Gaining benefits from discarded textiles

LCA of different treatment pathways

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Nordic consumers purchase 365 000 tonnes of new clothing and home textiles each year. After food, housing and mobility, textiles is our consumption area that causes most environmental impacts. Reusing and recycling used textiles can offset some of these impacts but with an increasing number of options available, government and business need more information to make decisions on which pathways to choose.

The Nordic Council of Ministers commissioned a consortium to carry out an LCA study to compare the environmental benefits of treatment options. Reuse was found to give by far the greatest benefits, regardless of whether the textiles are reused in the Nordic region or exported for reuse elsewhere. Further down the waste hierarchy, recycling is a better environmental option than incineration, although the benefits are moderate compared to the benefits of reuse.

The primary aim of the project was to provide a database that can assist policymakers and businesses to estimate the environmental benefits of strategies for gathering and treating discarded textiles. As such this report presents only a fraction of the results of the LCA modelling. Hundreds of additional results can be found in a number of spreadsheets that can also be downloaded here.



Data quality assessment

A pedigree (hybrid) approach, modified from Weidema and Wesnæs (1996) was used to assess the data quality. For each unit process the data quality is scored on a scale from 1–4 with respect to Technology, Time, Geography, Completeness and Reliability. The scores from 1 to 4 reflect whether the data are “poor”, “fair”, “good” or “very good”. In this way an operational overview is established, but it must be acknowledged that the scoring to a large extent is subjective and that the matrix is not equally well suited to address all types of processes. It is also noted that many of the unit processes scored in this way in fact reflects aggregated values established from a number of sub-processes. Finally, it is mentioned that some unit processes have not been scored with respect to data quality, because they are judged to be without importance in the overall results.


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