TOMATOES · Web viewPost-harvest loss 1-4% Leoni, 1997 Industrial loss - tomato juice - peels and...

Supplementary material

Techno-economic and profitability analysis of food waste biorefineries at

European level

Jorge Cristóbala, Carla Caldeiraa, Sara Corradoa, Serenella Salaa,1

aEuropean Commission, Joint Research Centre (JRC), Directorate D – Sustainable Resources, Bio-economy Unit,

Via E. Fermi, 21027, Ispra (VA) – Italy.

Content

The Supplementary material is organized by product (i.e. tomato, potato, olives and orange). In the case of orange, most of the information has been given in the paper, so herein further information is included for the sake of clarity. For each product the information is organized in the following order:

- First of all, the information concerning the quantification of the food waste available, including a table with the literature and data used for the food waste estimation, the resulting Sankey diagram and the data from Prodcom.

- Secondly, information on alternative valorisation technologies, the rationale for selection and a flow diagram of the pathways selected to assess profitability

- Thirdly, the procedure for each case study to calculate the costs and the profitability ratios.

1. TOMATOES..........................................................................................................................................2

2. POTATOES.........................................................................................................................................10

3. OLIVES...............................................................................................................................................18

4. ORANGES (Further information).......................................................................................................26

References Supplementary material............................................................................................................29

1Corresponding author: [email protected]

1. TOMATOES

Food waste quantification

Table A1: Literature data used to estimate the amount of tomatoes and tomato-based products lost and wasted in EU.

Type of lossLoss percentage(referred to the input)

Reference

Post-harvest loss 1-4% Leoni, 1997Industrial loss - tomato juice - peels and seeds 5% FAO, 2011 - water 5% Mass balance Industrial loss - preserved tomatoes - peels and seeds 19.50% Leoni, 1997 - water 2% Mass balance Industrial loss - unconcentrated puree and paste - peels and seeds 13.30% Leoni, 1997 - water 1% Mass balance Industrial loss - concentrated puree and paste

- peels and seeds 9.00%Average Leoni (1997) and Unipr (2017)

- water 75% Mass balance Industrial loss - tomato ketchup and sauces

- peels and seeds 9%Average Leoni (1997) and Unipr (2017)

- water 49% Mass balance

Distribution loss - fresh tomatoes 5.80% Lebersorger and Schneider, 2014Distribution loss - manufactured tomato products 1% Assumption Consumption loss - fresh tomatoes 0.262 Vanham et al., 2015Consumption loss - manufactured tomato products 8% Rivera et al., 2014

Figure A1: Sankey diagram of the European tomato wastes (year 2015)

The European tomato production is equal to around 1.76×107 t/year and the industrial food wastes have been estimated as 1.48×106 t/year. According to Prodcom data per country, Italy and Spain are the major tomato waste producers in Europe with 64 % and 16 %, respectively.

Valorization pathway

Tomatoes are rich in bioactive and valuable compounds, such as carotenoids, mainly lycopene and β-carotene and many studies have been published in the literature concerning the extraction of those valuable compounds from tomato wastes (Mirabella et al., 2014). The most common implemented industrial process for their extraction makes use of organic solvents and presents certain weaknesses such as toxicity and flammability of some organic solvents as well as their high cost (Papaioannou et al., 2016). In order to overcome the safety issue, other alternative extraction techniques have been investigated such as microwave assisted extraction (MAE), pressurized solvent extraction (PSE), ultrasound assisted extraction (UAE), supercritical fluid extraction (SFE) and enzyme-assisted extraction, among others (Papaioannou et al., 2016). In this study, the SFE using CO2 as supercritical fluid (SFECO2) was analysed. The use of CO2 as extraction fluid allows overcoming some of the problems of the organic solvents since CO2 is not toxic or flammable, it is available at low cost and high purity, it operates at low process pressure and temperature, it can be easily separated from the extracts leaving no traces of solvent in the final product, and it is a renewable solvent (Machmudah et al., 2012; Shilpi et al., 2013). However, it presents high capital expenses and high electricity consumption during the process. Several publications have investigated the extraction of carotenoids using SCFCO2 (Vasapollo et al., 2004; Machmudah et al., 2012; Kehili et al., 2016). In this paper, for the techno-economic analysis, the biorefinery proposed by Kehili et al., (2016) in Fig. A2 was used as a model for scaling the results.

Figure A2: Flow diagram of the tomato waste biorefinery (Kehili et al., 2016).

Costs and profitability calculations

In Kehili et al., (2016) the feedstock of the process is the residue from a processing plant of peeled tomato consisting on tomato peels and seeds. The residues are dried (under sunlight when possible or using solar assisted technology) until a dry matter content of around 95%. The dried residue, consisting of 35% of tomato seeds (TS) and 65% of tomato peels (TP) on dry basis, is separated, then ground using a conventional grinder to a maximum particle size of 300 µm and cooled till -20 °C. This feedstock, enters a stainless steel extraction column, in which compressed CO2 is fed continuously being the extractor maintained at the operating pressure of 400 bar and temperature of 80 °C. 10 g of ground tomato biomass was loaded and the flow of CO2 is 4 gCO2/min for 2 h. Results show an extraction yield of almost 60% of the lycopene form TP and 82.2% from TS. Regarding b-carotene, the extraction yield is 58.8% from TP and 90% from TS.

First of all, the ISBL (in €) must be calculated using the Bridgwater’s correlation in Eq. 1 and Eq. 2 (in the paper). In this case, the number of function units (N) is equal to 6 as shown in Error:Reference source not foundA2 (in the paper) (i.e. separation, grinding, supercritical extraction, CO2 compression, refrigeration and purification).

The throughput (Q/s) used for the ISBL calculation of a single biorefinery plant is the dry throughput calculated as shown in Eq. A1.

( Qs )= Total residues

Number of plants∗dry matter content (A1)

Where dry matter content of the tomato residue is 298.4 g/kg considering that the water content of the tomato residue is 738.5 g/kg (Kalogoropoulos et al., 2012) and enter the biorefinery after the drying process (95% dry matter).

Then, considering that the extraction process is a solid-fluid process, the FCI and the TCI are calculated using the values reported in Perry and Green (1999) and the middle vales for working capital and start-up expenses. Results are shown in Error: Reference source not foundA2.

