Carbon Footprint Calculation
This section provides a detailed explanation of how the carbon footprint (CF) is calculated specifically for the manufacturing phase of materials.
Last updated
This section provides a detailed explanation of how the carbon footprint (CF) is calculated specifically for the manufacturing phase of materials.
Last updated
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For the manufacturing of metallic materials, Total Materia utilizes its proprietary composition data combined with ecoinvent's Life Cycle Inventory Assessment (LCIA) datasets for elements, with a focus on composition-based weighting in the calculations. For non-metallic materials, producer-specific data is prioritized over polymer family average calculations, ensuring a more accurate representation.
The formula below outlines the specific calculations performed by the algorithm to derive the carbon footprint of the manufacturing of material.
Description of the elements of the formula is available below:
The chemical composition data utilized in the calculations originate from material specifications that populate the Horizon database. These specifications are drawn from a variety of references, including standards from Standard Development Organizations (SDOs), scientific articles, handbooks, and other authoritative sources.
Typically, material compositions are presented as ranges or specified with minimum and maximum values. For carbon footprint calculations, a single representative value is needed. A patented method (US20090076739A1), initially developed for the identification of metal alloys, is applied to convert these ranges or minimum and maximum values into a single value. This approach leverages statistical analysis, taking into account the distribution of chemical composition values for each element within a material group.
The following elements are neglected in the calculation: hydrogen, oxygen, and nitrogen.
Threshold of alloying elements - For each group of metals, a different set of threshold values is assigned to alloying elements. They are obtained by using metallurgical expertise and have sounded physical meaning. The threshold parameter indicates at which level the element is considered in calculations; elements with value below threshold are treated as impurities and neglected in the calculation.
Carbon footprint values for both base and alloying elements are sourced from Ecoinvent's LCIA (Life Cycle Impact Assessment) datasets. These datasets are normalized and weighted in accordance with the ISO 14000 standards methodology, helping to ensure consistency and comparability of results across various studies and applications.
System model: Allocation cut-off by Classification
Geography: Global - representing the average global production
Dataset type: Market
LCIA method: IPCC 2021 no LT
Indicator: Climate change – Global Warming Potential 100 years (GWP100)
The system model “Allocation, cut-off by classification,” or the cut-off system model, is based on the recycled content, or cut-off, approach. In this system model, wastes are the producer’s responsibility (“polluter pays”), and there is an incentivization to use recyclable products, that are available burden free (cut-off).
Ecoinvent continuously updates its database to capture the latest advancements in industrial processes, technology, and global supply chains, ensuring the data remains both relevant and precise. These updates are regularly integrated in Green Line, allowing for the most up-to-date carbon footprint calculations for selected materials. This ensures that the analysis reflects current industry standards and provides accurate insights into material emissions.
Data from selected and validated scientific articles is used to significantly broaden the scope of carbon footprint calculations. These valuable sources provide critical information, enabling more comprehensive assessments, particularly in regions or processes where Ecoinvent data is limited or unavailable. This allows for the inclusion of a wider range of countries and manufacturing methods, improved precision in definition of key parameters such as scrap content in material production, and enhanced calculations of environmental impacts for different manufacturing routes across various regions.
Carbon Footprint and Energy Transformation Analysis of Steel Produced via a Direct Reduction Plant with an Integrated Electric Melting Unit / J. Suer, F. Ahrenhold, M. Traverso / Springer / 2022 / Journal of Sustainable Metallurgy, 8(2022), pp.1532-1545. Available at: https://doi.org/10.1007/s40831-022-00585-x
Steel’s recyclability: demonstrating the benefits of recycling steel to achieve a circular economy / C. Broadbent / Springer / 2016 / The International Journal of Life Cycle Assessment, 21(2016), pp.1658-1665. Available at: https://link.springer.com/article/10.1007/s11367-016-1081-1
Influence of direct reduced iron on the energy balance of the electric arc furnace in steel industry / M. Kirschen, K. Badr, H. Pfeifer / Elsevier / 2011 / Energy, 36(2011), pp.6146-6155. Available at: https://doi.org/10.1016/j.energy.2011.07.050
Steel Climate Impact: An International Benchmarking of Energy and CO2 Intensities / A. Hasanbeigi / 2022 / Available at: https://www.globalefficiencyintel.com
Best Available Techniques (BAT) Reference Document for Iron and Steel Production / R. Remus, M. A. Aguado Monsonet, S. Roudier, L. Delgado Sancho / Joint Research Centre of the European Commission / 2013 / Available at: http://eippcb.jrc.ec.europa.eu
The manufacturing routes for steel available in the Green Line module include several key processes, each with distinct characteristics and environmental impacts:
1. Blast Furnace-Basic Oxygen Furnace (BF-BOF): This is one of the most widely used methods for steel production. The process begins with the blast furnace, where iron ore, coke, and limestone are heated to produce molten iron. The molten iron is then transferred to the basic oxygen furnace, where it is mixed with scrap steel and oxygen to reduce carbon content, resulting in the production of steel. While this method is efficient for large-scale production, it is energy-intensive and associated with significant CO2 emissions due to the reliance on coal-derived coke as a fuel source.
