Horn 2023_Tschirt LCA

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<p>Science of the Total Environment 884 (2023) 163821</p><p>Contents lists available at ScienceDirect</p><p>Science of the Total Environment</p><p>j ourna l homepage: www.e lsev ie r .com/ locate /sc i totenv</p><p>Environmental sustainability assessment of a polyester T-shirt – Comparison</p><p>of circularity strategies</p><p>Susanna Horn a,⁎, Kiia M. Mölsä a, Jaana Sorvari a, Hannamaija Tuovila b, Pirjo Heikkilä b</p><p>a Finnish Environment Institute, Latokartanonkaari 11, 00790 Helsinki, Finland</p><p>b VTT Technical Research Centre of Finland Ltd, Visiokatu 4, 33103 Tampere, Finland</p><p>H I G H L I G H T S G R A P H I C A L A B S T R A C T</p><p>⁎ Corresponding author.</p><p>E-mail address: susanna.horn@syke.fi (S. Horn).</p><p>http://dx.doi.org/10.1016/j.scitotenv.2023.163821</p><p>Received 30 August 2022; Received in revised form 1</p><p>Available online 1 May 2023</p><p>0048-9697/© 2023 The Authors. Published by Elsevi</p><p>• Life cycle assessment and risk assessment</p><p>offer complementary perspectives.</p><p>• Circularity strategies for a polyester shirt</p><p>yield different environmental benefits.</p><p>• Less washing reduces most LCA impacts</p><p>while reuse is most efficient in lowering</p><p>risks.</p><p>• However, the maximum benefit from cir-</p><p>cularity requires a set of different solu-</p><p>tions.</p><p>• Lack of life cycle data is a major cause hin-</p><p>dering informed decision-making.</p><p>A B S T R A C T</p><p>A R T I C L E I N F O</p><p>Editor: Deyi Hou</p><p>Keywords:</p><p>Life cycle assessment</p><p>Environmental impacts</p><p>Circular economy</p><p>Textile</p><p>Health risk</p><p>Environmental risk</p><p>The considerable environmental burden of textiles is currently globally recognized. This burden can be mitigated by</p><p>applying circular economy (CE) strategies to the commonly linear, short garment life cycles that end with incineration</p><p>or landfill disposal. Even though all CE strategies strive to promote environmental sustainability, they might not be</p><p>equally beneficial. Environmental data on different textile products is insufficiently available, which leads to compli-</p><p>cations when assessing and deciding on different CE strategies to be implemented. This paper studies the environmen-</p><p>tal impacts of a polyester T-shirts linear life cycle through life cycle assessment (LCA) and evaluates the benefits</p><p>attainable by adopting different CE strategies, and their order of priority, while noting uncertainty arising from poor</p><p>data quality or unavailability. The LCA is complemented by assessing health and environmental risks related to the dif-</p><p>ferent options. Most of the linear life cycle's LCA-based impacts arise from use-phase washing. Hence, it is possible to</p><p>reduce the environmental impact notably (37 %) by reducing the washing frequency. Adopting a CE strategy in which</p><p>the shirt is reused by a second consumer, to double the number of uses, enables an 18% impact reduction. Repurposing</p><p>recycled materials to produce the T-shirt and recycling the T-shirt material itself emerged as the least impactful CE</p><p>strategies. From the risk perspective, reusing the garment is themost efficient way to reduce environmental and health</p><p>risks while washing frequency has a very limited effect. Combining different CE strategies offers the greatest potential</p><p>for reducing both environmental impacts as well as risks. Data gaps and assumptions related to the use phase cause the</p><p>highest uncertainty in the LCA results. To gain themaximum environmental benefits of utilizing CE strategies on poly-</p><p>ester garments, consumer actions, design solutions, and transparent data sharing are needed.</p><p>1 April 2023; Accepted 25 April 2</p><p>er B.V. This is an open access artic</p><p>1. Introduction</p><p>The current textile industry is facedwith significant environmental con-</p><p>cerns caused by resource-intensive value chains and further aggravated by</p><p>023</p><p>le under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</p><p>http://crossmark.crossref.org/dialog/?doi=10.1016/j.scitotenv.2023.163821&domain=pdf</p><p>http://dx.doi.org/10.1016/j.scitotenv.2023.163821</p><p>mailto:susanna.horn@syke.fi</p><p>Journal logo</p><p>http://dx.doi.org/10.1016/j.scitotenv.2023.163821</p><p>http://creativecommons.org/licenses/by/4.0/</p><p>Unlabelled image</p><p>http://www.sciencedirect.com/science/journal/00489697</p><p>www.elsevier.com/locate/scitotenv</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>the sheer size of the market. The textiles sector contributes to 8–10 % of</p><p>global climate change (Quantis, 2018; United Nations Climate Change,</p><p>2018), produces over 92million tons of waste, and consumes 79 trillion liters</p><p>of water per year (Niinimäki et al., 2020). Furthermore, textiles' value chains</p><p>cause 16–35 % of ocean-bound microplastics (EEA (European Environment</p><p>Agency), 2022) and use hazardous chemicals (e.g., Chequer et al., 2013),</p><p>which lead to environmental risks. One of the root causes of these significant</p><p>environmental concerns arises from the textile industry relying on short-lived</p><p>garments, coupled with fast fashion business models in which issues such as</p><p>reusability, repairability, and recyclability are rarely considered. Fast fashion</p><p>has led to increased consumption volumes, shorter lifespans of garments, and</p><p>products that are treated as almost disposable (Remy et al., 2016; European</p><p>Environment Agency, 2019). Due to lower production costs, textilemanufac-</p><p>ture has moved from Western countries mainly to Asia (Ellen MacArthur</p><p>Foundation, 2017; WTO (World Trade Organisation), 2021), making related</p><p>social and environmental aspects often imperceptible toWestern consumers.</p><p>Currently, 85% of primary rawmaterial use, 92% of water use, 93% of land</p><p>use, and 76 % of climate impacts of the production of textiles consumed in</p><p>Europe occur in other regions of the world (EEA, 2019).