Table A2: Investment costs for the tomato waste biorefinery

Number of plants

One Plant(Q/s) [x1000 t/year]

One Plant dry (Q/s) [x1000 t/year]

One Plant ISBL [×107EUR]

One Plant FCI[×107EUR]

One Plant TCI[×107EUR]

All plants FCI[×108EUR]

All plants TCI[×108EUR]

7 211.18 63.02 1.34 3.09 3.88 2.16 2.7114 105.59 31.51 1.23 2.83 3.55 3.96 4.9721 70.39 21.01 1.19 2.74 3.44 5.76 7.2228 52.80 15.76 1.17 2.70 3.38 7.56 9.4735 42.24 12.60 1.16 2.67 3.35 9.35 11.742 35,20 10.50 1.15 2.65 3.33 11.1 14.049 30.17 9.00 1.15 2.64 3.31 12.9 16.256 26.40 7.88 1.14 2.63 3.30 14.7 18.563 23.46 7.00 1.14 2.63 3.29 16.5 20.770 21.12 6.30 1.14 2.62 3.28 18.3 23.0

For the calculation of the COM for one biorefinery plant (Eq. 3) (in the paper), the five elements present in the equation must be estimated:

1. The FCI has been already calculated as shown in Error: Reference source not found.2. For COL (in EUR/year) the NOL as shown in Eq. 4 (in the paper) must be calculated and

then multiplied by the yearly salary of each operator. In this case, the number of processing steps involving the handling of particulate (P) is equal to 2 (i.e. charge and discharge of the extraction vessels) and the number of non-particulate processing steps Nnp equals 8 (i.e. separator, grinder, extraction vessel, back pressure regulator, refrigeration, high pressure pump CO2, CO2 flow meter and purification unit). Solving the equation gives a value of NOL equal to 11.62 that is the number of operators required to run the process unit per shift. Considering that each operator works 49 weeks a year, five 8-hour shifts a week. This leads to 245 shifts per operator per year. Since the chemical plant operate 24 hours/day, this requires 1095 operating shifts per year (i.e. 3 shifts/day x 365 days/year). Thus, the number of operators needed to provide this number of shifts is approximately 4.5 operators. The needed operating labor, without including any support or supervision staff, is equal to (4.5x11.62=52.18) 53 operators per plant. The COL for one plant is equal to 2.65×106 EUR/year.

3. As mentioned in the previous section the CWT is considered negligible in this case since wastes can be utilized further downstream in the biorefinery process.

4. The CRM (see Table A1) is calculated as the sum of four components:a. The cost of the biomass, in this case, is considered zero since it is a waste from an

industrial process that otherwise should be properly managed and disposed. b. The cost of the pre-processing steps, that in this case is the drying process of the

biomass before entering the biorefinery. Sometimes in literature, this cost is

neglected because solar drying is used (with no energy input needed) (Kehili et al., 2016). But since this is a European case study and not all countries have the solar conditions for drying the whole raw material using sunlight, a solar assisted technology has been used (Karabacak and Atalay, 2010). The specific moisture extraction rate (SMER) of this technology is around 1.4 kg water/kWh. The cost in EUR per year is calculated to dry the tomato residues till 5% moisture (this is around 0.7 kg water/kg tomato) and considering that the cost of electricity is 0.125 EUR/kWh (EUROSTAT, 2017c).

c. The price for the chemicals and reactants used. In this case, the only chemical product used is the CO2, but this cost is negligible since CO2 is recovered in the plant and the CO2 lost is minimum.

d. Finally, the price for the transport of the biomass. The biomass can be transported before or after drying. In this case it is considered that the wastes are transported after the drying process. A linear function (Eq. A2) calculated from the maximum transport scenario (with 7 plants located in Spain supplied by Spanish and Portuguese wastes and Italy supplied by Italian and other countries’ wastes) and the minimum transport scenario (with 70 plants) has been used for calculating the transport distances (in tkm) depending on the number of plants. Then, the transport value for one plant is calculated considering that the unitary transport cost is 0.14 EUR/tkm.

Distance (¿ tkm )=−1×106∗N plants+2× 108 (A2)

Table A1: Cost of raw material for the tomato waste biorefinery

Number of plants

dry (Q/s) [x1000 t/year]

Drying cost One plant [×106

EUR/year]

Transport cost One Plant[×105

EUR/year]

CRM

One plant[×106

EUR/year]7 63.02 13.2 38.6 17.114 31.51 6.61 18.6 8.4721 21.01 4.41 11.9 5.6028 15.76 3.31 8.60 4.1735 12.60 2.65 6.60 3.3142 10.50 2.20 5.27 2.7349 9.00 1.89 4.31 2.3256 7.88 1.65 3.60 2.0163 7.00 1.47 3.04 1.7770 6.30 1.32 2.60 1.58

5. For the CUT calculation (Table A2), according to Attard et al., (2015), three main cost are involved:

a. Costs associated with the electric power used in the CO2 pump. The same conditions of the experiments in Kehili et al., (2016) are maintained. The specific enthalpy of CO2 using a pressure of 400 bar and 80 °C is 341.8 kJ/kgCO2. Each

batch will take 2 h, so considering that the plant is operating 8760 h per year, 4380 batches will take place in a year. The load of tomato residue per batch will depend on the annual dry throughput of the plant (depending on the number of plants installed) and therefore this will also determine the flow of CO2 that will be needed per hour (considering 0.4 gCO2/g of residue min). The cost of electricity is considered to be 0.125 EUR/kWh (EUROSTAT, 2017c).

b. Costs associated with the CO2 heater. The CO2 has to be heated from 4°C to 80°C. The flow of CO2 per hour (M) depends on the dry throughput of the plant as mentioned before and the Cp (the specific heat capacity of CO2 at 80°C) is equal to 0.895 kJ/kgK and the variation of temperature is 76 °C. Therefore, the heat required in MJ, is calculated with Eq. A3 assuming 50% efficiency. The price of the MJ (from Natural Gas) for industrial consumers is 0.0083 EUR/MJ (EUROSTAT, 2017d).

Q=M C p ∆ Tefficiency

(A3)

c. Costs associated with refrigeration. The refrigeration cycle comprises a working fluid (in this case water) that has to be cooled from 20 °C to 4 °C. The Coefficient of performance (COP) at 20 °C and 4 °C is 0.08 and 0.15, respectively. The energy required (in MJ) for the refrigeration of the CO2 (M) is given by Eq. A4 considering Cp of CO2 at 27 °C equal to 0.846 KJ/kg. The refrigeration requires electrical power which price is 0.125 EUR/kWh.

Q=M Cp ∆T COP 4 ° CCOP 20 °C (A4)

Table A2: Cost of utilities for the tomato waste biorefinery

N of plants

dry (Q/s)[x1000 t/year]

CO2 Pump One Plant[×106

EUR/year]

CO2 Heater One Plant[×105

EUR/year]

Refrigeration One Plant[×105

EUR/year]

CUT

One Plant[×106

EUR/year]7 63.02 35.9 34.3 26.7 42.014 31.51 18.0 17.1 13.3 21.021 21.01 12.0 11.4 8.89 14.028 15.76 8.98 8.57 6.66 10.535 12.60 7.18 6.86 5.33 8.4042 10.50 5.98 5.72 4.44 7.0049 9.00 5.13 4.90 3.81 6.0056 7.88 4.49 4.29 3.33 5.2563 7.00 3.99 3.81 2.96 4.6770 6.30 3.59 3.43 2.67 4.20

Finally, once all the five elements have been estimated, the COM can be calculated for one plant using Eq. 3 (in the paper) and the COM for all plants multiplying the COM by the number of plants (see Table A3).

