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Process Data set: Peanut shell pellets, at plant (en) en

Key Data Set Information
Location BR-SP
Geographical representativeness description Itaju, Sao Paulo State, Brazil
Reference year 2021
Name
Peanut shell pellets, at plant
Classification
Class name : Hierarchy level
  • ILCD: Biomass pellets
General comment on data set Data obtained though a semi structured interview made in 2021 with the industry owner in a technical visit at the enterprise located in São Paulo State, Brazil. It is considered from biomass collecting point to industry (distance: 10 kilometers in average). The pellets manufacturing considers a Lippel pelletizer machine with production capacity 10 ton/Hour in a cogeneration system: #17.845 MJ/Kg = Average calorific value for penut husk, based on the paper "Optimal use of condensed parameters of ultimate analysis to predict the calorific value of biomass" (Ozyuguran et al., 2014). #Furnace heating power (Kcal/h) 7,000,000 = 29,307.6MJ #Total peanut residue to the furnace = 1,642.34 KG Annual Production of the site = 1,048 ton/year pellets 1 Year is equal to 8,760h average time for production of 10 tons = 83h35min
Copyright No
Owner of data set
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2021
Time representativeness description Data was collected in December 2021 and the reference year is 2021 (twelve months).
Technological representativeness
Technology description including background system Data related to electricity consumption is based on a Lippel pelletizer machine with capacity of 10 ton/Hour (2,095.83 CV = 1,562.8 kWh). According to the inteviwed people, the peanut shell is bought as dry mass. The data for biomass transportation to the factory considers the average distance from the collecting point to industry (10 km).
Mathematical model
Variable / parameter Formula Mean value Minimum value Maximum value Uncertainty distribution type Relative StdDev in % General comment
Pellets 10.0 LOG_NORMAL 1.0 % Total pellet production per reference flow
Distance_to_Industry 10.0 LOG_NORMAL 1.0 % According to the average estimates of Industry manager
Biomass_Gross 10.0 LOG_NORMAL 1.0 % Based on reference flow of 10 tons of pellets produced
Transport_Biomass_Gross distance_to_Industry *biomass_Gross 100.0 % Values in *tkm
gd_price_waste 0.5 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent for being wastes (i.e. negative reference product), and that were considered that they should have a cost/revenue specified. The prices used for them, equal to the prices of the same product in other processes of the database, are modified by this parameter with value 0.5 (i.e. half the price of the normal product), considering that the reference product of a waste treatment process might have a lower price in reality than the same flow produced by a production process. However, you can modify this value to 0 if you prefer to consider no price for them like ecoinvent, or also 1 if you do not want to distinguish wastes from other products.
gd_price_product 1.0 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent and that were considered to be products or co-products of waste treatments (i.e. positive reference product), and that they should have a cost/revenue specified. The prices used for them, equal to the prices of the same product in other processes of the database, are modified by this parameter with value 1. However, you can modify this value to 0 if you prefer to consider no price for them like ecoinvent.
ei_price_product 1.0 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent in this specific system model, but yes in at least one of the other two system models. The prices used for them, equal to the prices of the same product and provider in the other system model, are modified by this parameter with value 1. However, you can modify this value to 0 if you prefer to consider no price for them in this system model like ecoinvent.
Heavy_metal_uptake 1.0 % Take the heavy metal emissions into account? Yes = "1", "no" = "0" (If the heavy metals direct emissions are included, put the value to "1". If the heavy metals direct emissions are excluded, put the value to "0".)
LUC_crop_specific 1.0 % Approach for LUC: If the approach is "Crop specific", put the value to "1". If the approach is "Shared responsability", put the value to "0"
temp_olca_param9 pellets 10.0 %
temp_olca_param10 biomass_Gross 10.0 %
temp_olca_param11 transport_Biomass_Gross 100.0 %
LCI method and allocation
Type of data set Unit process, black box
LCI Method Principle Other
Deviation from LCI method principle / explanations Attributional.
Modelling constants The LCI is entirely done with an attributional methodology.
Data sources, treatment and representativeness
Data cut-off and completeness principles No statement.
Deviation from data cut-off and completeness principles / explanations None.
Data selection and combination principles All the input/output data was collected for the specific context of the studied Brazilian enterprise from São Paulo State. Data are based in 10 tons of produced pellets in 2021.
Deviation from data selection and combination principles / explanations None.
Data treatment and extrapolations principles see 'Geography' and 'Technology' in 'General information' section.
Data source(s) used for this data set
Sampling procedure Average values representing 10 tons of peanut shell pellets production were obtained from semi-structured interviews performed in a technical visit to the Industry. Data is based on the internal companies data such as records of raw material consumption, emissions and waste management inventories. When process input/output data was not avaiable, secondary data were used.
Data collection period Data were collected in December 2021 and is based on the production statistics for 2021 (twelve months).
Completeness
Completeness of product model No statement
Commissioner and goal
Project FAPESP grant number 2019/16996-4
Intended applications This LCI can be used for any types of LCA studies demanding the southeast Brazilian pellets produced from peanut shell
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2023-01-20T08:53:30.387-02:00
Data set format(s)
Data entry by
Publication and ownership
UUID 8c6bda5c-2b1a-4936-b649-44e1c49e1da2
Date of last revision 2023-01-20T08:52:44.644-02:00
Data set version 00.00.037
Unchanged re-publication of
Owner of data set
Copyright No
Access and use restrictions The dataset can be used free of charge by anybody to perform LCA studies, to distribute it to third parties, to convert it to other formats, to develop own data sets, and for any other application.

Inputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
Agriculture, forestry and fishing / Growing of fibre crops temp_olca_param10 1.0 kg10000.0 kg
General comment Considering biomass consumption to produce 10 tons of pellets Biomass is obtained as dry mass
Product flow
H:Transportation and storage / 49:Land transport and transport via pipelines / 492:Other land transport / 4923:Freight transport by road temp_olca_param11 1.0 t*km100.0 t*km
General comment Biomass feed - avg distance of 10 km according to the Manager Considering 10 tons of biomass 10*10 = 100*TKM
Product flow
17.17 kg17.17 kg
General comment Related to the Wheel loader which unload the biomass from the truck Considering a Caterpillar machine 966H with an avg. consumption of 14.6 liters per hour Diesel density = 0.85 l / kg = 17.17 Kilograms
Product flow
Energy / Utilities / Other Electric Power Generation 5626.08 MJ5626.08 MJ
General comment Cogeneration, considering Lippel pelletizer machine
Product flow
L:Real estate activities / 68:Real estate activities 81300.00000000001 m281300.00000000001 m2
General comment LUC data were calculated using the ‘Direct Land Use Change Assessment Tool’ from Blonk Consultants (2014) Total volumetric production per hectar = 6m³ Density of peanut shell = 205 kg/m³ Based on DOURADO et al., 2017. "Avaliação das propriedades físicoquímicas de resíduos lignocelulósicos"

Outputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
temp_olca_param9 1.0 kg10000.0 kg
General comment According to the interviewed team, the biomass is obtained as dry mass which means that the input and output amount are the same