</p><p>Based on their environmental impacts, risks, and circularity potential, tex-</p><p>tiles have been identified as a priority product group for implementing novel</p><p>circular practices covering the whole life cycle of the product (EC (European</p><p>Commission), 2020). According to the EU's textile strategy (EC, 2022), fast</p><p>fashion and a growing demand for textiles is fueling the inefficient use of</p><p>non-renewable resources, including the production of synthetic fibers from</p><p>fossil fuels. For more sustainable value chains, circular economy (CE)-based</p><p>actions are needed not only to cover the collection of textile waste and</p><p>recycling, but also to include production and consumption patterns to favor</p><p>environmentally sound raw materials, facilitate longer lifetimes, utilize pro-</p><p>duction processes that generate less waste and fewer emissions, and phase</p><p>out hazardous chemicals (European Environment Agency, 2019). It has</p><p>been noted that different CE strategies offer diverse benefits, also varying</p><p>with the type of textile product. Recently, there has been a growing interest</p><p>in amore nuanced hierarchy of CE-based actions, emphasizing smarter prod-</p><p>uct use or extension of life cycles, which enable greater value retention than</p><p>actions focusing on recycling, for example (Reike et al., 2018).</p><p>Although several life cycle assessment (LCA) or risk-based case studies</p><p>exist for textiles, there is currently limited knowledge available to assess</p><p>and compare different CE options for different types of textiles, covering</p><p>both perspectives. Moreover, polyester textiles have received little attention</p><p>in recent LCA studies compared to their large market share (Statista, 2022).</p><p>To fill this research gap, this study endeavors to estimate the environmental</p><p>sustainability of selected CE-based strategies in a practical case example of a</p><p>polyester T-shirt in Finland, using LCA and risk approaches as study</p><p>methods. The impacts of the CE strategies are compared to the current linear</p><p>practice, as well as to each other, through individually defined scenarios im-</p><p>plementing these strategies, either separately or in combination. As data</p><p>availability and traceability are critical factors for such assessments (Papú</p><p>Carrone, 2020), data quality issues are taken into consideration through un-</p><p>certainty analysis.</p><p>The research questions are:</p><p>1. What are the environmental impacts of a polyester T-shirts full value</p><p>chain, and how will different circular economy</p><p>stud-</p><p>ied by LCA, since they would reduce the environmental impacts only by</p><p>8–9 % in comparison to the baseline. This result is in line with Potting</p><p>et al. (2017) order of priority, in identifying recycling and repurposing as</p><p>the least favorable options after energy recovery. The results from the risk</p><p>identification also indicate a relatively modest overall reduction of health</p><p>and environmental risks in these scenarios.</p><p>The two scenarios impacting the number of uses of the garment (S2</p><p>reuse and S3 remanufacture) lead to a similar impact reduction of</p><p>approximately 18 % compared to the baseline. However, the way in</p><p>which reusability is implemented becomes a significant factor. In our</p><p>study, remanufacturing considered only minor material additions (addi-</p><p>tional printings) and minor additional logistics in addition to the reuse sce-</p><p>nario. In fact, the remanufacturing strategy may be close to Potting et al.</p><p>(2017) rethink strategy, which makes product use more intensive through</p><p>sharing. Even though Potting raised rethink as a highly prioritized option,</p><p>in the case of garments, offering the product as a servicemay increase trans-</p><p>ports, washing, and drying substantially, as Zamani et al. (2017), have ar-</p><p>gued. If the garment is sent to the service provider, and washed and dried</p><p>after each use, this causes increasingly more environmental impacts rela-</p><p>tive to each use. In our case, we did not consider this option, since in the</p><p>case of sports T-shirts, it was not considered viable. The reuse and</p><p>remanufacturing scenarios (S2 and S3) are the most efficient in decreasing</p><p>12</p><p>the health and environmental risks as a consequence of increased use times</p><p>(assumably leading to reduced production volumes). Compared to S2, the</p><p>contribution of S3 to the reduction of occupational risks is slightly lower,</p><p>due to remanufacturing, which involves removal of old printing material.</p><p>The option providing clearly the most environmental savings estimated</p><p>by LCA (−37 %) was the reduce option (S6), in which it was considered</p><p>that the T-shirt would be washed less frequently (100 washes instead of</p><p>150 per 200 uses) and not tumble dried. This result is sensitive to the num-</p><p>ber of uses, as well as the equipment's energy and load efficiency, as well as</p><p>to the sources of electricity. The viability of the option is also dependent on</p><p>the users' personal preferences. Since the use times of T-shirts was expected</p><p>to remain unchanged in S6 (hence, no impact on production volumes), less</p><p>frequent cleaning at the use phase would result only in a negligible reduc-</p><p>tion of the overall risks during the life cycle of a T-shirt.</p><p>By introducing all CE strategies simultaneously (S7), a 70 % of reduc-</p><p>tion in total, weighted environmental impacts can be achieved, of which</p><p>the reduction in climate change impact and resource depletion are the</p><p>most dominant ones. Additionally, the health and environmental risks are</p><p>reduced considerably. Summing up, CE solutions are often most impactful</p><p>when a combination of different methods are introduced, instead of relying</p><p>on an individual solution.</p><p>Our results show that less washing and drying of garments and longer</p><p>life cycles enable considerable environmental benefits. Attaining these de-</p><p>pends on consumers' behavior; they need to be adequately informed of</p><p>the effects of their choices and to be willing to change their behavior ac-</p><p>cordingly. Indirectly, the consumer may also affect the impacts of the</p><p>end-of-life andmanufacturing stages through their purchasing and disposal</p><p>actions. However, the responsibility of CE utilization does not lie solely</p><p>with the consumers. It is primarily the manufacturers and brand owners</p><p>who need to take these perspectives into consideration in their design</p><p>choices. The garments should be designed for circularity to support long-</p><p>term trends, durability and reusability, repairability, and recyclability,</p><p>while considering safety to the environment and humans. Moreover, even</p><p>though the results propose a certain order of priority for selected CE solu-</p><p>tions, these may be contested due to the selection of studied indicators</p><p>and how the indicators are prioritized in case tradeoff situations occur</p><p>(Niero and Kalbar, 2019).