Table A3: Cost of manufacturing for the tomato waste biorefinery

Number of plants

COM One Plant[×107 EUR/year]

COM All Plants[×108 EUR/year]

7 8.86 6.2014 5.14 7.2021 3.90 8.1928 3.28 9.1935 2.91 10.242 2.66 11.249 2.49 12.256 2.35 13.263 2.25 14.270 2.17 15.2

For the calculation of the revenues obtained with the extraction of the lycopene and the b-carotene from the tomato residues, first of all the quantity of product extracted must be estimated assuming that the extraction efficiency reported in Kehili et al., (2016) is maintained. Taking into account the tomato residue composition reported by Kalogoropoulos et al., (2012) the dry solids content at 95% is equal to 298.4 g/kg of tomato. Kehili et al., (2016) reported a quantity of tomato seeds (TS) and tomato peels (TP) in 1 kg of tomato residue equal to 104.5 gTS/kg tomato residue (35% of the dry basis) and 194 gTP/kg tomato residue (65% of the dry basis) and the extraction efficiencies for lycopene and b-carotene as shown in Table A4.

Table A4: Extraction efficiency in the tomato waste biorefinery

Lycopene from TP 410.53 mg lycopene/kg dry TPLycopene from TS 27.84 mg lycopene/kg dry TSbeta-carotene from TP 31.38 mg b-carotene/kg dry TPbeta-carotene from TS 5.25 mg b-carotene/kg dry TS

Being the total production of lycopene equal to 36413.3 kg/year and the production of beta-carotene equal to 2927.2 kg/year. In order to calculate the total revenues, those quantities must be multiplied by the price of those products in the market. Several prices (EUR/kg) are found in literature (Ciriminna et al., 2016; Washam, 2005) and in the actual market (MERCK, 2017) for those products and since it is very variable and uncertain, within this study three scenarios are tested (i.e. low, medium and high prices) as shown in Table A5.

Table A5: Price (EUR/kg) scenarios for the tomato waste biorefinery products

Product Low Medium Highlycopene 4×103 4×104 4×105

b-carotene 4×102 4×103 4×104

Thus, the total revenues obtained for the Low, Medium and High scenarios are 1.47×108, 1.47×109 and 1.47×1010 EUR/year, respectively. The profitability ratios (i.e. ROI and Payback time) for the three price scenarios are calculated (Table A6).

Table A6: ROI and payback time for the tomato waste biorefinery scenarios

Number of plants

ROI (%) Payback time (years)Low Medium High Low Medium High

7 -1.22 2.19 36.28 -0.82 0.46 0.0314 -0.81 1.06 19.68 -1.24 0.95 0.0521 -0.65 0.63 13.44 -1.53 1.59 0.0728 -0.57 0.41 10.17 -1.75 2.46 0.1035 -0.52 0.27 8.16 -1.92 3.73 0.1242 -0.49 0.18 6.79 -2.05 5.71 0.1549 -0.46 0.11 5.81 -2.16 9.28 0.1756 -0.44 0.06 5.06 -2.25 17.60 0.2063 -0.43 0.02 4.48 -2.33 58.95 0.2270 -0.42 -0.02 4.01 -2.40 -66.33 0.25

2. POTATOES


Table A9: Literature data used to estimate the amount of potatoes and potato-based products lost and wasted in EU.

Type of lossLoss percentage (referred to the input)

Reference

Post-harvest loss 12% JRC database Over-production 9% Willersinn et al., 2015Industrial loss - frozen potatoes, uncooked or cooked by steaming or boiling in water - peels 8% Somsen, 2004 - other loss 22% Assumption Industrial loss - frozen potatoes, prepared or preserved - peels 8% Somsen, 2004 - other loss 29% Somsen, 2004Industrial loss - dried potatoes whether or not cut or sliced but not further prepared - peels 8% Somsen, 2004

- other loss 75%Mass balance (production yield from Marwaha et al., 2010)

Industrial loss - dried potatoes in the form of flour, meal, flakes, granules and pellets - peels 8% Somsen, 2004


Industrial loss - potatoes prepared or preserved in the form of flour, meal or flakes - peels 8% Somsen, 2004


Industrial loss - potatoes prepared or preserved, including crisps - peels 8% Somsen, 2004


Industrial loss - potato starch - peels 8% Somsen, 2004


Starch used in the paper industry 70% van Holsteijn et al., 2017Distribution loss - fresh potatoes 2% JRC database Distribution loss - manufactured tomato products 1% Willersinn et al., 2015Consumption loss - fresh tomatoes 36% JRC database

Consumption loss - manufactured tomato products 3%

Figure A3: Sankey diagram of the European potato wastes (year 2015)

The European potato production is equal to around 5.36×107 t/year and the industrial food losses and wastes that correspond to the potato peels (PP) have been estimated as 2.34×106 t/year. The major potato waste producers according to Prodcom are Netherlands, Germany and UK with 36%, 25% and 11.5%, respectively.


Potato wastes can be valorised through different pathways such as animal feed and fertilizer (Pathak et al., 2017), biogas production via anaerobic digestion (Wu, 2016; Phatak et al., 2017), ethanol production (Arapoglou et al., 2010), lactic acid production (Wu, 2016), and natural antioxidants extraction (Wu, 2016; Pathak et al., 2017). This study focused on the extraction of value-added products such as phenolic acids due to their possible use in the food industry as food preservatives (Akyol et al., 2016) and glycoalkaloids that can be used in the pharmaceutical industry (Maldonado et al., 2014). Traditionally, antioxidants from potato peels are extracted using organic solvents, even though they present some disadvantages such as the need for longer extraction times or high toxicity. Mixtures of water and ethanol are alternatives for the recovery of phenolic compounds from potato peels facilitating food applications (Kannat, et al., 2005; Onyeneho and Hettiarachchy, 1993; Singh and Rajini, 2004). On the other hand, glycoalkaloids from potatoes are traditionally extracted with chloroform/methanol mixtures (Bushway & Ponnampalam, 1981; Friedman et al., 2003) but this method is detrimental for the environment (Maldonado et al., 2014). Water/acetic acid mixtures have been used to extract glycoalkaloids (Friedman et al., 2003; Machado et al., 2007; Sotelo and Serrano, 2000) as well. In this paper, the techno-economic analysis of a low pressure solid-liquid extraction (Meireles, 2009) using a mixture of water and ethanol (H2O+EtOH) with acetic acid was done using the biorefinery data from Maldonado et al. (2014). The flow diagram of the process is presented in Fig A4. Six different products are recovered, three phenolic acids, i.e. neochlorogenic, chlorogenic and caffeic acids and three glycoalkaloids, i.e. alfa-chaconine, alfa-solanine and solanidine.

