Three methods for strategic product toxicity assessment - the case of the cotton T-shirt

Journal article, 2015

Purpose: The use and emission of chemicals and the intrinsic toxic properties of some of these chemicals are an important topic in the textile industry. Quantitative evaluation of toxic impacts is a life cycle assessment (LCA) approach, termed “toxic footprint” in this article. We ask whether calculation of toxic footprints is a useful method to steer the textile industry towards more sustainable use of chemicals. Methods: Three different methods by which strategic product toxicity assessment can be performed within the context of LCA are illustrated and compared using a wet treatment process for a cotton T-shirt as the basis of a case study. The methods are the USEtox model chosen for the European Product Environmental Footprint work, the Score System presented in the European Commission’s Reference Document on Best Available Techniques for the Textiles Industry, and the Strategy Tool presented by Askham. The methods are compared in terms of their ease of use and whether the results give a consistent evaluation of a set of chemicals. Results and discussion: New USEtox characterisation factors for textile chemicals were calculated and used for this article. The results show that the three methods do not give a consistent evaluation of the different wet treatment chemicals. Both the Score System and the Strategy Tool are very concerned with persistent contaminants such as the optical brightener in this case study, which is deemed to be less important by USEtox. The calculations also show how the results generated by the USEtox model depend on whether users apply (1) only the recommended characterisation factors or (2) these and the interim characterisation factors or (3) these and the new characterisation factors calculated for this article. Conclusions and recommendations: With current policy initiatives such as the Product Environmental Footprint now being applied for textile products, toxicity assessment will by default be performed in the LCA of textiles. It is important that the results are relevant and representative as the intended users are supposed to take actions based on them. Confidence in the results is crucial for a scientific method, and therefore, this exploratory comparison exercise shows how benchmarking can be a tool to make the differences in background assumptions explicit, to better understand the differences in the results, and help create such confidence.