</p><p>5.1.3. Life cycle data issues remain problematic</p><p>Even though the manufacturing processes of various products are being</p><p>digitalized, and there is an increasing amount of data available, there are</p><p>still substantial data gaps, and in addition, the data is scattered or not us-</p><p>able, and it does not easily support transformative decision-making</p><p>(Circle Economy, 2019). In our study, significant uncertainties were in-</p><p>volved in the LCA data. The most significant data gaps and their contribu-</p><p>tion to the result uncertainty, studied using Monte Carlo analysis</p><p>(Heijungs and Huijbregts, 2004), were related to the use phase. If the num-</p><p>ber of uses in different scenarios changes, so may the order of priority</p><p>between them.</p><p>The assessment of the environmental and health riskswas limited due to</p><p>a lack of factual case-specific data on chemicals and other harmful sub-</p><p>stances, such as microplastics. This lack of data prevented us from con-</p><p>ducting a truly case-specific risk assessment. Therefore, a conservative</p><p>approach was used and risks were scored for different scenarios on the</p><p>basis of toxicity data and reference values of the most critical substances</p><p>(identified based on literature). It needs to be noted that this can lead to</p><p>an overestimation of risks, while risks of some contaminants, such as</p><p>microplastics and nanoparticles, can be underestimated due to lack of tox-</p><p>icity reference values. For more realistic quantitative risk estimates, case-</p><p>specific data is required.</p><p>To enable a shift from a linear textile value chain to a more circular and</p><p>sustainable one, data availability and traceability is necessary for informed</p><p>decision-making (Papú Carrone, 2020). Even though the absolute level of</p><p>the results may not be vitally important in this case, the different options'</p><p>order of priority, as well as the order of magnitude of the benefits attained</p><p>or risks avoided, provides important information for the decision-maker.</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>Visibility to the full value chain is a key aspect in designing for more envi-</p><p>ronmentally sound life cycles, as it allows for more reliable and up-to-date</p><p>data for environmental monitoring and CE applications. However, in prac-</p><p>tice, obtaining reliable data can be very challenging (Hospido et al., 2010),</p><p>as the brand owners, selling the garments to consumers, often have limited</p><p>visibility to the value chain, both upstream and downstream.</p><p>6. Conclusions and future prospects</p><p>Moving toward an environmentally sound CE requires capabilities to as-</p><p>sess and compare value chains and their environmental impacts and risks</p><p>analytically. The different CE options available need to be assessed from a</p><p>holistic environmental perspective, according to which the solutions to be</p><p>implemented can be chosen. To support this choice, we produced informa-</p><p>tion on the relevant environmental impacts, as well as on health and envi-</p><p>ronmental risks of a polyester T-shirts life cycle, and assessed how different</p><p>CE scenarios would affect these.</p><p>Based on the results, the most beneficial strategy from the LCA-</p><p>perspective is reduction of washing and drying between uses. On the</p><p>other hand, reusing the garment is themost efficientway to reduce environ-</p><p>mental and health risks caused by harmful substances. In the LCA results,</p><p>reuse (with or without remanufacturing) was the second best option. The</p><p>greatest environmental benefits in terms of LCA based impacts as well as</p><p>the environmental and health risks could be gained by combining the stud-</p><p>ied strategies of washing less frequently, reusing the shirt, utilizing recycled</p><p>materials, and recycling the polyester after use. Hence, to achieve the full</p><p>benefits fromCE, the textile sector cannot rely on a single action, but should</p><p>rather implement a combination of several practical solutions.</p><p>Moreover,</p><p>the magnitude of the benefits is dependent on the consumers' behavior;</p><p>they need to be adequately informed of the effects of less washing and lon-</p><p>ger life cycles, and to be willing to change their behavior accordingly. Be-</p><p>sides raising consumer awareness, the design of garments for long-term</p><p>use, recyclability, and chemical safety is essential for a more sustainable</p><p>value chain.</p><p>The uncertainty of the study results is derived from the gaps in both</p><p>life cycle and chemical data, which, in the case of risks, prevented the</p><p>generation of robust case-specific assessment. The absence of data is a</p><p>common problem in similar studies and the textile sector in general,</p><p>which causes difficulties in realistically prioritizing and applying CE</p><p>strategies. The availability of more transparent, traceable, and up-to-date</p><p>data would offer more accurate results and make it easier to include these</p><p>issues in policy development. Better visibility of all types of environmental</p><p>data could be gained if value chain actors began demanding more specific</p><p>and factual information over the full value chain, for example, through dig-</p><p>ital product passports or clearer eco-labels. Regulations or other policies,</p><p>such as the EU's Chemicals Strategy, will also push producers toward</p><p>more sustainable processes. In the end, the use phase data may remain</p><p>scattered and undisclosable due to, for example, technical and privacy</p><p>constraints.</p><p>Data availability</p><p>Data will be made available on request.</p><p>Declaration of competing interest</p><p>The authors declare that they have no known competing financial inter-</p><p>ests or personal relationships that could have appeared to influence the</p><p>work reported in this paper.</p><p>Acknowledgments</p><p>This work was supported by the Academy of Finland (grant nos.</p><p>337717, 327300) as part of the projects “Circular Design Network</p><p>(CircDNet)” and “Sustainable textile systems: Co-creating resource-wise</p><p>business for Finland in global textile networks (FINIX).”