The topic of shedding of micro-sized polymeric particles, so called microplastics, from textiles has been covered by an increasing number of studies over the past years. However, the methods with which the shedding of microplastics from textiles has been measured so far has shown a large variation. Consequently, the results regarding the amount of shed particles also vary, from 120 to 728,289 particles from similar garments in recent studies. This article presents research enabling for identification of whether the shedding of microplastics from different types of fabric was dependent on construction parameters. As none of the methods in the existing literature could be used for evaluating shedding of microplastics from textiles, a method was developed for this purpose. The resulting final method is described in this paper as well as the work with minimizing the error sources and consequently the standard deviation of the results through selection of material samples, equipment and procedure for sample preparation, washing, filtering the washing water and analyzing the shed microplastics. Comparing the environmental load of different garments, or identifying improvement possibilities in garment construction are two examples of how the method can be utilized.

The applicability of life-cycle assessment (LCA) for the textile industry is discussed with a special focus on environmental impact from chemicals. Together with issues of water depletion and energy use, the use of chemicals and their emissions are important environmental considerations for textile products. However, accounting for chemicals is a weak point in LCA methodology and practice. Two research questions were investigated in a case study of hospital garments: 1) whether LCA adds value to assessments of the chemical performance of textile products, and 2) whether inclusion of toxicity issues in LCA affects environmental performance rankings for textile products. It is concluded that the quantitative and holistic tool LCA is useful for environmental decision makers in the textile industry, and becomes more effective when chemical impacts are included. A flexible way forward is demonstrated to meet the challenge of accounting for chemicals in LCAs of textile products.

Toxicity impacts of chemicals have only been covered to a minor extent in LCA studies of textile products. The two main reasons for this exclusion are (1) the lack of life cycle inventory (LCI) data on use and emissions of textile-related chemicals, and (2) the lack of life cycle impact assessment (LCIA) data for calculating impacts based on the LCI data. This paper addresses the first of these two.

Purpose Life cycle assessments (LCAs) of textile products which do not include the use and emission of textile chemicals, such as dyes, softeners and water-repellent agents, will give non-comprehensive results for the toxicity impact potential. The purpose of this paper is twofold: (1) to provide a set of characterisation factors (CFs) for some of the most common textile chemicals and (2) to propose a data source selection strategy in order to increase transparency when calculating new CFs. Methods A set of 72 common textile-related substances was matched with the USEtox 2.01, USEtox 1.01 and the COSMEDE databases in order to investigate coverage and coherence. For the 25 chemicals that did not already have established CFs in any of these databases, new CFs were calculated. A data source selection strategy was developed and followed in order to ensure consistency and transparency, and USEtox 2.01 was used for calculations. The parameters that caused the most uncertainty were identified during the modelling and strategies for handling them were developed. Results and discussion Of the 72 textile-related substances, 48 already had calculated recommended or indicative CFs in existing databases, which showed good coherence. The main uncertainty identified during the calculation of 25 new CFs was the selection of input data regarding toxicity and degradation in water. However, for substances such as per- and polyfluoroalkyl substances (PFAS), the acid dissociation constant (pK_a) and partitioning coefficients (K _ow and K_OC) also require special considerations. Other input parameters had less than one order of magnitude impact on the CF result for essentially all substances. Conclusions The paper presents a strategy for how to provide a complete set of toxicity CFs for a given list of substances. In addition, such a set of CFs for common textile-related substances is presented. The data source selection strategy provides a structured and transparent way of calculating additional CFs for textile chemicals with USEtox. Consequently, this study can help future LCA studies to provide relevant guidance towards environmentally benign chemical management in the textile industry.