro-methane (halon 1211). These chemicals are used as a

gaseous fire-suppression agent, and, therefore, these chemicals are mostly used in the upstream crude

oil and natural gas procurement processes. The tetrachloro-methane (CFC-10), a solvent agent,

conspicuously used in pesticides production, is responsible for the 29% of the ODP. In fact, pest

control is the main contributor to this impact (47%), followed by irrigation (27.4%), which is the

second most energy consuming process.

These two processes together are the main contributors (57%) also for the ABD impact category. The

main abiotic resources that are depleted are fossil fuels: oil (54.4%), coal (20.4%) and natural gas

(20%). Like ODP, ABD presents the highest scores in whichever process consumes the most fossil

fuels.

ADP is entirely caused by three stressors: nitrogen oxides (NOx) (49.5%), sulfur dioxide (38.4%) and

ammonia (12.1%). These chemicals are emitted to the air because of irrigation, pest control and

fertilization activities, respectively. NOx is also one stressor for ETP impact, accounting for 26%.

However, this impact is dominated with about the 53% by phosphorous (P) and phosphate (PO4-)

water emissions, mainly occurring during fertilization. In fact, this process alone is responsible for the

52.3% of the total ETP.

Both TEP and MTP are dominated by emissions generated from the frame system installation

(49.13% and 33.7%, respectively) and pest control process (23.6% for TEP, and 29.5% for MTP).

Mercury and Chromium VI contribute more than half (about 57%) of TEP environmental impacts.

These chemicals derive mostly from the background processes of steel production and manufacturing

and electricity production and distribution. The major stressors of MTP are beryllium and nickel,

emitted during the background processes of steel and fossil fuel disposal. The most problematic

process creating FWTP is found to be the understory management (58.6%), due to the glyphosate

largely used as weed-killer. For HTP, pest control and irrigation process are the main contributors,

with 31.4% and 26.6% respectively. Polycyclic aromatic hydrocarbons and arsenic are the

constituents of more concerns.

5.2 Downstream emissions

As shown in Fig.4, the most problematic process generating the major part of impacts during the

bioenergy production is the CHP operation. In fact, the direct CHP operational emissions represent

about the 73% of PCOP (largely due to SO2, benzene, toluene and CO2), the 86% of ADP and 83% of

ETP , both caused mainly by NOx and ammonia,73% of TEP (due to mercury and zinc), and 86% of

HTP (because of high emissions of polycyclic aromatic hydrocarbons).

Acquatic ecotoxicity is caused mainly by the disposal of bioashes in sanitary landfills; this process

contributes to 33.4% and 66% to the overall MTP and FWTP, respectively. Heavy metal ions, such as

beryllium, nickel, copper and vanadium, are the major stressors creating these impacts.

ABD is due to transportation (47%) and chipping and harvesting of pruning residues and cut trees

(35.4%), since they are the most energy demanding processes.

6. Foreground process inventory

Below, we report the inventory and the emissions of the main foreground processes used in the LCA

analysis.

6.1 Biomass process

Biomass production 1 yearOutputsAWRs 2.93 tonApples 11.2 tonInputs from TechnosphereSoil preparation 0.05 haFrame system 0.05 haIrrigation 1 haUnderstory management 1 haFertilization 1 haPest control 1 haWood management 1 ha

For process reference information see inventory details below

Soil preparation 1 haInputs from TechnosphereTillage, ploughing/CH U 0.05 haTillage, cultivating, chiselling/CH U 0.05 ha

Tillage, harrowing, by spring tine harrow/CH U 0.05 ha

Emissions to airAmmonia 4.60E-05 kgBenzene 1.68E-05 kgBenzo(a)pyrene 6.91E-08 kgCadmium 2.30E-08 kgCarbon dioxide, fossil 7.17E+00 kgCarbon monoxide, fossil 1.82E-02 kgChromium 1.15E-07 kgCopper 3.92E-06 kgDinitrogen monoxide 2.76E-04 kgHeat, waste 1.05E+02 MJMethane, fossil 2.97E-04 kgNickel 1.62E-07 kgNitrogen oxides 9.18E-02 kgNMVOC, non-methane volatile organic compounds, unspecified origin 4.63E-03 kgPAH, polycyclic aromatic hydrocarbons 7.58E-06 kgParticulates, < 2.5 um 1.21E-02 kgSelenium 2.30E-08 kgSulfur dioxide 2.32E-03 kgZinc 2.30E-06 kgEmissions to soilCadmium 6.82E-08 kgLead 2.98E-07 kgZinc 1.80E-04 kg

This process is based on Nemecek and Kägi [18]´s processes. See [18] for more details.