</p><p>13</p><p>CRediT authorship contribution statement</p><p>Susanna Horn: life cycle assessment, conceptualization, data curation</p><p>and analysis, methodology, investigation, project administration, writing –</p><p>original draft, writing – review & editing, visualization</p><p>Kiia M. Mölsä: life cycle assessment, conceptualization, data curation</p><p>and analysis, methodology, investigation, writing – original draft, writing –</p><p>review & editing, visualization</p><p>Jaana Sorvari: Identification of the risks related to potential contami-</p><p>nants, conceptualization, data compilation and analysis, formal analysis,</p><p>methodology, investigation, writing – original draft, writing – review &</p><p>editing</p><p>Hannamaija Tuovila: writing – original draft</p><p>Pirjo Heikkilä: writing – original draft</p><p>Appendix A. Supplementary data</p><p>Supplementary data to this article can be found online at https://doi.</p><p>org/10.1016/j.scitotenv.2023.163821.</p><p>References</p><p>Avagyan, R., Luongo, G., Thorsén, G., Östman, C., 2015. Benzothiazole, benzotriazole, and</p><p>their derivates in clothing textiles–a potential source of environmental pollutants and</p><p>human exposure. Environ. Sci. Pollut. Res. 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sustainability assessment of a polyester T-�shirt – Comparison of circularity strategies</p><p>1. Introduction</p><p>2. Background</p><p>2.1. Circular economy in the context of textiles</p><p>2.2. A polyester T-shirts life cycle and related environmental impacts</p><p>2.3. Textiles and chemical safety</p><p>2.4. Life cycle data problems and related uncertainties</p><p>3. Methods and data</p><p>3.1. Life cycle assessment and assessment of chemical risks</p><p>3.2. T-shirt system boundaries, scenarios, and data</p><p>4. Results</p><p>4.1. Life cycle impact assessment</p><p>4.1.1. Baseline scenario (S1)</p><p>4.1.2. Comparison of scenarios</p><p>4.1.3. Data uncertainty</p><p>4.2. Risks to the environment and human health</p><p>4.2.1. Potential critical contaminants and consequent risks</p><p>4.2.2. Risks caused by contaminants in different circularity scenarios</p><p>5. Discussion</p><p>Outline placeholder</p><p>5.1.1. Most LCA-based impacts from the use phase</p><p>5.1.2. Different CE strategies offer unequal benefits</p><p>5.1.3. Life cycle data issues remain problematic</p><p>6. Conclusions and future prospects</p><p>Declaration of competing interest</p><p>section25</p><p>Acknowledgments</p><p>CRediT authorship contribution statement</p><p>Appendix A. Supplementary data</p><p>References</p><p>strategies affect these?</p><p>What are the most significant causes of uncertainty in the assessment,</p><p>and how does this data uncertainty affect the results?</p><p>2. What types of environmental and health risks arise from the potential</p><p>contaminants, such as chemicals and other relevant harmful elements</p><p>(microplastics, fibers), during the life cycle of a T-shirt, and howwill dif-</p><p>ferent circular economy strategies affect these?</p><p>2. Background</p><p>2.1. Circular economy in the context of textiles</p><p>ACE-based textiles system is described as a system “… that is restorative</p><p>and regenerative by design and provides benefits for business, society and</p><p>2</p><p>the environment. A system in which clothes, fabric and fibers are kept at</p><p>their highest value during use, and re-enter the economy after use, never</p><p>ending up aswaste” (EllenMacArthur Foundation, 2017). To achieve circu-</p><p>larity, fundamental and systemic changes are required across the textile</p><p>value chain (EEA, 2019) and on different levels of society.</p><p>Often, all CE-based approaches are considered to be intrinsically benefi-</p><p>cial, regardless of how they are operationalized in practice. However, the</p><p>environmental benefits of CE vary among the different alternatives</p><p>(Potting et al., 2017), sometimes not yielding benefits at all or entailing sig-</p><p>nificant tradeoffs (Roos Lindgreen et al., 2021). For this reason, a more de-</p><p>tailed prioritization of different approaches, or so-called CE (or R-)</p><p>strategies, has been developed to attain a higher degree of circularity, to re-</p><p>duce the related environmental impacts, and to improve resource efficiency</p><p>in products (see, e.g., Potting et al., 2017; CE and MVO, 2015). The com-</p><p>monly used CE strategies are presented in Fig. 1 in order of priority.</p><p>For example, recycling (R9) may generate less environmental benefits</p><p>compared to other CE approaches (Ghisellini et al., 2016). The magnitude</p><p>of the environmental benefits depends on the used raw materials, the com-</p><p>plexity of product design, recycling technologies, and the presence and ac-</p><p>cumulation of hazardous materials, among other things. If the number of</p><p>uses could be increased (as in R3, R4, R5), the resources needed for produc-</p><p>tion and the waste rates of consumption could be decreased nearly in the</p><p>same proportion (Stahel, 2017). Approaches falling under rethink (R1),</p><p>such as products-as-a-service models, may shift textile consumption onto</p><p>a more sustainable basis by prolonging the life cycle, but increased logistics</p><p>may reduce the overall benefits of such models (Zamani et al., 2017).</p><p>Hence, the order of priority of the CE strategies is ambiguous and depends</p><p>on the product at hand andmay vary depending on themetrics used to com-</p><p>pare different options (Niero and Kalbar, 2019). Ultimately, the choice</p><p>should be based on analytical grounds, providing more insight into the po-</p><p>tential benefits of each option at hand (Roos Lindgreen et al., 2021).</p><p>2.2. A polyester T-shirts life cycle and related environmental impacts</p><p>The process of producing polyester T-shirts consists of producing fibers,</p><p>spinning yarns, knitting or weaving them into fabrics, dyeing, and sewing.</p><p>The fibers used for polyester's synthetic, fossil-based polymers are derived</p><p>from coal, air, water, and petroleum. Fibers may be spun from colored poly-</p><p>mers or dyed after knitting. Finished fabrics are cut and sewn into T-shirts.</p><p>The use phase is mainly influenced by consumer behavior and includes</p><p>varying numbers of uses, washes, and maintenance activities. From the</p><p>CE perspective, both the design and use phases are of central importance,</p><p>as these can provide significant points for optimization (Stahel, 2017;</p><p>Schwarz et al., 2017). For example, extending and intensifying use, reusing</p><p>the same product in a new context, and other innovative reuse models are</p><p>examples of such measures (Niinimäki, 2018). The last phases of the life</p><p>cycle include different end-of-life options, such as recycling, incineration,</p><p>or landfill disposal (outside the EU). Polyester can be recycled into second-</p><p>ary rawmaterials for textile or other industries using different mechanical,</p><p>thermo-mechanical, chemical, and thermal processes (e.g., Damayanti</p><p>et al., 2021; Dissanayake and Weerasinghe, 2021). Currently, less than</p><p>1 % of discarded textiles are recycled into new fibers globally (Ellen</p><p>MacArthur Foundation, 2017), and as for polyester, 15 % polyester fibers</p><p>produced worldwide came from recycled materials (Textile Exchange,</p><p>2022).