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Process Data set: Canola meal and crude oil production | mechanical and solvent extraction | 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 | 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 16% moisture content, by using mechanical extraction followed by the use of solvent. The products considered are: crude oil, with out degumming, which can be further refined to become edible or used as biofuel; and dried meal which can be used as animal feed. According to primary data collected in 2019 at a canola processing plant, 0.34 kg of canola crude oil, and 0,60 kg of meal were 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. 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 crude oil and dried canola meal, being considered a gate-to-gate system. No further treatment of crude oil or meal is included. Main references as follow: 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 Mostly primary data colllected one year and 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, when primary data was not available, data from soybean meal and crude oil - BR dataset was considered and converted. The following sources were considered: Soybean meal and crude oil production, BR 2015", Ecoinvent v.3.6. 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. Folegatti-Matsuura, M. I. S.; Picoli, J. F. Life Cycle Inventories of Agriculture, Forestry and Animal Husbandry – Brazil. 2018. Zürich, Switzerland: p. 1-143.
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)
Intended applications Dataset will be submited and entered into the National Life Cycle Inventories Database - SICV Brasil.
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2021-12-08T15:08:26.505-02:00
Data set format(s)
Data entry by
Publication and ownership
UUID 7db5bdd0-6c1c-4c54-b6fe-2ad2b3016467
Date of last revision 2021-12-08T15:00:52.152-02:00
Data set version 03.01.065
Copyright Yes

Inputs

Type of flow Classification Flow Mean amount Resulting amount Minimum amount Maximum amount
Product flow
0.002436 kg0.002436 kg
General comment Calculated based on primary data - 2,436 kg for processing 1 ton of canola.
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 6.69918 MJ6.69918 MJ
General comment Calculated based on primary data of the amount of wood to process 1 ton of canola. Considering the consumption of: 0.0003784 m3/ton of canola (cleaning and drying processes), ; 0.0002214 m3/kg of canola (preparation and extraction processes); 0.0001107 m3 of wood/kg (canola for meal production). Totalizing 0.0007105 m3 wood/kg of canola. Assuming 9430 MJ/m3 madeira (from provider process for mixed logs).
Product flow
0.243972 MJ0.243972 MJ
General comment Calculated based on primary data - consumption of 67.77 kwh/ton of canola.
Elementary flow
Elementary flows / resource / in water 7.2E-4 m37.2E-4 m3
General comment Data for Soybean meal and crude oil production, BR Inventorie 2015 was applied, consisting in water for the boilers, which was calculated based on literature (Dorsa, R., 2004. Tecnologia de Óleos Vegetais. Campinas: Ideal).
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 3.0E-4 m33.0E-4 m3
General comment Data from dataset "Soybean meal and crude oil production, BR 2015", at Ecoinvent DB, v. 3.6.
Product flow
1.86E-10 Item(s)1.86E-10 Item(s)
General comment Data from dataset "Soybean meal and crude oil production, BR 2015", at Ecoinvent DB, v. 3.6, was applied.

Outputs

Type of flow Classification Flow Mean amount Resulting amount Minimum amount Maximum amount
Elementary flow
Elementary flows / Emission to air / unspecified 4.1E-4 m34.1E-4 m3
General comment Fraction of water from boilers (0.00011m3), according to the same relation consider for "Soilbean meal and crude oil prodution", as follows: Value 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. 4.1E-4 Water used in the process (0.0003 m3) is also inlcuded as emisson in this flux.
Elementary flow
Elementary flows / Emission to water / surface water 0.06 kg0.06 kg
General comment Resulting from preliminar grain cleaning process according to primary data.
Elementary flow
Elementary flows / water / surface water 2.27466E-6 kg2.27466E-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
Elementary flow
Elementary flows / Emission to water / surface water 1.13733E-5 kg1.13733E-5 kg
General comment Calculated based on recommendations given in the ecoinvent Data Quality Guidelines (item 5.9.7) as follows: BOD5 = 0.2*COD
Elementary flow
Elementary flows / water / surface water 2.52E-7 kg2.52E-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
Elementary flow
Elementary flows / water / surface water 7.1E-8 kg7.1E-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
Elementary flow
Elementary flows / Emission to water / surface water 4.21234E-6 kg4.21234E-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
Elementary flow
Elementary flows / Emission to water / surface water 4.21234E-6 kg4.21234E-6 kg
General comment Calculated based on recommendation given in the ecoinvent Data quality Guidelines (item 5.9.7) as follows: DOC = TOC
Elementary flow
Elementary flows / air / high population density 0.002436 kg0.002436 kg
General comment Emissions are taken to be equal to the input of the solvent, as assumed in others inventories, given the volatile nature of hexane.
Elementary flow
Elementary flows / Emission to water / unspecified 6.1E-4 m36.1E-4 m3
General comment Mostly water from boilers (0.00061m3), according to the same relation considered for "Soilbean meal and crude oil prodution" dataset, calculated as follows: Value 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.
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 (2019). (0.600 of meal and 0.340 of crude oil are produced/kg of canola).
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 (2019). (0.600 of meal and 0.340 of crude oil are produced/kg of canola).
Elementary flow
Elementary flows / Emission to air / unspecified 9.52381E-5 m39.52381E-5 m3
General comment Emission resulted from grains drying process (liters/kg canola). Calculated based on the following equation % of dry grains × ("UGs - U c" )/(UGc- 1), where: % of dry grains is 100% UGs is the final moisture content - 8% according to the processing plant; UGc is the harvested moisture content - 16% according to the processing plant;