Model recycled materials using the cut-off approach
In Ecodesign Studio, all integrated databases follow the cut-off approach, based on the polluter-pays principle. According to this principle, data on recycled materials do not include environmental charges, as these are attributed to the producer of the recyclable or valuable waste flow. The distribution of impacts is therefore 100/0. However, some waste has to be treated before it can be reused, and in this case the impacts associated with treatment are attributed to the system that recovers the stream.
However, it is possible to apply a different allocation, distributing 50% of the impacts to the producer of the flow and 50% to the system that recovers the flow (50/50 allocation). This is a methodological choice and a modeling technique that comes under the heading of sensitivity analysis. Let's take an example to illustrate this principle:
Consider the production of a board of wood used to make a bench. At the end of its life cycle, the bench is dismantled, the wood recovered and chipped.
With the cut-off approach, the disposal of these chips is considered to have no impact, as they represent a waste product from the first life cycle. As the material is available without transformation (it is a waste product), it is therefore "preferable" to chips produced directly from raw wood.
However, this illustration raises a number of questions. As the chipping stage is necessary to make the flow usable, should we allocate the impacts of this activity upstream (end-of-life treatment of the bench) or downstream (wood revalorization)? If the bench was designed to be dismantled, shouldn't part of the production of the initial board be allocated to the production of the chips? These questions are frequently asked in LCA. However, there is no single answer, since everything depends on the context, the objectives of the study and the methodological choices made. So we sometimes find 50/50 allocations or mass or economic ratios at the limits of the scope.
In all cases, it is important to consult the data description in order to understand the scope taken into account, which will enable you to make an appropriate modeling choice.