</p><p>Several LCA-based case studies exist for textiles (for a review, see</p><p>Munasinghe et al., 2021), but less so for polyester, in particular. For exam-</p><p>ple, van der Velden et al. (2014) have carried out a comparative LCA study-</p><p>ing the impacts of cotton, polyester (PET), nylon, acrylic, and elastane,</p><p>according to which the environmental burden correlates with the choice</p><p>of the base material and also with the thickness of the yarn. According to</p><p>their study, textiles made from acrylic and PET have the least impact on</p><p>the environment. Sandin et al. (2019) have compared the environmental</p><p>impacts of different garments, manufactured from different material mix-</p><p>tures of cotton, polyester, polyamide, and viscose. Both van der Velden</p><p>et al. (2014) and Sandin et al. (2019) conclude that the use phase impacts</p><p>Fig. 1. Circular economy strategies (based on Potting et al., 2017).</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>are relatively small, mainly due to short life cycles, or in other words the as-</p><p>sumption of a relatively small number of uses. As for recycled polyester,</p><p>Zhang et al. (2020a) have made an LCA of blankets made of recycled PET</p><p>bottles. According to their results, production processes (steam and</p><p>recycled polyester filament production) caused most environmental im-</p><p>pacts, as well; however, the use phase was omitted from the analysis.</p><p>Using secondary data, Wu (2020) studied a polyester T-shirt and found a</p><p>use phase of 52 washes to be the main factor behind the environmental im-</p><p>pacts. It is noteworthy that while most of the LCA studies focus on climate</p><p>impacts and energy consumption, less focus is given to water usage, chem-</p><p>ical usage, and emissions to water and land, or to assessments covering sev-</p><p>eral impact categories (Munasinghe et al., 2021).</p><p>2.3. Textiles and chemical safety</p><p>The safety of chemicals used in the different life stages of the product is</p><p>becoming an increasingly prevalent issue, which can contribute signifi-</p><p>cantly to its sustainability. Various chemicals are used during the manufac-</p><p>ture of garments, and these chemicals may enter the environment via</p><p>different transport routes. For example, textile industry wastewater is con-</p><p>sidered to be one of theworst polluters of water and soil ecosystems (Kishor</p><p>et al., 2021), and synthetic fibers spreading from domestic washing are a</p><p>main source of microplastic (Cesa et al., 2017). Moreover, although many</p><p>process chemicals aremeant tomodify the rawmaterial or used as auxiliary</p><p>chemicals to bring about a desired reaction and, hence, not to stay in the</p><p>final product, their residues or reaction products may remain in the final</p><p>clothing. Again, some chemicals, such as UV stabilizers used for protecting</p><p>clothing against sunlight, are meant to stay in the final product. Chemical</p><p>safety has been highlighted as a crucial issue in the implementation of</p><p>CE, meaning that any harmful substances present in the circular system</p><p>need to be managed, for example by removing them from the cycle if</p><p>they pose a significant risk to the environment or human health or aggra-</p><p>vate the recycling of materials.</p><p>At present, chemicals are heavily regulated in the EU (Regulation 1907/</p><p>2006, Directives 98/24/EC, 2004/37/EC, 2019/1831, 2017/164/EU).</p><p>Many such regulations apply, besides manufacturers, also to, for example,</p><p>importers of clothes. Even though these policy instruments are in place in</p><p>the EU, they are still absent in many countries where textiles are produced.</p><p>Therefore, risks arising from chemicals used in the manufacture of gar-</p><p>ments marketed in Finland</p><p>cannot be excluded.</p><p>3</p><p>2.4. Life cycle data problems and related uncertainties</p><p>Collecting reliable life cycle data, covering LCA and risk-related data, is</p><p>a major challenge due to the complexities of tracking and quantifying in-</p><p>puts and outputs at multiple supply chain stages (Zhang et al., 2020b).</p><p>Even though the data is increasingly used in decision-making, it may not</p><p>be transparent or of high-quality (Galatola and Pant, 2014). Particularly</p><p>in the context of LCA and textiles, Munasinghe et al. (2021) identified</p><p>gaps in the availability of life cycle data and provided recommendations</p><p>for LCA studies to address these gaps, as without comprehensive data, ro-</p><p>bust decisions cannot be made. Minimum data quality requirements need</p><p>to be in place, which go beyond reporting data quality (Manfredi et al.,</p><p>2015). For example, an environmental improvement at one stage may</p><p>lead to negative environmental impacts in another part of the life cycle,</p><p>or may cause different types of environmental impacts. The data on differ-</p><p>ent impacts should be reliable and up-to-date, and the impact assessment</p><p>methods should be comparable with each other. For textiles, the use</p><p>phase data, such as the number of uses or washing times, or the use of</p><p>driers, is often difficult to obtain (van der Velden et al., 2014), uncertain,</p><p>and of a different scale (Barnardo's, 2015, ref. in Lerpiniere, 2020), which</p><p>is why the used assumptions need to be tested. In addition to the use</p><p>phase, the global and complex textiles value chain poses challenges for col-</p><p>lecting data on, for example, chemical consumption related to the raw ma-</p><p>terials acquisition and manufacturing phases, and it is often difficult, if not</p><p>impossible, for designers to obtain first-hand and reliable data on their raw</p><p>materials from countries such as China, Bangladesh, or India (Finnish</p><p>Textile &amp and Fashion, 2022).