Frame system 1 haInputs from TechnosphereAnchor 32 pSteel wire Ø8mm 100 p

Steel wire Ø6mm 48 pAl-Zn wire Ø4mm 9.78 pZn-coated anchoring plate 32 pNet against hail 0.5 pPlastic clips 1,254 pConcrete poles_9*9*480 cm 32 pConcrete poles_7*7*470 cm 84.66 pPost caps_9*9*480 cm 48 pPost caps_7*7*470 cm 229.14 pTransport, lorry 3.5-16t, fleet average/RER U 1,606,441 kgkm

This process is modelled by the Authors, following data given by Laimburg experts [19] and

using Ecoinvent v2.0 processes [20]. For more details, please contact the corresponding

author.

Irrigation 1 haInputs from TechnosphereTractor, production/CH/I U 4.58E-01 kg

Agricultural machinery, general, production/CH/I U2.17E+0

1 kg

Diesel, at regional storage/CH U3.33E+0

2 kgShed/CH/I U 5.89E-02 m2

Polyethylene, HDPE, granulate, at plant/RER U2.31E+0

1 kg

Extrusion, plastic film/RER U2.42E+0

1 kg

Excavation, hydraulic digger/RER U4.00E+0

0 m3

Cast iron, at plant/RER U4.27E+0

0 kg

Electricity, low voltage, at grid/IT U1.75E+0

2kWh

Polyvinylchloride, bulk polymerised, at plant/RER U1.12E+0

0 kgDisposal, building, bulk iron (excluding reinforcement), to sorting plant/CH U 4.27E-03 kgDisposal, building, polyvinylchloride products, to final disposal/CH U 1.12E-03 kgDisposal, building, polyethylene/polypropylene products, to final disposal/CH U 6.67E-03 kg

Emissions to airAmmonia 6.64E-03 kgBenzene 2.42E-03 kgBenzo(a)pyrene 9.92E-06 kgCadmium 3.32E-06 kg

Carbon dioxide, fossil1.03E+0

3 kg

Carbon monoxide, fossil3.19E+0

0 kg

Chromium 1.66E-05 kgCopper 5.65E-04 kgDinitrogen monoxide 3.99E-02 kg

Heat, waste2.92E+0

5 MJMethane, fossil 4.29E-02 kgNickel 2.33E-05 kg

Nitrogen oxides1.70E+0

1 kg

NMVOC, non-methane volatile organic compounds, unspecified origin1.45E+0

0 kgPAH, polycyclic aromatic hydrocarbons 1.09E-03 kg

Particulates, < 2.5 um1.37E+0

0 kgSelenium 3.32E-06 kgSulfur dioxide 3.35E-01 kgZinc 3.32E-04 kgEmissions to soilCadmium 9.57E-05 kgLead 4.66E-04 kgZinc 2.38E-04 kg

Process adapted from Nemecek and Kägi [18]´s Ecoinvent v2.0 process “Irrigating/ha CH U”.

Understory management 1 haInputs fromTechnosphereSowing/CH U 0.04 haMowing, by rotary mower/CH U 2.78 haHerbicides application 0.20 haGlyphosate, at regional storehouse/CH U 2.69 kgMCPA, at regional storehouse/RER U 0.87 kgTransport, lorry 3.5-7.5t, EURO5/RER U 1300 kgkm

Emissions to air1-Butanol 6.54E-05 kgAcetic acid 3.62E-03 kgAmmonia 1.18E-03 kgBenzene 2.06E-04 kgBenzo(a)pyrene 8.44E-07 kgCadmium 2.81E-07 kgCarbon dioxide, fossil 8.89E+01 kgCarbon monoxide, fossil 1.37E-01 kgChlorine 4.38E-03 kgChloroacetic acid 3.60E-03 kgChromium 1.41E-06 kgCopper 4.79E-05 kg

