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Process Data set: Canola meal and crude oil production | mechanical and solvent extraction | Canola meal | Cutoff, U (en) en

Key Data Set Information
Location BR-Southern grid
Geographical representativeness description Data represents the operation of a general mill in the south region of Brazil, but can be considered in other regions of the country.
Reference year 2019
Name
Canola meal and crude oil production | mechanical and solvent extraction | Canola meal | Cutoff, U
Classification
Class name : Hierarchy level
  • ILCD: C:Manufacturing / 10:Manufacture of food products / 104:Manufacture of vegetable and animal oils and fats / 1040:Manufacture of vegetable and animal oils and fats
General comment on data set This dataset represents the operation of a mill with regards the processing of 1 kg of canola grain with in average 18% moisture content, by using mechanical extraction followed by the use of solvent. The product considered is canola dried meal, which can be used as animal feed. According to primary data collected at a canola processing plant, between 0.60 kg of canola meal per kg of canola grain is produced. The plant is located at the south region of Brazil, and is responsible for the processing of almost all the canola produced in the Brazil by the time of the project implementation. A current industrial process is used to obtain canola vegetable oil, through the combination of mechanical and solvent extraction, but it should be mentioned that infrastrufture of the plant is more than 20 years old. Differentiation can occurs regarding electricity consumption and type of energy feedstock used to supply the boiler. A few exceptions are applied, where data gaps are filled with information from the existing ecoinvent dataset, mainly from brazillian dataset for soybean oil. This activity starts with the transpot of the grains from the field to the plant (in average 200 km), reception, cleaning and drying of canola grain up to 13% moisture content, followed by oil extraction, and disolventizing, drying and griding of meal,resulting in dried meal, being conidered a gate-to-gate system. An allocation approach is applied based on a massic criterion. Main references as follow: Soybean meal and crude oil production, BR 2015", Ecoinvent v.3.6.?? FOLEGATTI-MATSUURA, M. I. S.; PICOLI, J. F. Life Cycle Inventories of Agriculture, Forestry and Animal Husbandry – Brazil. 2018. Zürich, Switzerland: p. 1-143. ZORTEA, R. B., 2015. Avaliação da sustentabilidade do biodiesel da soja no Rio Grande do Sul: uma abordagem de ciclo de vida. PhD Thesis. Porto Alegre. DORSA, R., 2004. Tecnologia de Óleos Vegetais. Campinas:Ideal. RODRIGUES, T. O.; SUGAWARA, E. T.; SILVA, D. A. L.; FOLEGATTI-MATSUURA, M. I. S.; BRAGA, T. E.N.; UGAYA, C. M. L. (2016) Guia Qualidata: requisitos de qualidade de conjuntos de dados para o Banco Nacional de Inventários do Ciclo de Vida. 58 p. 
Copyright Yes
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2020
Time representativeness description Time period for the most of the data collected for this dataset.
Technological representativeness
Technology description including background system Typical oil mill designed for canola oil production by means of of mechanical and solvent extraction. Plant infrastructure is more than 20 years old.
LCI method and allocation
Type of data set Unit process, black box
LCI Method Principle Other
Data sources, treatment and representativeness
Deviation from data cut-off and completeness principles / explanations None.
Deviation from data selection and combination principles / explanations None.
Sampling procedure Most of the data was provided by a mill located in the south region of Brazil which processes most of the canola (in average 40 ton/year). Considering that operations for vegetable oil production are similar among the mills, where primary data was not available, data from soybean meal and crude oil - BR dataset was used. Only the flux for oil mill, as an infreestructure, was obtained from another conuntry to fill the gap.
Data collection period 07/2019 -07/2020
Completeness
Completeness of product model No statement
Validation
Type of review
Not reviewed
Reviewer name and institution
Commissioner and goal
Project Life Cycle Inventory of canola production and bioproducts in the South Region of Brazil - a contribution to SCVI Brasil (CNPq-MCTIC)
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2021-12-08T15:15:48.637-02:00
Data set format(s)
Data entry by
Publication and ownership
UUID 6df7db04-7668-478b-ad4f-6c5e869dd2fc
Date of last revision 2021-12-08T10:25:40.045-02:00
Data set version 03.01.051
Copyright Yes