</p><p>3. Methods and data</p><p>3.1. Life cycle assessment and assessment of chemical risks</p><p>LCA is a standardized method of compiling and evaluating the inputs,</p><p>outputs, and potential environmental impacts of a product system through-</p><p>out its life cycle (ISO 14040, 2011). The method acknowledges each life</p><p>cycle stage of a product or service (Baumann and Tillman, 2004) and mul-</p><p>tiple environmental impact categories (EC, 2012). Thus, LCA is useful to</p><p>avoid problem-shifting and increase awareness of trade-offs between life</p><p>cycle phases and different impacts (Finnveden et al., 2009). In this study,</p><p>we utilized LCA to quantify the environmental impacts of the linear system,</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>as well as to study the benefits generated by the various circular economy</p><p>strategies in the context of a polyester T-shirt. The used impact assessment</p><p>method was EF 2.0 (Fazio et al., 2018). The European Commission’s PEF</p><p>guidance (Zampori and Pant, 2019) and the PEF category rules (PEFCR)</p><p>for a T-Shirt (Pesnel and Payet, 2019) were used as methodological guid-</p><p>ance for: 1) choosing the most relevant impact categories, 2) applying the</p><p>circular footprint formula, including allocation factors, and 3) determining</p><p>the normalization and weighting factors for the results. In accordance with</p><p>the PEFCR, the normalized results were used as a basis for comparison be-</p><p>tween the scenarios and impact categories. The normalization factors repre-</p><p>sent the total impact of a reference region, in this case the global impacts,</p><p>for a certain impact category (Sala et al., 2017). The calculation was</p><p>Excel-based, but utilized data from ecoinvent 3.3, among others. The life</p><p>cycle inventory (LCI) data assumptions are detailed in Appendix A.</p><p>In a Monte Carlo analysis, variables are expressed as probable value</p><p>ranges that follow a specific distribution, instead of as deterministic values,</p><p>and a series of calculations are run using random parameter values within</p><p>the given ranges (Raynolds et al., 1999). This sampling reflects the influ-</p><p>ence of uncertain factors more accurately (Heijungs, 2020; Sun and Ertz,</p><p>2020). We studied the uncertainty of the data and subsequent LCIA results</p><p>statistically based on Monte Carlo analysis (Heijungs and Huijbregts,</p><p>2004). Each LCI flow was categorized using a three-scale data quality</p><p>index: 1 (data based on measurement), 2 (data based on secondary litera-</p><p>ture sources), or 3 (data based on estimates by the researchers or involved</p><p>actors). These data quality indexes are presented for individual flows in</p><p>Appendix A. Subsequently, the index was used to assign minimum and</p><p>maximum ranges with 5 %, 10 %, and 30 % deviation for quality indexes</p><p>1, 2, and 3, respectively, when minimum and maximum values were not</p><p>known. The ranges were also assigned for the number of uses of the</p><p>T-shirt in different scenarios, affecting all flows. As for theMonte Carlo sim-</p><p>ulation, an Excel-based add-on tool, Simulacion 5.0, was used with 5000</p><p>sample runs.</p><p>Generation of risk estimates requires data on the full event chain of the</p><p>formation of risks, i.e., data on the source (used chemicals, other harmful</p><p>elements released), transport pathways, exposure routes, and responses</p><p>(of humans, biota) to potential toxic effects in the case of exposure. In this</p><p>study, environmental and human health risks were considered, and the</p><p>most critical risk factors, recipients, and potential toxicity responses arising</p><p>from the possible harmful substances in the different life cycle phases of a</p><p>polyester T-shirt were identified. Due to lack of data on the chemicals</p><p>used in the actual manufacture, a literature search was conducted to iden-</p><p>tify the potential harmful chemicals and other elements, their most critical</p><p>transport and exposure routes, and the environmental and health risks</p><p>these induce. The Substance Infocards provided by the European Chemicals</p><p>Agency (ECHA) were used as a source of ecotoxicity and human toxicity</p><p>data of the identified key substances. In the Infocards, the toxicity to</p><p>aquatic and terrestrial organisms is expressed as a PNEC (Predicted</p><p>No-Effect Concentration) while the human toxicity is indicated by DNELs</p><p>(Derived No-Effect Level) or DMELs (Derived Minimal Effect Level).1</p><p>The assessment of risks to human health and biota was based on a con-</p><p>servative case, meaning the use of the lowest reference values given for a</p><p>particular substance and taking themost harmful substance as a representa-</p><p>tive of the group of chemical substances it belongs to. For example, benzo</p><p>(a)pyrene, which has the highest human toxicity classification, i.e. class 1</p><p>(=carcinogenic to humans) by IARC (International Agency for Research</p><p>on Cancer), was selected as the key contaminant to represent polyaromatic</p><p>hydrocarbons. Hence, the results are in line with risk management follow-</p><p>ing the precautionary principle. In the case of metals, the actual chemical</p><p>1 The DNEL corresponds to the level of exposure above which humans should not be ex-</p><p>posed (ECHA (European Chemicals Agency), 2012). In the case of non-threshold endpoints,</p><p>such as mutagenicity and carcinogenicity, derivation of DNEL has not been possible. In such</p><p>cases, DMELs are provided instead. DMEL refers to a reference risk level considered to be of</p><p>very low concern. Hence, it should be interpreted as a tolerable level of effects, but not a level</p><p>where no effects can be foreseen. Both the DNEL and DMEL take into account the likely route</p><p>(s), duration and frequency of exposure and hence, separate reference values are available for</p><p>workers and general public.</p><p>4</p><p>species present in different life stages were unknown. Therefore, the toxic-</p><p>ity reference values refer to themetallic form,whichmight be relevant only</p><p>in some life stages and exposure routes. The assessment of the risks caused</p><p>by discharges to waterbodies (treated effluent) was complemented by con-</p><p>sidering the prioritization of chemicals used in textile production, con-</p><p>ducted by Tian et al. (2020). This prioritization is based on the USEtox</p><p>model, which generates comparative toxic units (CTU) indicating either</p><p>health hazards (CTUh) or ecological hazards (CTUe)</p><p>based on the toxicity</p><p>and quantity of a substance.