Dinitrogen monoxide 3.38E-03 kgEthylene oxide 9.87E-05 kgFormaldehyde 2.23E-03 kgGlyphosate 0.135 kgHeat, waste 1.29E+03 MJMCPA 0.0434 kgMethane, fossil 3.64E-03 kgMethanol 2.09E-04 kgNickel 1.97E-06 kgNitrogen oxides 1.19E+00 kgNMVOC, non-methane volatile organic compounds, unspecified origin 9.02E-02 kgPAH, polycyclic aromatic hydrocarbons 9.27E-05 kgParticulates, < 2.5 um 9.98E-02 kgPhenol 8.34E-04 kgPhenol, 2,4-dichloro- 2.49E-04 kgPropane 6.54E-05 kgPropene 8.22E-05 kgPropionic acid 2.48E-04 kgSelenium 2.81E-07 kgSulfur dioxide 2.84E-02 kgZinc 2.81E-05 kgEmissions to water1-Butanol 1.57E-04 kgAcetic acid 9.33E-03 kgAmmonium, ion 7.69E-03 kgChloride 3.95E+00 kgChloroacetic acid 8.96E-03 kgEthylene oxide 2.37E-04 kgFluoride 2.22E-03 kgFormaldehyde 5.35E-03 kgGlyphosate 1.1069 kgMCPA 0.02597 kgMethanol 5.03E-04 kgPhenol 1.24E-03 kgPhosphorus 2.88E-02 kgPropene 1.97E-04 kgPropionic acid 5.95E-04 kgSodium, ion 2.24E+00 kgEmissions to soilCadmium 3.48E-06 kgGlyphosate 8.88E-01 kgLead 1.55E-05 kgMCPA 2.86E-01 kgZinc 9.14E-03 kg

All the sub-processes used to model this process are available in the Ecoinvent database v2.0

[13]. The process called “Herbicides application” is adapted from Nemecek and Kägi [18]´s

Ecoinvent v2.0 process “Application of plant protection products, by field sprayer/CH U”.

Fertilization 1 haInput from TechnosphereWater, process, well, in ground 10,500 kgFertilization (from Fertilization, by broadcaster/CH U) 1 haAmmonium nitrate, as N, at regional storehouse/RER U 0.083 kgSingle superphosphate, as P2O5, at regional storehouse/RER U 34.15 kgFoliar fertilization (from Application of plant protection products, by field sprayer/CH U) 1 haMagnesium oxide, at plant/RER U 0.65 kgBoric acid, anhydrous, powder, at plant/RER U 0.11 kgCalcium chloride, CaCl2, at plant/RER U 6 kgTransport, van <3.5t/RER U 46,700 kgkm

Emissions to airAmmonia 2.08E+00 kgNitrogen oxides 5.90E-01 kgDinitrogen monoxide 2.82E+00 kgMagnesium 3.22E-02 kgBoric acid 5.70E-03 kgCalcium 1.09E-01 kgChlorine 9.60E-02 kgEmissions to waterBoron 6.00E-04 kgCadmium 7.71E+01 mgCalcium 6.50E-02 kgChlorine 3.60E+00 kgChromium 2.35E+04 mgCopper 7.11E+03 mgLead 2.03E+03 mgMagnesium 1.93E-02 kgNickel 2.19E+03 mgNitrate 2.57E+01 kgPhosphorus 1.86E+00 kgZinc 3.51E+04 mgEmissions to soilBoron 2.00E-02 kgCadmium 1.54E+03 mgCalcium 7.15E-01 kgChlorine 6.30E-01 kg

Chromium 1.41E+04 mgCopper -6.15E+04 mgLead -1.26E+03 mgMagnesium 2.13E-01 kgNickel 1.69E+03 mgZinc -6.30E+04 mg

All the sub-processes used to model this process are available in [13]. The process called

“Fertilization” is adapted from Nemecek and Kägi [18]´s Ecoinvent v2.0 process

“Fertilization, by broadcaster/CH U”, as well as the process “Foliar fertilization” is modified

from “Application of plant protection products, by field sprayer/CH U”. The emissions

reported in this table refer only to the emission derived from the use of the fertilizers reported

in the process. They are calculated following [18,21].