Inputs

Type of flow Classification Flow Mean amount Resulting amount Minimum amount Maximum amount
Product flow
0.001554168 kg0.001554168 kg
General comment Based on primary data for processing 1 kg of canola (0.00243 kg). Application of a 0.638 factor based on massic criteria.
Product flow
D:Electricity, gas, steam and air conditioning supply / 35:Electricity, gas, steam and air conditioning supply / 353:Steam and air conditioning supply / 3530:Steam and air conditioning supply 4.65276 MJ4.65276 MJ
General comment Calculated based on primary data for the total amount of wood for processing 1 kg of canola. A 0.638 factor based on mass was applied to the consumption of wood, considering: 0.0003784 m3/ton of canola (cleaning and drying processes), ; 0.0002214 m3/kg of canola (preparation and extraction processes); Totalizing 0.0005998 m3/kg canola * 0.638= 0.0003827 m3/kg canola alocated to meal. In addition, 100 % of the consumption for meal production, 0.0001107 m3 of wood/kg . Totalizing 0.0004934 m3/kg canola alocated to meal Assuming 9430 MJ/m3 madeira (from provider process for mixed logs).
Product flow
0.18036 MJ0.18036 MJ
General comment Based on primary data for the total amount for processing 1 kg of canola. A 0.638 factor based on mass was applied for the energy consumed up to oil extraction (0.0489 KWh), common to the production of oil and meal; in addition to 100% of energy consumed for meal production (0.01882 kwh)
Elementary flow
Elementary flows / resource / in water 4.5936E-4 m34.5936E-4 m3
General comment Application of a 0.638 factor based on mass basis. considering "Soybean meal and crude oil production, BR 2015", dataset (calculated based on literature (Dorsa, R., 2004. Tecnologia de Óleos Vegetais. Campinas: Ideal). Water consumed in the boiler.
Product flow A:Agriculture, forestry and fishing / 01:Crop and animal production, hunting and related service activities / 011:Growing of non-perennial crops / 0111:Growing of cereals (except rice), leguminous crops and oil seeds 1.0 kg1.0 kg
Elementary flow
Elementary flows / Resource / in water 1.9E-4 m31.9E-4 m3
General comment Application of a 0.638 factor based on a mass basis. considering "Soybean meal and crude oil production, BR 2015" dataset, which considered 3 literatures as references for the amount of water used in the process. Water for the boilers is not inlcuded
Product flow
1.19E-10 Item(s)1.19E-10 Item(s)
General comment Application of a 0.638 factor based on mass considering data from dataset "Soybean meal and crude oil production, BR 2015", at Ecoinvent DB, v. 3.6.

Outputs

Type of flow Classification Flow Mean amount Resulting amount Minimum amount Maximum amount
Elementary flow
Elementary flows / Emission to air / unspecified 2.615E-4 m32.615E-4 m3
General comment Part of water from boilers and water used in the process, allocated on mass basis, according to the same relation considered for "Soilbean meal and crude oil prodution" dataset, calculated with the same mathematical relation as the original dataset "Soybean meal and crude oil production, BR 2006". Values of parameters "fraction_TW_to_air" and "fraction_CW_to_air" were also adopted from the original dataset. Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 1.45E-6 kg1.45E-6 kg
General comment Calculated based on data from Zortea (2015) for soybean processing, considering: BOD=4.09199E-6/kg soybean processed. 0.189 kg oil/kg of soybean Adjusting for canola oil yield, considering: 0.34 kg oil/kg of canola Ratio: 0.189/0.34 Application of a 0.638 factor based on massic criteria
Elementary flow
Elementary flows / Emission to water / surface water 7.25618E-6 kg7.25618E-6 kg
General comment Calculated based on recommendation given in the ecoinvent Data Quality Guidelines (item 5.9.7) as follows: BOD5 = 0.2*COD Based on primary data for processing 1 kg of canola (0.00243 kg). Application of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 1.6E-7 kg1.6E-7 kg
General comment Calculated based on data from Zortea (2015) for soybean, considering: N emission= 4.5245E-7/kg of soybean 0.189 kg oil/kg og soybean Adjusting for canola oil yield, considering: 0.34 kg oil/kg of canola Ratio: 0.189/0.34 Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 4.53E-8 kg4.53E-8 kg
General comment Calculated based on data from Zortea (2015) for soybean, considering: P emission= 1.27671E-7/kg of soybean 0.189 kg oil/kg of soybean Adjusting for canola oil yield, considering: 0.34 kg oil/kg of canola Ratio: 0.189/0.34 Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 2.68747E-6 kg2.68747E-6 kg
General comment Calculated based on recommendation given in the ecoinvent Data Quality Guidelines (item 5.9.7) as follows: COD = 2.7*TOC Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 2.68747E-6 kg2.68747E-6 kg
General comment Calculated based on recommendation given in the ecoinvent Data quality Guidelines (item 5.9.7) as follows: DOC = TOC. Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / air / high population density 0.001554168 kg0.001554168 kg
General comment Emissions are taken to be equal to input of the solvent. Aplication of a 0.638 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / unspecified 3.89244E-4 m33.89244E-4 m3
General comment Mostly water from the boilers, allocated on a mass basis, according to the same relation considered for "Soybean meal and crude oil prodution" dataset, calculated with the same mathematical relation as the original dataset "Soybean meal and crude oil production, BR 2006". Values of parameters "fraction_TW_to_air" and "fraction_CW_to_air" were also adopted from the original dataset. Aplication of a 0.638 factor based on massic criteria.
Product flow
C:Manufacturing / 10:Manufacture of food products / 104:Manufacture of vegetable and animal oils and fats / 1040:Manufacture of vegetable and animal oils and fats 0.6 kg0.6 kg
General comment Based on primary data,
Elementary flow
Elementary flows / Emission to water / ground water 0.0383 kg0.0383 kg
General comment Based o primary data for processing 1 kg of canola (0.060 kg). Aplication of a 0.638 factor based on massic criteria.