Fig. A4 Flow diagram of the potato waste biorefinery. EtOH – Ethanol


In this study, the techno-economic and profitability analysis of a low pressure solid-liquid extraction (Meireles, 2009) using the biorefinery data from Maldonado et al., (2014) is done. In the biorefinery plant, the feedstock is crushed and mixed with the solvent in the extraction vessel (with a batch time of 1.3 h). The solvent used contains 46% water, 51% ethanol and 3% acetic acid. Then the solvent is evaporated and there is a fractionation of the phenolic acids and glycoalkaloids. Six different products are recovered. Three phenolic acids, i.e. neochlorogenic, chlorogenic and caffeic acids and three glycoalkaloids, i.e. alfa-chaconine, alfa-solanine and solanidine.

First of all, the ISBL (in €) must be calculated using the Bridgwater’s correlation in Eq. 1 and Eq. 2 (see Table A9). In this case, N equals 5 (i.e. crashing/sizing, blending/extraction, evaporation, condensation and fractionation). For the PP there is no need for drying and the throughput (Q/s) used for the ISBL calculation of a single biorefinery plant is calculated as shown in Eq. A5.

( Qs )= Total residues

Number of plants (A5)

Then, considering that the extraction process is a solid-fluid process, the FCI and the TCI are calculated using the values reported in Perry and Green (1999) and middle vales for working capital and start-up expenses. Results are shown in Table A7.

Table A7: Investment costs for the potato waste biorefinery

Number of plants

(Q/s)[x1000 t/year]

One Plant ISBL[×107EUR]





7 334.42 1.94 4.46 5.59 3.12 3.9214 167.21 1.44 3.30 4.14 4.62 5.7921 111.47 1.27 2.91 3.65 6.12 7.6728 83.61 1.18 2.72 3.41 7.62 9.5535 66.88 1.13 2.60 3.26 9.11 11.442 55.74 1.10 2.53 3.17 10.6 13.349 47.77 1.07 2.47 3.10 12.1 15.256 41.80 1.06 2.43 3.05 13.6 17.163 37.16 1.04 2.40 3.01 15.1 18.970 33.44 1.03 2.37 2.97 16.6 20.8

For the calculation of the COM for one biorefinery plant (Eq. 3 in the paper), the five elements present in the equation must be estimated:

1. The FCI has been already calculated as shown in Table A7.2. For COL (in EUR/year) the NOL as shown in Eq. 4 (in the paper) must be calculated and

then multiplied by the yearly salary of each operator. In this case, P (i.e. the number of processing steps involving the handling of particulate) is equal to 2 (i.e. charge and discharge of the extraction vessels) and Nnp (i.e. the number of non-particulate processing steps) equals 7 (i.e. crusher, agitation tank, extraction vessel, filtration unit, evaporator, condenser and purification unit). Solving the equation gives a value of NOL equal to 11.6 that is the number of operators required to run the process unit per shift. The number of operators needed to provide this number of shifts is approximately 4.5 operators (for 365 days of operation 24 hours). The needed operating labor, without including any support or supervision staff, is equal to (4.5x11.6=52.2) 53 operators per plant. The COL for one plant is equal to 2.65×106 EUR/year.

3. The CWT is considered negligible case since wastes can be utilized further downstream in the biorefinery process.

4. The CRM (see Table A8) is calculated as the sum of the following components:a. The cost of the biomass and the cost of the pre-processing, in this case, are

considered as zero since it is a waste from an industrial process and no drying is needed.

b. The price for the chemicals and reactants used. For its calculation, first of all the number of batches per year have to be calculated. It is considered that the solvent extraction plant will operate 365 days – 24 h. This time is divided by the batch time which is 1.3 hours, giving 6738 batches per year. For calculating the quantity of solvent used during the whole year, the densities and costs of the raw material components are obtained from Meireles (2009) and Turton et al., (2008). The density of water, ethanol and acetic at 298 K are 994.7 kg/m3, 785.89 kg/m3, and 1049 kg/m3, respectively. And their prices are 0.0009 EUR/kg, 0.429 EUR/kg,

0.91 EUR/kg, respectively. The solvent to solid ratio reported in Maldonado et al., (2014) is 0.4 g of potato peel per mL. The quantities of solvent obtained for the first batch cannot be multiplied for the price, since the solvent is recycled for further uses in the same process. It was considered a 10% of ethanol and acetic acid loss and a 5% of water loss. The total cost is calculated multiplying the quantities in the first batch plus the quantities lost annually by their prices.

c. Finally, the price for the transport of the biomass. A linear function (Eq. A6) calculated from the maximum transport scenario (with 7 plants located in Netherlands, Germany, Italy and UK) and the minimum transport scenario (with 70 plants) has been used for calculating the transport distances (in tkm) depending on the number of plants. Then, the transport value for one plant is calculated considering that the unitary transport cost is 0.14 EUR/tkm.

Distance (¿ tkm )=−5× 106∗N plants+7 ×108 (A6)

Table A8: Cost of raw materials for the potato waste biorefinery

Number of plants

(Q/s)[x1000 t/year]

Chemicals cost One Plant [×106EUR/year]

Transport cost One Plant[×106EUR/year]

CRM

One Plant[×106EUR/year]

7 334.42 16.8 13.3 30.114 167.21 8.41 6.30 14.721 111.47 5.60 3.97 9.5728 83.61 4.20 2.80 7.0035 66.88 3.36 2.10 5.4642 55.74 2.80 1.63 4.4449 47.77 2.40 1.30 3.7056 41.80 2.10 1.05 3.1563 37.16 1.87 0.86 2.7270 33.44 1.68 0.70 2.38

5. For the CUT calculation (Table A9), according to Meireles (2009), two main cost are involved: the costs of the heat required for the evaporator and the cost of cooling water (including the water needed plus the water makeup, the chemicals added to reduce the tendency of the water to foul heat-exchanger surfaces within the process and the electricity to pump the water (Turton et al., 2008)).

a. The costs of the heat required for the evaporator. The heat (Q) in MJ necessary to evaporate the solvent (M measured in kg and composed of water, ethanol and acetic acid) from the extract solution is calculated as shown in Eq. A7, considering both the increase of their temperature (T) from 298 K to the normal boiling points of water, ethanol and acetic acid (373.15 K, 351.4 K, and 391.2 K, respectively) and the additional heating that would be necessary to promote the phase change. The heat of vaporization (∆ H v) related to the phase change for water, ethanol and acetic acid are 42306.7 J/gmol, 38930.56 J/gmol, and 41600

J/gmol, respectively. The heat capacity (Cp) of the liquids is for water, ethanol and acetic acid, 75.25 J/gmolK, 113 J/gmolK and 123.1 J/gmolK, respectively.