Pest control 1 haInputs from TechnospherePesticide unspecified, at regional storehouse/RER U 3.96E+00 kgPyridine-compounds, at regional storehouse/RER U 6.75E-02 kgInsecticides, at regional storehouse/RER U 6.90E-01 kgCyclic N-compounds, at regional storehouse/RER U 1.08E-01 kgDinitroaniline-compounds, at regional storehouse/RER U 4.15E-01 kgCaptan, at regional storage/RER U 1.56E+00 kgPyridine-compounds, at regional storehouse/RER U 4.50E-01 kgInsecticides, at regional storehouse/RER U 1.07E-01 kgInsecticides, at regional storehouse/RER U 1.33E-01 kgInsecticides, at regional storehouse/RER U 6.00E-02 kgDithiocarbamate-compounds, at regional storehouse/RER U 2.14E+00 kgCopper, primary, at refinery/RER U 3.14E-01 kgInsecticides, at regional storehouse/RER U 3.60E+01 kgCyclic N-compounds, at regional storehouse/RER U 1.05E-01 kgPesticides application 1.00E+00 haTransport, van <3.5t/RER U 6.70E+03 kgkmWater, process, unspecified natural origin/kg 3.75E+04 kg

Emissions to airDithianone 1.98E-01 kgPyridine 3.38E-03 kgBupirimate 3.46E-02 kgDifenoconazole 5.40E-03 kgFluazinam 2.08E-02 kgCaptan 7.80E-02 kgCyprodinil 2.25E-02 kgImidacloprid 5.35E-03 kgSpinosad 6.65E-03 kg

Metiram 1.07E-01 kgCopper sulfate 3.94E-02 kgMineral oil 1.80E+00 kgDifenoconazole 5.25E-03 kgEmissions to waterDithianone 1.19E-01 kgPyridine 2.03E-03 kgBupirimate 2.07E-02 kgDifenoconazole 3.23E-03 kgFluazinam 1.25E-02 kgCaptan 4.68E-02 kgCyprodinil 1.35E-02 kgImidacloprid 3.21E-03 kgSpinosad 3.98E-03 kgMetiram 6.41E-02 kgCopper sulfate 2.37E-02 kgMineral oil 1.08E+00 kgDifenoconazole 3.15E-03 kgEmissions to soilDithianon 1.31E+00 kgPyridine 2.23E-02 kgBupirimate 2.28E-01 kgDifenoconazole 3.55E-02 kgFluazinam 1.37E-01 kgCaptan 5.15E-01 kgCyprodinil 1.49E-01 kgImidacloprid 3.53E-02 kgSpinosad 4.38E-02 kgMetiram 7.05E-01 kgCopper sulfate 2.60E-01 kgMineral oil 1.19E+01 kgDifenoconazole 3.47E-02 kg

All the sub-processes used to model this process are available in [18]. The emissions reported

in this table refer only to the emission derived from the use of the fertilizers reported in the

process. They are calculated following [15,16].

Wood management 1 haInputs from TechnospherePower sawing, with catalytic converter/RER U 1 hrScraper 4 hrPruning 1 ha

The sub-process “Scraper” refers to the removal of old trees. It is adapted from Nemecek and

Kägi [18]´s Ecoinvent v2.0 process “Harvesting, by complete harvester, beets/ha/CH U”. The

sub-process “Pruning” is modelled by the authors using data from [19]. For more information,

please contact the corresponding author.

6.2 Bioenergy process

Bioenergy production 1 MJuseful energy

Input from TechnosphereAWRs (from “Biomass production”) 6.61E-02 kgHarvesting pruning residues (tractor+shredder) 2.26E-05 haAWRs chopping 4.15E-02 kg

Transportation, lorry 3.5-7.5t, EURO5/RER U 5.23E-03 tkm

Lubricating oil, at plant/RER U 8.86E-06 kgAmmonia, liquid, at regional storehouse/CH U 2.22E-08 kgChemicals organic, at plant/GLO U 1.55E-05 kgChlorine, liquid, production mix, at plant/RER U 8.86E-07 kgSodium chloride, powder, at plant/RER U 1.11E-05 kgWater, decarbonised, at plant/RER U 2.13E-03 kgUrea, as N, at regional storehouse/RER U 7.96E-05 kgCogen unit ORC 1MWel, wood burning, common components for heat+electricity/CH/I U 1.49E-09 p

Cogen unit ORC 1MWel, wood burning, building/CH/I U 3.72E-10 pCogen unit ORC 1MWel, wood burning, components for electricity only/CH/I U 1.49E-09 pDisposal, used mineral oil, 10% water, to hazardous waste incineration/CH U 8.86E-06 kgDisposal, municipal solid waste, 22.9% water, to municipal incineration/CH U 8.86E-06 kgTreatment, sewage, to wastewater treatment, class 2/CH U 2.13E-06 m3

