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Process Data set: Canola meal and crude oil production | mechanical and solvent extraction | Canola oil, crude | 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 oil, crude | 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 crude oil, with out degumming, which can be refined to become edible or to be used as biofuel. According to primary data collected in 2019 at a canola processing plant, 0.34 kg of canola crude oil was produced per kg of canola grain. The plant is located at the south region of Brazil, and is responsible for the processing of almost all the canola produced in th Brazil during the period of the Idata collection. TA 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 the operations for oil extraction, resulting in crude oil, being considered a gate-to-gate system. No further treatment of crude oil or meal is included. 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.
Data treatment and extrapolations principles Dry mass, carbon content and gross calorific value are based on ecoinvent database.
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.
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) 2021-12-08T15:17:50.846-02:00
Data set format(s)
Data entry by
Publication and ownership
UUID a32c8b68-ebab-4df0-9c5c-c40aa274a166
Date of last revision 2021-12-08T10:25:36.311-02:00
Data set version 03.01.056
Copyright Yes

Inputs

Type of flow Classification Flow Mean amount Resulting amount Minimum amount Maximum amount
Product flow
8.81832E-4 kg8.81832E-4 kg
General comment Based on primary data for processing 1 kg of canola 0.002436 kg), and application of a 0.362 factor based on mass.
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 2.04642 MJ2.04642 MJ
General comment Calculated based on primary data for the total amount of wood for processing 1 kg of canola up to oil extraction. A 0.362 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 * 0.362= 0.0002171 m3/kg canola alocated to crude oil. Assuming 9430 MJ/m3 madeira (from provider process for mixed logs).
Product flow
0.06378516000000001 MJ0.06378516000000001 MJ
General comment Based on primary data for the total amount for processing 1 kg of canola up to the process of oil extraction (0.0489 KWh). A 0.362 factor based on mass was applied for the energy consumed up to oil extraction.
Elementary flow
Elementary flows / resource / in water 2.6064E-4 m32.6064E-4 m3
General comment Application of a 0.362 factor based on mass. 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 1.1E-4 m31.1E-4 m3
General comment Application of a 0.362 factor based on mass. 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
6.73E-11 Item(s)6.73E-11 Item(s)
General comment Application of a 0.362 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 1.48387E-4 m31.48387E-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. Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 0.0217 kg0.0217 kg
General comment Based o primary data for processing 1 kg of canola. Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 8.23E-7 kg8.23E-7 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 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 4.12E-6 kg4.12E-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 Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 9.1E-8 kg9.1E-8 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 Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / water / surface water 2.57E-8 kg2.57E-8 kg
General comment Calculated based on data from Zortea (2015) for soybean, (soybean meal BR dataset). Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 1.52487E-6 kg1.52487E-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 Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / surface water 1.52487E-6 kg1.52487E-6 kg
General comment Calculated based on recommendation given in the ecoinvent Data quality Guidelines (item 5.9.7) as follows: DOC = TOC Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / air / high population density 8.81832E-4 kg8.81832E-4 kg
General comment Emissions are taken to be equal to input of the solvent. Application of a 0.362 factor based on massic criteria.
Elementary flow
Elementary flows / Emission to water / unspecified 2.2E-4 m32.2E-4 m3
General comment Mostly water from the boilers, allocated on a 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. Application of a 0.362 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 0.34 kg0.34 kg
General comment Based on primary data.
Elementary flow
Elementary flows / Emission to air / unspecified 3.44762E-5 m33.44762E-5 m3
General comment Emission resulted from grains drying process. Calculated based on information provided by the processing plant (harvested moisture contend 16%, and 8% final moisture contend). Alocated only to crude oil production.