Recycling potential aluminium (sheet and profiles); End of Life; production mix, at plant; 95% primary metal content to recycling, 5% to landfill

Category:
End-of-life treatment/Material recycling
Location:
BR - Brazil
Reference year: 2019 - 2022
Description

This dataset is part of the GaBi 2020 database.

The data set covers all relevant process steps for the End of Life stage including the avoided burden of the recycling product (system expansion). The inventory is mainly based on industry data and is completed, where necessary, by secondary data.

Technology

The recycling potential describes the ecological value of a materials accumulation in the technosphere. It states how many environmental burdens may be avoided in relation to a new production of the material (avoidance of primary aluminium production). For this purpose, a collection rate of 95% is assumed. The datasets also considers disposal of material that is not recycled, i.e. 5%.

Since the recycling potential when manufacturing the product represents a saving, it is composed of a complete data set with full characteristics.   If the complete recycling potential is used, the characteristics for manufacturing the product are lowered by those for the recycling potential. This demonstrates the life cycle view.Example (see also flow diagram): To produce 1000 kg of a metal product at present 80% virgin material and 20% recycled material are used (800 kg virgin material, 200 kg recycled material input). The recycled material input requires 220kg of scrap metal (e.g. 10% metal loss during production), 780 kg scrap will be left for a recycling potential for future recycled material input leading to 702 kg recycled metal (e.g. 10% metal loss during production). The recycling potential is calculated as avoided production of 702 kg virgin material (taking into account the mass flows from the recycling process).      

Background system:

Electricity: Electricity from renewable and non- renewable powerplants is modelled so that it represents a country’s specific consumption mix including transmission / distribution losses, own consumption, imports, emissions and efficiency standards, and energy carrier properties. Several factors are taken into account. (1) Energy carrier production - The exploration, mining / production, processing, and transportation of energy carrier supply chains are modelled for each country. The models account for differences among countries in production and processing, including crude oil production technologies, flaring rates, production efficiencies, emissions, etc. (2) Energy carrier supply - Each country’s specific energy carrier supply is modelled, taking into account domestic supply versus imports from abroad. Energy carrier properties (e.g. carbon and energy content), which can vary depending from where an energy carrier is sourced, are adjusted accordingly. (3) Power plants - Models are created to represent energy carrier-specific power plants and electricity generation facilities specific to different renewable energy resources. Energy carrier production and supply models are used to represent power plant inputs. Combined heat and power (CHP) plants are also considered. (4) Electricity grid - Models representing the electricity generation facilities are combined into a larger model that reflects a country’s consumption mix. The larger model accounts for a country’s production mix, internal consumption (e.g. pumped storage for hydro power), transmission / distribution losses, and imported electricity. The country model is also adjusted according to national power plant emission and efficiency standards, as well as the country’s share of electricity plants versus CHP facilities.

Thermal energy, process steam: The thermal energy and process steam supply is modelled to reflect each country’s emission standards and typical energy carriers (e.g., coal, natural gas, etc.) Both thermal energy and process steam are assumed to be produced at heat plants. Thermal energy datasets assume energy carrier inputs are converted to thermal energy with 100% efficiency; process steam datasets assume conversion efficiencies of 85%, 90% to 95%. The energy carriers used for the generation of thermal energy and process steam are modelled according to each country’s import situation (see electricity above).

Transportation: All relevant and known transportation processes are included. Ocean-going and inland ship transport as well as rail, truck and pipeline transport of bulk commodities are considered.

Energy carriers: The energy carriers and their respective properties are modelled according to the specific supply situation (see electricity above).

Refinery products: Diesel fuel, gasoline, technical gases, fuel oils, lubricants and residues such as bitumen are modelled with a parameterised country-specific refinery model. The refinery model aims to represent each country’s refining processes (e.g. emissions levels, internal energy consumption, etc.), as well as the country’s product output spectrum, which can vary significantly among countries. The supply of crude oil is likewise modelled according to the country-specific situation and accounts for differences in resource properties (e.g., crude oil energy content).

Process type
Fully aggregated
Supported nomenclature
ILCD, EF2.0, EF3.0
LCI modeling approach
Attributional
Multifunctional modeling
PHYSICAL
Format
ILCD
Aggregation type
UNKNOWN
Data provider
Sphera
Review status
External
Cost
For sale
License

The GaBi datasets are available as packages in so called Extension databases, next to the central Professional database, for GaBi users. Licensing is via subscription or maintenance contracts. Single datasets can be ordered by GaBi Software clients as data-on-demand orders. The general and specific license conditions are found at https://scn.spherasolutions.com/client/tc/Sphera-Software-Terms-and-Con… and https://scn.spherasolutions.com/client/tc/Sphera-GaBi-Software-Special-…. For requests for an offer, please write to the contact email provided on this present website.

Contact
gabi@sphera.com