Disposal, wood ash mixture, pure, 0% water, to sanitary landfill/CH U 2.51E-03 kg

Emissions to airAcetaldehyde 1.43E-07 kgAmmonia 3.97E-05 kgArsenic 2.34E-09 kgBenzene 2.12E-06 kgBenzene, ethyl- 7.01E-08 kgBenzene, hexachloro- 4.00E-07 kgBenzo(a)pyrene 1.17E-09 kgBromine 1.40E-07 kgCadmium 1.63E-09 kgCalcium 1.37E-05 kgChlorine 4.21E-07 kgChromium 9.29E-09 kgChromium VI 9.37E-11 kgCopper 5.14E-08 kgDinitrogen monoxide 5.14E-06 kgDioxin, 2,3,7,8 Tetrachlorodibenzo-p- 7.24E-14 kgFluorine 5.47E-05 kgFormaldehyde 8.44E-07 kgHeat, waste 2.43E+00 MJHydrocarbons, aliphatic, alkanes, unspecified 2.12E-06 kg

Hydrocarbons, aliphatic, unsaturated 7.24E-06 kgLead 5.81E-08 kgMagnesium 8.44E-07 kgManganese 4.00E-07 kgMercury 3.04E-06 kgm-Xylene 2.80E-07 kgNickel 1.40E-08 kgNitrogen oxides 1.31E-04 kgNMVOC, non-methane volatile organic compounds, unspecified origin 1.43E-06 kgPAH, polycyclic aromatic hydrocarbons 2.57E-08 kgParticulates, < 2.5 um 2.57E-05 kgPhenol, pentachloro- 1.89E-11 kgPhosphorus 7.01E-07 kgPotassium 3.97E-05 kgSodium 3.04E-06 kgSulfur dioxide 5.81E-06 kgToluene 7.01E-07 kgZinc 7.01E-07 kg

This process is adapted from the Ecoinvent v2.0 database. The sub-process “AWRs (from

“Biomass production”)” refers to the Biomass production process. Depending on AWRs´

interpretation and the allocation method used for upstream emissions, we insert the specific

biomass production process (i.e: “B”, “E_Aup” and “M_Aup”). The sub-processes related to

the CHP-ORC plant are adapted from Dones et al. [20]´s processes: “Cogen unit ORC 1400

kWth, wood burning, common components for heat+electricity/CH/I U”, “Cogen unit ORC

1400 kWth, wood burning, building/CH/I U” and “Cogen unit ORC 1400 kW th, wood burning,

components for electricity only/CH/I U”.

Harvesting pruning residues (tractor+shredder) 1 haInputs from TechnosphereTractor apple orchards 1.88 hrAgricultural machinery, general, production/CH/I U 2.19 kgShed/CH/I U 0.02 m2

This sub-process is adapted from Nemecek and Kägi [18]´s Ecoinvent v2.0 process

“Harvesting, by complete harvester, beets/ha/CH U”.

Tractor apple orchards 1 hrInputs from TechnosphereTractor, production/CH/I U 0.376389 kgShed/CH/I U 2.75E-06 m2

Diesel, at regional storage/RER U 6.64 kg

Emissions to airNMVOC, non-methane volatile organic compounds, unspecified origin 1.30E-03 kg

Nitrogen oxides 2.62E-01 kg

Carbon monoxide, fossil 5.57E-03 kg

Carbon dioxide, fossil2.07E+0

1 kg

Sulfur dioxide 6.70E-03 kgMethane, fossil 8.57E-04 kgBenzene 4.87E-05 kgParticulates, < 2.5 um 0.035585 kgCadmium 6.64E-08 kgChromium 3.33E-07 kgCopper 1.13E-05 kgDinitrogen monoxide 7.99E-04 kgNickel 4.67E-07 kgZinc 6.64E-06 kgBenzo(a)pyrene 2E-07 kgPAH, polycyclic aromatic hydrocarbons 2.19E-05 kgHeat, waste 302.9903 MJAmmonia 0.000133 kgSelenium 6.64E-08 kgEmissions to soilZinc 5.29E-04 kgLead 8.9E-07 kgCadmium 2.01E-07 kg

This sub-process is adapted from Nemecek and Kägi [18]´s Ecoinvent v2.0 process

“Harvesting, by complete harvester, beets/ha/CH U”.