</p><p>After the risk identification, a semi-quantitative method, i.e. scoring,</p><p>was conducted to assess the change of chemical risks in each life stage in</p><p>each studied CE scenario (S2-S7) as compared to the baseline scenario</p><p>(S1). The scoring used a scale of 0–4 where 4 denotes the highest potential</p><p>hazard of chemicals and 0 indicates the no-hazard situation. In each life</p><p>stage, the highest score (4) was addressed to the baseline scenario (S1).</p><p>The severity of toxic response(s) of substances present in different life</p><p>stages was taken into account per the severity classification2 presented by</p><p>Burke et al. (1996).</p><p>While LCA generates a quantitative comparison of the environmental</p><p>impacts of different products, or the impacts arising during their life</p><p>cycle, environmental risk assessment integrates information on the envi-</p><p>ronmental fate of, exposure to, and toxicity of chemicals (and other harmful</p><p>elements) and evaluates the likelihood and magnitude of the consequent</p><p>adverse impacts. The risk approach complements LCA by generating more</p><p>detailed and exhaustive information on the potential toxic effects and</p><p>helps to identify critical points in the life cycle that should be targeted to</p><p>avoid such effects. Hence, LCA and risk assessment address different aspects</p><p>of the overall environmental impact. Complementing the LCA with a risk</p><p>approach facilitates a better-informed decision process (Dong et al.,</p><p>2018), e.g., by providing a more exhaustive picture, especially about the</p><p>eco-toxicological and toxicological factors (Jeswani et al., 2010). The com-</p><p>plementary benefits of integrating LCA and environmental risk assessment</p><p>were also confirmed in the review by Muazu et al. (2021).</p><p>3.2. T-shirt system boundaries, scenarios, and data</p><p>The functional unit (FU) of the LCA is defined as “one use of a polyester</p><p>T-shirt.” The chosen system boundary considers the life cycle of a polyester</p><p>T-shirt from rawmaterial acquisition to the end-of-life options (Fig. 2), with</p><p>an extension of raw material substitution for the material recycling option</p><p>and fuel substitution for the energy recovery option. The considered life</p><p>cycle impacts are climate change, water consumption, fresh water and ma-</p><p>rine eutrophication, acidification, disease incidents due to particulate mat-</p><p>ter emissions (respiratory inorganics), and resource depletion of energy</p><p>carriers. In terms of risk identification, the potential presence of chemicals</p><p>in the different phases of the life cycle were considered.</p><p>The life cycle of a new polyester T-shirt begins with extraction of virgin</p><p>raw materials, followed by the polyester fiber and yarn production in</p><p>China. In our case, the yarn is dyed and knitted into fabric and data was</p><p>acquired from the brand owner and its subcontractor. The fabric is</p><p>transported to manufacturing for cutting, sewing, printing, finishing treat-</p><p>ments, and packing, for which data was also acquired from the brand</p><p>owner and its subcontractor. The T-shirt is then transported to Finland for</p><p>retail. Data about the locations and distances was collected from the</p><p>brand owner and its subcontractor. Other supporting data related to</p><p>upstream processes was collected from Ecoinvent 3.3 and literature (see</p><p>Appendix A for inventory details).</p><p>In Finland, specific sports team logos and player identificationmarkings</p><p>(e.g., name and player number) are printed on the shirt before shipping it to</p><p>customers. Due to the lack of available statistical data on the use phase, data</p><p>2 The most severe effects (sub-category 1) are those that cause irreversible/life-shortening</p><p>effects, e.g. cancer, reproductive effects, teratogenic effects, acute fatal or acute severe and ir-</p><p>reversible effects (i.e. fatal poisoning) and mutagenicity. In the other end, there are generally</p><p>reversible/generally not life-shortening effects, such as irritation, sensitization and reversible</p><p>acute organ effects.</p><p>Fig. 2. Scenarios for a polyester T-shirt life cycle.</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>was acquired from the brand owner, but was largely based on assumptions.</p><p>The shirt is used by a player for 80 times per year for 2–3 years on average,</p><p>as stated by the brand owner. This results in 200 uses per one user, after</p><p>which the shirt is currently mostly disposed of by incineration (with energy</p><p>recovery). Alternatively, it could be handed on to another player. On esti-</p><p>mate, the quality of the textile deteriorates after five years of use. This</p><p>means a technical maximum of 400 wears per shirt lifetime can be</p><p>achieved, after which the shirt is incinerated. The uncertainty related the</p><p>use times was identified as high and given the most uncertain quality</p><p>index in the Monte Carlo simulation.</p><p>On estimate, the shirt is washed 0.75 times per use (i.e., washed 150</p><p>times when used 200 times) and tumble dried in 34 % of cases</p><p>(i.e., tumble dried 68 times when used 200 times), as studied by Sandin</p><p>et al. (2019). Depending on user preferences, the shirt can also be washed</p><p>less frequently, e.g. only after every second use (washed 100 times when</p><p>used 200 times) and not tumble dried at all.</p><p>Team logos and player identification prints on the shirt may limit its</p><p>reuse. Rethinking the life cycle, the shirt can be offered as a rented service</p><p>(product-as-service), where the player-specific prints could be changed by</p><p>printing over the old markings. This way, the shirt could be rented for the</p><p>season and reused by another player with their personal markings.</p><p>Overprinting is a new technology, with certain limitations, which can</p><p>only be used for light colored textiles. Data about printing was based on</p><p>Ecoinvent 3.3 and literature (see Appendix A for details).</p><p>It is also possible with current technologies to manufacture a polyester</p><p>T-shirt from recycled and repurposed PET bottles, without compromising</p><p>its quality. In addition, the T-shirt material itself could be mechanically</p><p>recycled at the end of its life, into new polyester fiber. Data about recycling</p><p>was based on Ecoinvent 3.3 and literature (see Appendix A for details).</p><p>To study the different scenarios available for the sports T-shirt seller, we</p><p>distinguished the following six CE strategies (scenarios) for the polyester</p><p>T-shirt life cycle (Fig. 2), in addition to the baseline scenario:</p><p>1. Scenario 1 (S1): Incinerating the T-shirt after the first user and recover-</p><p>ing the energy (baseline).