Q=M Cp ∆T +M ∆ H v (A7)

The cost of the MJ is 0.0083 EUR/MJ (i.e. 0.03 EUR/kWh) (EUROSTAT, 2017d).

b. The costs associated with the cooling water. First of all, the quantity of cooling water needed per batch per year (M) measured in kg is calculated using Eq. A8. It is considered that the water enters the equipment at 303 K and leave it at 313 K, and that the specific heat (Cp) of water is 4.18 kJ/kgK.

M= QCp ∆ T (A8)

This calculation allows obtaining the quantity of water needed per batch and per year. However, since the water is recycled for the same process, the quantity lost (evaporated) must be calculated. The latent heat of water at the average temperature of 35 °C is 2417 kJ/kg (Turton et al., 2008). Then the quantity of water evaporated is calculated dividing the heat load (Q) by this value. The cost of the water needed will be the first batch plus the water needed to replace the evaporated one multiplied by its unitary price (i.e. 6.01×10-5 EUR/kg water) (Meireles, 2009; Turton et al., 2008). We have to add the price of the chemicals to treat the makeup water which price is 1.4×10-4 EUR/kg makeup water (Turton et al., 2008). Moreover, the cost of the electricity used for pumping the water must be added. The pump power is calculated as in Turton et al., (2008) and multiplied by the price of the electricity (0.125 EUR/kWh (EUROSTAT, 2017c)).

Table A9: Cost of utilities for the potato waste biorefinery

N of plants

(Q/s) [x1000 t/year]

Heat Evap. Cost One Plant[×106

EUR/year]

Cooling water cost One Plant[×103

EUR/year]

Chemicals cost One Plant[×103

EUR/year]

Pump Energy Cost One Plant[×103

EUR/year]

CUT One Plant[×106

EUR/year]

7 334.42 11.4 34.5 34.5 64.9 11.514 167.21 5.70 17.3 17.2 32.5 5.7721 111.47 3.80 11.5 11.5 21.6 3.8528 83.61 2.85 8.63 8.62 16.2 2.8835 66.88 2.28 6.90 6.90 13.0 2.3142 55.74 1.90 5.75 5.75 10.8 1.9249 47.77 1.63 4.93 4.93 9.28 1.6556 41.80 1.43 4.32 4.31 8.12 1.4463 37.16 1.27 3.84 3.83 7.22 1.2870 33.44 1.14 3.45 3.45 6.49 1.15

Finally, once all the five elements have been estimated, the COM can be calculated for one plant using Eq. 3 (in the paper) and the COM for all plants multiplying the COM by the number of plants (see ).

Table A10: Cost of manufacturing for the potato waste biorefinery

N of plants COM One Plant[×107EUR/year]

COM All Plants[×108EUR/year]

7 7.10 4.9714 4.17 5.8321 3.19 6.7028 2.70 7.5635 2.41 8.4342 2.21 9.2949 2.07 10.256 1.97 11.063 1.89 11.970 1.82 12.8

For the calculation of the revenues obtained with the extraction of the 3 phenolic acids and 3 glycoalkaloids from the PP, first of all the quantity of product extracted must be estimated assuming that the extraction efficiency reported in Maldonado et al., (2014) is maintained (see Table A11).

Table A11: Extraction efficiency in the potato waste biorefinery

Product Recovery efficiency

Unit

Neochlorogenic acid 13.3 mg /100 g of PP fresh weightChlorogenic acid 77.6 mg /100 g of PP fresh weightcaffeic acid 7.8 mg /100 g of PP fresh weightalfa-chaconine 17 mg /100 g of PP fresh weightalfa-solanine 7.1 mg /100 g of PP fresh weightsolanidine 0.1 mg /100 g of PP fresh weight

The total extraction of all products summed together equals to 2806807.44 kg/year. Several prices are found in the actual market (MERCK, 2017) for those products spanning from 6.05 EUR/g of caffeic acid to 1.3×105 EUR/g of solanidine. Since they are so uncertain and volatile, again three scenarios (i.e. low, medium and high prices) as shown in Table A12 are tested, considering that all products have the same price.

Table A12: Price (EUR/kg) scenario for the potato biorefinery products

Low Medium High30 300 3000

Thus, the total revenues obtained for the Low, Medium and High scenarios are 8.42×107, 8.42×108 and 8.42×109 EUR/year, respectively. The profitability ratios (i.e. ROI and Payback time) for the three price scenarios are calculated (Table A13).

Table A13: ROI and payback time for the potato waste biorefinery scenarios

N of plants ROI (%) Payback time (years)Low Medium High Low Medium High

7 -0.74 0.62 14.17 -1.36 1.62 0.0714 -0.60 0.31 9.47 -1.66 3.20 0.1121 -0.53 0.16 7.07 -1.87 6.36 0.1428 -0.49 0.06 5.62 -2.03 15.92 0.1835 -0.46 0.00 4.64 -2.15 -1910.55 0.2242 -0.44 -0.05 3.94 -2.25 -21.74 0.2549 -0.43 -0.08 3.41 -2.33 -12.47 0.2956 -0.42 -0.11 3.00 -2.39 -9.35 0.3363 -0.41 -0.13 2.67 -2.45 -7.79 0.3770 -0.40 -0.15 2.40 -2.50 -6.86 0.42

3. OLIVES


Table A16: Literature data used to estimate the amount of olives and olive oil lost and wasted in EU.

Type of loss Loss percentage Reference(referred to the input)

Post-harvest loss n.c.Industrial loss - preserved olives 1% Assumption Industrial loss - olive oil - Olive mill waste (OMW) 30% Tekerlekopoulou et al., 2017 - Olive mill waste water (OMWW) 50% Tekerlekopoulou et al., 2017Distribution loss - preserved olives 1% Assumption Distribution loss - olive oil 1% Assumption Consumption loss (avoidable) - preserved olive 4% WRAP 2012 (considered equal to

oils)Consumption loss (unavoidable) - preserved olive 16% INRAN, 2013

Consumption loss - olive oil 4% WRAP 2012

Figure A5: Sankey diagram of the European olive wastes (year 2013)

The European olive production is equal to around 1.42E7 t/year. There are three main olive processing technologies (i.e. the traditional olive-pressing process, the three-phase and the two-phase extraction process). The majority of olive mills utilize the three-phase centrifugation system (Schievano et al., 2015) that produce two types of waste: olive mill wastewater (OMWW) and the olive mill waste (OMW) (Souilem et al., 2017). The three-phase process usually yields 10-20% olive oil, 30% OMW, and 50-60% OMWW (i.e. 4 times more waste is produced than the actual product) (Tekerlekopoulou et al., 2017; Doula et al., 2017). In this study, only the OMW is considered as feedstock for the biorefinery process, being the quantity

estimated 4.1×106 t/year. According to Prodcom data per country, Spain and Italy are the major olive waste producers in Europe with 71.5 % and 19 %, respectively.