AWRs chopping 1 kgInputs from TechnosphereAWRs Chopper 1.33E-08 pDiesel, burned in building machine/GLO U 0.141 MJLubricating oil, at plant/RER U 0.0000512 kgSteel, low-alloyed, at plant/RER U 0.0000867 kgSynthetic rubber, at plant/RER U 0.0000794 kgBuilding machine/RER/I U 1.89E-08 p

This sub-process is adapted from Werner et al. [22]´s Ecoinvent v2.0 process “Wood

chopping, mobile chopper, in forest/kg/RER”.

AWRs Chopper 1 pInput from TechnosphereElectricity, medium voltage, production UCTE, at grid/UCTE U 720 kWhNatural gas, burned in industrial furnace >100kW/RER U 7,860 MJTransport, freight, rail/RER U 156.6 tkmTransport, lorry >16t, fleet average/RER U 78.3 tkmSteel, low-alloyed, at plant/RER U 783 kg

Emissions to airHeat, waste 2,595 MJ

This sub-process is adapted from Werner et al. [22]´s Ecoinvent v2.0 process “Chopper,

mobile, diesel/p/RER/I”.

6.3 Reference processes

Italian electricity grid mix, non-renewables 1 kWhInputs from TechnosphereElectricity, hard coal, at power plant/IT U 0.112 kWhElectricity, oil, at power plant/IT U 0.45 kWhElectricity, natural gas, at power plant/IT U 0.438 kWh

This sub-process is adapted from Dones et al. [20]´s process: “electricity, production mix

IT/kWh/IT”. We consider the fraction of electricity produced in Italy solely from non-

renewable sources [23].

Electricity, Natural gas 1kWhInputs from TechnosphereGas power plant, 100MWe/RER/I U 6.52E-11 pNatural gas, high pressure, at consumer/IT U 9.6 MJWater, decarbonised, at plant/RER U 1.92 kgWater, completely softened, at plant/RER U 0.0576 kgDisposal, residue from cooling tower, 30% water, to sanitary landfill/CH U 9.6E-06 kg

Emissions to airHeat, waste 6.96E+00 MJNitrogen oxides 6.14E-04 kgCarbon monoxide, fossil 2.88E-05 kgCarbon dioxide, fossil 5.39E-01 kgSulfur dioxide 4.80E-06 kgParticulates, < 2.5 um 4.80E-06 kgDinitrogen monoxide 9.60E-06 kgMercury 2.88E-10 kgDioxin, 2,3,7,8 Tetrachlorodibenzo-p- 2.78E-16 kgMethane, fossil 9.60E-06 kgAcetaldehyde 7.68E-09 kgBenzo(a)pyrene 5.08E-12 kgBenzene 8.89E-09 kgButane 8.89E-06 kgAcetic acid 1.16E-06 kgFormaldehyde 3.18E-07 kgPAH, polycyclic aromatic hydrocarbons 7.68E-08 kgPentane 1.10E-05 kgPropane 6.77E-06 kgPropionic acid 1.54E-07 kgToluene 1.44E-08 kgAcenaphthene 7.61E-12 kgEthane 1.32E-05 kgHexane 7.61E-06 kg

This sub-process is adapted from Dones et al. [20]´s processes: “Electricity, natural gas, at

power plant/IT U”, and “Natural gas, burned in power plant IT/U”.

7. Acronyms and abbreviations used

Table S3: Explanation of the acronyms and abbreviations used.

Acronym or abbreviation ExplanationBiomass type

ARs agricultural residuesAWRs apple woody residues

Biomass characteristicsHHV high heating valueLHV low heating valueC carbonN nitrogenP phosphorous

Biomass interpretation and allocationB AWR as by-product: cut-offE_A AWR as co-product: economic allocationM_A AWR as co-product: mass allocationO+B AWR as main product: no allocationImpact categoriesCED cumulative energy demandGWP global warming potential

Impact categories´ unitsCO2eq carbon dioxide equivalentCFC-11 eq trichlorofluoromethane equivalentC2H4 eq ethene equivalent1,4-DB eq 1,4-dichlorobenzene equivalentSbeq antimony equivalentSO2 eq sulphur dioxide equivalentPO4 eq phosphate equivalent

OthersAI active ingredientCHP combined heat and powerGHG greenhouse gasdLUC direct land use changeiLUC indirect land use change

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