2. Electric Arc Furnace (EAF): This process is primarily used for recycling scrap steel. In an electric arc furnace, high-voltage electric arcs are used to melt scrap steel, which is then refined into new steel. EAF is considered more energy-efficient and environmentally friendly compared to BF-BOF, as it uses significantly less energy and does not require iron ore. Since it heavily relies on recycled materials, its carbon footprint is generally lower, especially when renewable energy is used to power the furnace.
3. Direct Reduced Iron-Electric Arc Furnace (DRI-EAF): In this route, iron ore is first reduced to direct reduced iron (DRI) using a reducing gas (typically natural gas or hydrogen) rather than coke. The resulting DRI is then melted in an electric arc furnace to produce steel. This method is more energy-efficient than BF-BOF and produces fewer carbon emissions. When hydrogen is used as the reducing gas, the DRI-EAF process can be nearly carbon-free, making it an increasingly attractive option for green steel production.
4. Undefined (Country Average): This represents the average steel production route for a given country. It combines data from various manufacturing methods used within that country, providing a general overview of steel production's environmental impact. This option allows for an average calculation when specific production routes are not defined, offering a useful approximation for carbon footprint assessments based on regional manufacturing practices.
For non-metallic materials, carbon footprint calculations are approached differently due to the nature of the available data. When specific producer data is available, it takes precedence, offering the most accurate reflection of the material's environmental impact based on real-world production conditions. This producer-specific information can include details such as energy consumption, production processes, or regional factors that directly influence emissions. By prioritizing this data over broader industry averages, the calculation can more accurately represent the material’s actual carbon footprint.
However, in many cases, non-metallic materials, such as polymers, do not have fully disclosed chemical compositions. This lack of transparency makes it impossible to base the carbon footprint calculation on precise chemical data. As a result, the system utilizes average data for the material's broader classification. While this approach may not capture the exact emissions profile of a specific product, it provides a reasonable and standardized estimate based on industry-wide trends. This method ensures that even in the absence of detailed composition data, the carbon footprint calculation remains robust, allowing for reliable assessments across a wide range of non-metallic materials.
All references utilized for carbon footprint calculations are meticulously documented and listed at the bottom of the Carbon Footprint page. This comprehensive documentation ensures that users have easy access to the sources of data and methodologies employed in the calculations, promoting transparency and credibility in the analysis. The accompanying screenshot illustrates this feature, highlighting the clear organization of references that supports the accuracy of the carbon footprint assessments.
The data sourced from producers is clearly indicated on the website, with a dedicated label "Producer data" in the Manufacturing column of the table. This labeling allows users to easily identify which data points are derived directly from manufacturers, ensuring transparency and confidence in the accuracy of the information presented. By highlighting producer-specific data, the system facilitates informed decision-making regarding the carbon footprint of non-metallic materials, making it straightforward for users to differentiate between producer data and broader averages. Below is a screenshot illustrating this feature.
– carbon footprint value of the base element obtained from Ecoinvent
– share of alloying element obtained from Horizon
– carbon footprint value of the alloying element obtained from Ecoinvent (it is considered only if the element is above the defined threshold for the selected material group)
– country normalization factor – relative factor that accounts for the emission performance of the selected country compared to a reference country. This factor is calculated for each material group using data sourced from relevant articles, ensuring that variations in emissions due to geographic differences are accurately reflected in the analysis.
– manufacturing route normalization factor. This factor is calculated for each material group using data sourced from relevant articles. Click here to see available manufacturing routes and their description.
– scrap content adjustment – linear interpolation based on emissions data from the literature for a selected manufacturing route as a function of scrap content
– scrap content
– linear coefficient for specified manufacturing route