For the olive mill waste (OMW), several valorization options appear in literature including recovery of high-added value compounds, production of absorbents, use the OMW as soil amendment for land application, direct combustion for energy, and biofuel production (biohydrogen, methane, biodiesel and bioethanol) (Roig et al., 2006; Kalderis and Diamadopoulos, 2010; Romero-Garcia et al., 2014; Kourmentza et al., 2017). Several techniques have been proposed in literature to recover phenols and other valuable compounds from OMW including solvent extraction, membrane systems, SFE, UAE, MAE and subcritical water extraction (Galanakis and Kotsiou, 2017). SFE present several advantages compared to the conventional ones such as higher selectivity, shorter extraction times and lower consumption of toxic organic solvents (Lozano-Sanchez et al., 2014), but the main issue with SFE using CO2

(SFECO2) is the limited use on low or medium polarity compounds due to the low polarity of CO2 (Schievano et al., 2015). As shown by Cardoso et al. (2013), SFECO2 alone is not sufficient to achieve satisfactory extraction of the polyphenols and the addition of ethanol (EtOH) as a co-solvent improves the extraction yield. On the other hand, EtOH addition makes the extract being moistier (i.e. more energy requirements to dry the extract, as compared to CO2 alone). In this paper, the techno-economic analysis of a SFECO2 with EtOH as cosolvent using the biorefinery data from Schievano et al., (2015) was done (Fig. A6). The main products obtained from the biorefinery are phenolic compounds (mainly hydroxytyrosol) that can be used in the food, cosmetic and pharmaceutical industries, fatty acids methyl ester (FAME) used for biodiesel production, and squalene that is an intermediate metabolite in the synthesis of cholesterol and phytosterols that can be used in the food and pharmaceutical industries.

Fig. A6. Flow diagram of the olive waste biorefinery


In this study, the techno-economic and profitability analysis of a SFECO2 with EtOH as cosolvent using the biorefinery data from Schievano et al., (2015) is done. One of the value-added products obtained from the biorefinery are phenolic compounds (mainly hydroxytyrosol) that can be used in the food, cosmetic and pharmaceutical industries. Other valuable products extracted are unsaturated fatty acids (UFA) and squalene that is an intermediate metabolite in the synthesis of cholesterol and phytosterols.

The extractions were performed on samples of fresh raw OMW. Extracting conditions were 250 bar, 70 °C, a CO2 flow rate of 80 kg/h and the extraction time was 480 min. Ethanol was added to the biomass in the ratio of 20% w/w, corresponding to a ratio of 0.25% w/w EtOH-CO2. After extraction, concentrated extracts were freeze –dried.

First of all, the ISBL (in €) must be calculated using the Bridgwater’s correlation in Eq. 1 and Eq. 2 (in the paper). In this case the number of function units (N) is equal to 5 (i.e. supercritical extraction, CO2 compression, refrigeration, ethanol recovery and drying).

For the OMW there is no need for drying before entering the extraction and the throughput (Q/s) used for the ISBL calculation of a single biorefinery plant is calculated as shown in Eq. A5. Then, considering that the SFECO2 is a solid-fluid process, the FCI and the TCI are calculated using the values reported in Perry and Green (1999)Error: Reference source not found and middle vales for working capital and start-up expenses. Results are shown in Table.

Table A17: Investment costs for the olive waste biorefinery

N of plants


One Plant ISBL[×107EUR]





7 579.14 2.68 6.16 7.72 4.31 5.4114 289.57 1.80 4.15 5.20 5.81 7.2821 193.05 1.51 3.48 4.36 7.31 9.1628 144.79 1.37 3.15 3.94 8.81 11.035 115.83 1.28 2.94 3.69 10.3 12.942 96.52 1.22 2.81 3.52 11.8 14.849 82.73 1.18 2.71 3.40 13.3 16.756 72.39 1.15 2.64 3.31 14.8 18.563 64.35 1.12 2.59 3.24 16.3 20.470 57.91 1.11 2.54 3.19 17.8 22.3

For the calculation of the COM for one biorefinery plant (Eq. 3 in the paper), the five elements present in the equation must be estimated:

1. The FCI has been already calculated as shown in Table.2. For COL (in EUR/year) the NOL as shown in Eq. 4 must be calculated and then multiplied

by the yearly salary of each operator. In this case, the number of processing steps involving the handling of particulate (P) is equal to 2 (i.e. charge and discharge of the

extraction vessels) and the number of non-particulate processing steps Nnp equals 7 (i.e. extraction vessel, back pressure regulator, refrigeration, high pressure pump CO2, CO2 flow meter, evaporator and drying unit). Solving the equation gives a value of NOL equal to 11.6 that is the number of operators required to run the process unit per shift. Considering that each operator works 49 weeks a year, five 8-hour shifts a week. This leads to 245 shifts per operator per year. Since the chemical plant operate 24 hours/day, this requires 1095 operating shifts per year (i.e. 3 shifts/day x 365 days/year). Thus, the number of operators needed to provide this number of shifts is approximately 4.5 operators. The needed operating labor, without including any support or supervision staff, is equal to (4.5x11.6=52.2) 53 operators per plant. The COL for one plant is equal to 2.65×106 EUR/year.

3. As mentioned in the previous section the CWT is considered negligible since the wastes could be further used in the biorefinery (for example in pyrolysis or combustion as shown by Schievano et al., (2015)). Besides, the extraction of polyphenols mitigates the phytotoxicity of OMW enabling the more widespread use as a soil amendment. In Greece, the exhausted OMW has a market value of 0.05 EUR/kg (MORE, 2010).

