Environmental sustainability assessment of a polyester T-shirt – Comparison of circularity strategies

Abstract

The considerable environmental burden of textiles is currently globally recognized. This burden can be mitigated by applying circular economy (CE) strategies to the commonly linear, short garment life cycles that end with incineration or landfill disposal. Even though all CE strategies strive to promote environmental sustainability, they might not be equally beneficial. Environmental data on different textile products is insufficiently available, which leads to complications when assessing and deciding on different CE strategies to be implemented. This paper studies the environmental impacts of a polyester T-shirt's linear life cycle through life cycle assessment (LCA) and evaluates the benefits attainable by adopting different CE strategies, and their order of priority, while noting uncertainty arising from poor data quality or unavailability. The LCA is complemented by assessing health and environmental risks related to the different options. Most of the linear life cycle's LCA-based impacts arise from use-phase washing. Hence, it is possible to reduce the environmental impact notably (37 %) by reducing the washing frequency. Adopting a CE strategy in which the shirt is reused by a second consumer, to double the number of uses, enables an 18 % impact reduction. Repurposing recycled materials to produce the T-shirt and recycling the T-shirt material itself emerged as the least impactful CE strategies. From the risk perspective, reusing the garment is the most efficient way to reduce environmental and health risks while washing frequency has a very limited effect. Combining different CE strategies offers the greatest potential for reducing both environmental impacts as well as risks. Data gaps and assumptions related to the use phase cause the highest uncertainty in the LCA results. To gain the maximum environmental benefits of utilizing CE strategies on polyester garments, consumer actions, design solutions, and transparent data sharing are needed.