Ready for some more information on LCA?
The LCA methodology is fundamentally based on very simple premises – materials and processes generate Environmental Impacts and depending on the quantity of our inputs, the environmental impacts are multiplied accordingly. Say, if production 🏭 of 1 kg of glass generates 1.25 kgCO2eq 💨, this emission factor can be applied to a desired quantity of glass included in our product or project.
However, things get complicated both due to the sheer volume of materials and processes used in the industry and the extensive array of environmental impacts that need to be considered ⚖️. Since many of these impacts are displaced in terms of place and time and thus expressed as potential or projected impacts, they often cannot be measured directly or efficiently. Additionally, we also want life cycle assessments to be as streamlined as possible to enable quick quantification of environmental impacts, which means that certain approximations need to be made.
🗝️ This is where the life cycle inventory databases come into play. When raw primary data of the environmental footprint of activities is unavailable, databases such as EcoInvent, GaBi, PEF, NMD, ÖKOBAUDAT and other are used. They contain scientific datapoints on energy requirements, material inputs, waste outputs and emissions generated of many conventional processes. This makes performing an LCA easier and faster.
For many datapoints, the data is geographically ‘localized’ to account for the typical energy mix and technology/materials available in a certain country or region 🌍️. Sometimes, geographically specific databases are required to ensure compliance with national standards. Some databases are freely available, whilst others require paid access – this is typically included within the cost of the LCA software used.
🎈The good news? The datapoints in the databases are continuously being updated and expanded as more information is collected and verified. Thus, with the increasing need for LCA in sustainability compliance, modelling will be even more target-specific and accurate.
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