4. The CRM (see ) is calculated as the sum of four components:a. The cost of the biomass, in this case, is considered zero since it is a waste from an

industrial process that otherwise should be properly managed and disposed. b. The cost of the pre-processing steps, that in this case is zero since there in no need

of a drying process of the biomass before entering the biorefinery. c. The cost of raw materials that includes the price for the CO2 and EtOH used as a

co-solvent. CO2 is fully recovered in the plant and the CO2 lost is minimum. Some EtOH is lost in the recovery process (around a 10% per batch). In order to calculate the cost of EtOH used in the biorefinery, the quantity of EtOH per batch is calculated considering that 20% (w/w biomass) is used and that 10% has to be replaced every batch. The price for the EtOH is considered 0.85 EUR/kg (Turton et al., 2008).

d. Finally, the price for the transport of the biomass. A linear function (Eq. A9) calculated from the maximum transport scenario (with 7 plants located in Spain supplied by Spanish and Portuguese wastes and Italy supplied by Italian and other countries’ wastes) and the minimum transport scenario (with 70 plants) has been used for calculating the transport distances (in tkm) depending on the number of plants. Then, the transport value for one plant is calculated considering that the unitary transport cost is 0.14 EUR/tkm.

Distance (¿ tkm )=−4 ×106∗N plants+1× 109 (A9)

Table A18: Cost of raw materials for the olive waste biorefinery

Number of plants


ChemicalsCost [×106EUR/year]

TransportCost[×106EUR/year]

CRM One Plant[×106EUR/year]

7 579.14 9.96 19.4 29.414 289.57 4.98 9.44 14.421 193.05 3.32 6.11 9.4328 144.79 2.49 4.44 6.9335 115.83 1.99 3.44 5.4342 96.52 1.66 2.77 4.4349 82.73 1.42 2.30 3.7256 72.39 1.24 1.94 3.1863 64.35 1.11 1.66 2.7770 57.91 0.996 1.44 2.44

5. For the CUT calculation (Table A19), according to Attard et al., (2015) and Schievano et al., (2015), five main cost are involved:

a. Costs associated with the electric power used in the CO2 pump. The same conditions of the experiments in Schievano et al., (2015) are maintained. The specific enthalpy of CO2 using a pressure of 250 bar and 70 °C is 337.25 kJ/kgCO2. Each batch will take 8 h (480 min), so considering that the plant is operating 8760 h per year, 1095 batches will take place in a year. The load of OMW per batch will depend on the annual throughout of the plant (depending on the number of plants installed) and so the flow of CO2 that will be needed per hour (considering 80 kgCO2/h). The cost of electricity is considered to be 0.125 EUR/kWh (EUROSTAT, 2017c).

b. Costs associated with the CO2 heater. The CO2 has to be heated from 4 °C to 70 °C. The flow of CO2 per hour (M) depends on the throughput of the plant as shown in the previous section and the Cp (the specific heat capacity of CO2 at 70 °C) is equal to 0.877 kJ/kgK and the variation of temperature is 66 °C. Therefore, the heat required (Q) in MJ is calculated with Eq. A3 considering an efficiency of 50%.

c. Costs associated with refrigeration. The refrigeration cycle comprises a working fluid (in this case water) that has to be cooled from 20 °C to 4 °C. The Coefficient of performance (COP) at 20 °C and 4 °C is 0.08 and 0.15, respectively. The energy required (in MJ) for the refrigeration of the CO2 (M) is given by Eq. A4 considering Cp of CO2 at 27 °C equal to 0.846 kJ/kgK. The refrigeration requires electrical power which price is 0.125 EUR/kWh.

d. Costs associated with ethanol recovery. The heat capacity (Cp) of Ethanol is 2.3 kJ/kgK and the heat of vaporization (Hv) of the ethanol (at 78.34 °C) is 841 kJ/kg. The quantity of heat (Q) needed to recovery the ethanol previously calculated (M) is calculated as in Eq. A7.

e. Costs associated with drying the extracts. Ratti (2001) explained the advantages and disadvantages of freeze drying comparing to other drying technologies. From Fayose et al., (2016) the SMER for the freeze drying is 0.4 kg/kWh. In order to calculate the quantity of water that is evaporated using dry-freezing, data from Schievano et al., (2015) is used. The initial moisture of the OMW will depend on the production process ranging between 40-70 % depending on the olive processing technology used (Romero-Garcia et al., 2014). The OMW entering the biorefinery has 50% moisture content. In the SCO2+EtOH the extraction and transport of the aqueous phase is really efficient (85% removal of initial moisture content) remaining the exhaust OMW almost dried (around 9%) and the extract with about 88% water content. After the drying process, the moisture content is almost 0%.

The total Cost of Utility and the total COM for each plant (both in EUR per year) and for all plants are shown in Table A19.

Table A19: Cost of utilities for the olive waste biorefinery

N of plants


(Q/s) t/batch

Cost electricty CO2 Pump [×107

EUR/year]

Cost CO2 Heater [×106

EUR/year]

Cost electricty Refrigeration [×106

EUR/year]

Cost EtOH recovery [×104

EUR/year]

Cost Drying [×106

EUR/year]

CUT One Plant [×107

EUR/year]7 579.14 528.90 60.3 49.7 45.4 83.0 54.1 75.314 289.57 264.45 30.1 24.8 22.7 41.5 27.1 37.621 193.05 176.30 20.1 16.6 15.1 27.7 18.0 25.128 144.79 132.22 15.1 12.4 11.3 20.7 13.5 18.835 115.83 105.78 12.1 9.93 9.07 16.6 10.8 15.142 96.52 88.15 10.0 8.28 7.56 13.8 9.02 12.549 82.73 75.56 8.61 7.09 6.48 11.9 7.74 10.856 72.39 66.11 7.54 6.21 5.67 10.4 6.77 9.4163 64.35 58.77 6.70 5.52 5.04 9.22 6.02 8.3670 57.91 52.89 6.03 4.97 4.54 8.30 5.41 7.53

Finally, once all the five elements have been estimated, the COM can be calculated for one plant using Eq. 4 and the COM for all plants multiplying the COM by the number of plants (see Table A20).

Table A20: Cost of manufacturing for the olive waste biorefinery

N of plants

COM One plant[×108

EUR/year]

COM All plants[×109

EUR/year]7 9.87 6.9114 5.00 6.9921 3.37 7.0828 2.56 7.1735 2.07 7.2642 1.75 7.3549 1.52 7.4356 1.34 7.5263 1.21 7.6170 1.10 7.70

For the calculation of the revenues obtained with the extraction of the three products previously mentioned (i.e. total phenolic compounds (TPC, expressed as Gallic Acid Equivalents (GAE)), UFA expressed as fatty acids methyl esters (FAME), and squalene), first of all their quantities must be estimated assuming that the extraction efficiency reported in Schievano et al., (2015) is maintained. The concentration in the extract of TPC, FAME and squalene are of 10.86 g GAE/kg DM, 925 g FAME/kg DM, and 10 g squalene/kg DM, respectively.

Being the total production of TPC, FAME and squalene equal to 3.39×106, 2.89×106 and 3.12×106 kg/year, respectively. In order to calculate the total revenues, those quantities must be multiplied by the price of those products in the market. Schievano et al., (2015) reported a price for biophenols (hydroxytyrosol) of around 450 EUR for 100 mg at 98% purity. Several prices (EUR/kg) are found in literature and in the actual market (MERCK, 2017) for those products ranging from 3.6×102 to 9.6×106 EUR/kg. Since prices are very variable and uncertain, within this study three scenarios are tested (i.e. low, medium and high prices) as shown in Table .

Table A21: Price (EUR/kg) scenarios for the olive waste biorefinery products

Product Low Medium HighTPC 200 2000 20000FAME 10 100 1000Squalene 10 100 1000

Thus, the total revenues obtained for the Low, Medium and High scenarios are 7.38×108, 7.38×109and 7.38×1010 EUR/year, respectively. The profitability ratios (i.e. ROI and Payback time) for the three price scenarios are calculated ().

Table A22: ROI and payback time for the olive waste biorefinery scenarios

Number of plants

ROI (%) Payback time (years)Low Medium High Low Medium High

7 -7.99 0.61 86.54 -0.13 1.65 0.0114 -6.01 0.37 64.16 -0.17 2.73 0.0221 -4.85 0.22 50.94 -0.21 4.46 0.0228 -4.08 0.13 42.23 -0.25 7.66 0.0235 -3.53 0.06 36.04 -0.28 15.61 0.0342 -3.13 0.01 31.43 -0.32 69.42 0.0349 -2.81 -0.02 27.85 -0.36 -41.56 0.0456 -2.56 -0.05 25.00 -0.39 -18.27 0.0463 -2.35 -0.08 22.67 -0.42 -12.53 0.0470 -2.18 -0.10 20.74 -0.46 -9.94 0.05

4. ORANGES (Further information)


Table A23: Literature data used to estimate the amount of oranges and orange-based products lost and wasted in EU.

Type of lossLoss percentage

Reference(referred to the input)

Post-harvest loss n.c.Industrial loss - orange juice - peels 50% Sharma et al., 2016Distribution loss - fresh oranges 6% Eriksson et al., 2012Distribution loss - orange juice 0.33% Eriksson et al., 2012Consumption loss - fresh oranges - avoidable 20% JRC database

Consumption loss - fresh oranges - unavoidable 20%

JRC database

Consumption loss - orange juice 11% WRAP, 2012

Figure A7: Sankey diagram of the European orange wastes (year 2014)


For orange wastes different uses have been proposed in literature such as cattle feed (Mirabella et al., 2014), biofuel production (bioethanol and biogas) (Vlysides et al., 2015; Rivas-Cantu et al., 2013; Lohrasbi et al., 2010) or value-added products with bioeconomic interest production. Among these products the most reported ones are essential oils (EO) due to their economic feasibility (Matharu et al., 2016), and pectin and phenolics that are typically used in liquor, paint,

rubber, food and pharmaceutical industries (Davila et al., 2015). Traditionally, those products are extracted by conventional methods such as cold pressing and steam- and hydro-distillation that present some economic and environmental drawbacks such as high energy input and high solvent usage (Matharu et la., 2016). For that reason, the “Green chemistry” promote environment-friendly techniques such as SFE, MAE, UAE and enzyme-assisted extraction. All of them reduce the extraction time and therefore the consumed energy. In literature, some biorefinery concepts appear based on these technologies in which no solvents are used (Putnik et al., 2017; Boukroufa et al., 2015; Gonzalez-Rivera et al., 2016). In this paper, the techno-economic analysis of a solvent free extraction process that uses Microwave Hydrodiffusion and Gravity (MHG), UAE and MAE (Fig. A8) using the biorefinery data from Boukroufa et al., (2015) is done.

Fig. A8. Flow diagram of the orange waste biorefinery. MHG - Microwave Hydrodiffusion and Gravity, MAE-Microwave Assisted Extraction, and UAE - Ultrasound Assisted Extraction.


Since the data for the orange case study have been published in the paper, herein the more detailed calculations for CUT are presented (Table A24).

All experimental data is from Boukroufa et al., (2015). First of all, the number of batches per year have to be calculated. It is considered that the plant will operate 365 days or 8760 h per year. This time is divided by the batch time which is 0.8 hours, giving 10950 batches per year.

a. In the MHG, a potency of 500 W has been used for 15 min in a sample of 400 g fresh peel waste. This gives a consumption of 0.0003 kWh/g. This quantity multiplied by the tons per batch and the number of batch per year allow obtaining the kWh per year. And multiplied by the cost of electricity used in this case study, i.e. 0.125 EUR/kWh (EUROSTAT, 2017c), we obtain the total cost of the electricity in a year for MHG.

b. For the UAE, the dried residue from the MHG is used (i.e. 164 g dried peel calculated using Eq. A10 where Wd is the dry weight, Ww is the wet weight and Mn is the moisture content). According to the formula in Eq. A11, the potency (P)

used is calculated taking into account that the diameter of the equipment is 14 cm and the UI is 0.958 W/cm2. This gives a value of 0.00045 kWh/g considering that the UAE time is 30 min. Multiplying this value for the dry tons in a batch and by the number of batches in a year, we obtain the kWh used in a year. Again multiplied by the cost of electricity, the total cost of the electricity in a year for UAE is calculated.

W d=W w−(W w∗( M n

100 )) (A10)

UI= 4 Pπ D2 (A11)

c. For the MAE, the same calculations as in the MHG are done. MAE applies 500 W during 3 minutes to 5 g dried peel waste. This gives a consumption of 0.005 kWh/g. The quantity of kWh per batch and finally per year are calculated. And multiplied by the cost of electricity, the total cost of electricity per year for MAE is obtained.

Table A24: Cost of utilities for the orange waste biorefinery

Number of plants


(Q/s) t/batch

(Q/s) dry t/batch

Cost electricty MHG[×106

EUR/year]

Cost electricty UAE[×106

EUR/year]

Cost electricty MAE[×107

EUR/year]

CUT

One Plant[×107

EUR/year]

7 454.29 41.49 17.01 17.7 10.5 11.6 14.514 227.14 20.74 8.50 8.87 5.23 5.82 7.2321 151.43 13.83 5.67 5.92 3.49 3.88 4.8228 113.57 10.37 4.25 4.44 2.62 2.91 3.6235 90.86 8.30 3.40 3.55 2.09 2.33 2.8942 75.71 6.91 2.83 2.96 1.74 1.94 2.4149 64.90 5.93 2.43 2.54 1.50 1.66 2.0756 56.79 5.19 2.13 2.22 1.31 1.46 1.8163 50.48 4.61 1.89 1.97 1.16 1.29 1.6170 45.43 4.15 1.70 1.77 1.05 1.16 1.45

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