</p><p>5</p><p>2. Scenario 2 (S2): Reusing the T-shirt and incinerating it (with energy re-</p><p>covery) at the end of its lifetime (corresponds to reuse strategy from Fig. 1).</p><p>3. Scenario 3 (S3): Renting the T-shirt yearly to a new player by removing</p><p>old prints and reprinting (corresponds to remanufacture strategy from Fig. 1).</p><p>4. Scenario 4 (S4): Manufacturing the T-shirt from recycled polyester mate-</p><p>rial (corresponds to repurpose strategy from Fig. 1).</p><p>5. Scenario 5 (S5): Recycling the T-shirt into newpolyesterfiber at the end of</p><p>its lifetime (corresponds to recycling strategy from Fig. 1).</p><p>6. Scenario 6 (S6): Increasing efficiency in product use by reducing washes</p><p>and avoiding tumble drying (corresponds to reduce strategy from Fig. 1).</p><p>7. Scenario 7 (S7): Combining CE approaches from scenarios S2, S4, S5,</p><p>and S6.</p><p>S1 represents a linear system inwhich the T-shirt is produced from virgin</p><p>raw materials, used for a specified amount of time, and incinerated at the</p><p>end of the life cycle (with energy recovery). S2-S7 represent the selected cir-</p><p>cular economy strategies. S2 allows for a second user of the T-shirt, after the</p><p>first user has discarded it after the default value of 200 uses, providing a total</p><p>of 400 uses. Even though technically the material would endure it, this sce-</p><p>nario is currently not frequently used in practice due to, for example, size is-</p><p>sues (particularly with children) or lack of interest. S3 also represents the</p><p>reuse of the T-shirt (total of 400 uses) but considers it to be provided as a ser-</p><p>vice, meaning that it will be collected and offered for reuse by a service pro-</p><p>vider,</p><p>adding some transports and a reprinting process. S4 considers the T-</p><p>shirt to be produced from recycled PET bottles, thus reducing the virgin</p><p>raw material need. S5 assumes that the T-shirt is recycled as polyester</p><p>material after its life cycle has ended after 200 uses, thus substituting virgin</p><p>polyesterfiber. In S6, the T-shirt iswashed less frequently (50%of use times,</p><p>instead of 75 %) in the use phase and not tumble dried (total of 200 uses).</p><p>Finally, S7 is a combination of all previously mentioned scenarios.</p><p>Primary LCI data was sourced from the brand owner of a specific Finn-</p><p>ish sports T-shirt, which has recently started collecting detailed information</p><p>about its own operations, as well as data from its direct suppliers abroad.</p><p>Certain data sets (such as chemicals use) could not be obtained, and there</p><p>was limited visibility beyond the direct suppliers. Hence only secondary</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>data or default values could be used for many processes or flows. Similar</p><p>data inadequacies relate to downstream processes, meaning use and end-</p><p>of-life processes. Primary use-phase data is difficult to obtain, and design</p><p>figures, such as the quality of fabrics, are often biased and do not reflect</p><p>the actual life cycle lengths. As for end-of-life processes, the recycling pro-</p><p>cesses are still maturing and business-sensitive, which means that process</p><p>data is not openly available, and even if they were, scaling-up assumptions</p><p>would need to be made.</p><p>As for additional assumptions, the T-shirt is produced in S1, S2, S3, S5</p><p>and S6 in a conventional process in China, utilizing local coal power. In</p><p>S4 and S7, the T-shirt is produced in China from recycled polyester from</p><p>PET bottles. Both virgin and recycled polyester are assumed to be of the</p><p>same quality. All life cycle phases following the shirt manufacturing occur</p><p>in Finland. The overall maximum technical lifetime of a polyester sports</p><p>T-shirt is 400 uses. The number of uses by one person is assumed to be</p><p>200 on average. In S1-S5, the ratio of shirt washing per use is 0.75 and it</p><p>is tumble dried in 34 % of cases. In S6 and S7, the shirt is washed after</p><p>every second use and only air dried. Electricity and heat recovered from</p><p>the incineration process substitute Finnish local average production. Due</p><p>to homogenous waste material (only polyester), the collection and sorting</p><p>stages of the recycling process are not required. Fiber produced through</p><p>recycling substitutes for polyester fiber made from virgin materials with a</p><p>replacement ratio of 1:2. The impact of substitution is calculated according</p><p>to PEFCR guidance (Pesnel and Payet, 2019). The life cycle inventory (LCI)</p><p>data and sources are detailed in Appendix A.</p><p>4. Results</p><p>4.1. Life cycle impact assessment</p><p>4.1.1. Baseline scenario (S1)</p><p>The LCA results provide information about the most relevant environ-</p><p>mental impacts of polyester T-shirts, as well as about the benefits provided</p><p>Fig. 3. Characterized LCA results for scenario S1 with</p><p>6</p><p>by different circular economy approaches. Fig. 3 presents the LCA results of</p><p>the baseline scenario (S1).</p><p>The most significant contributor in all impact categories is the use</p><p>phase, which causes 46% (respiratory inorganics) to 74 % (resource deple-</p><p>tion, energy carriers) of the various net life cycle impacts. This ismainly due</p><p>to the resource-intensive washing and drying processes during the use</p><p>phase and the high number of uses. The production of fabric causes slightly</p><p>less impacts, being the second most significant contributor with a share be-</p><p>tween 15 % (eutrophication, marine) and 30 % (water scarcity) of net im-</p><p>pacts. Due to incineration of the T-shirts at the end of life, some emissions</p><p>can be avoided through substituting other energy sources, even though</p><p>these avoided impacts generate only marginal benefits (net impact reduc-</p><p>tion between 1 and 3 %). Transports also represent only a small fraction</p><p>across all impacts categories (net impact reduction between 0.1 and 3 %).</p><p>By taking a closer look at the individual impact categories, it is evident</p><p>that in the impact categories of eutrophication and resource depletion, use</p><p>is by far the most dominant life cycle phase. In the category of respiratory</p><p>inorganics, the fabric production and T-shirt manufacturing (particularly</p><p>confectioning) phases dominate. In this study, fabric production and</p><p>confectioning were considered as separate life cycle phases, primarily due</p><p>to data quality differences between these phases and due to different geo-</p><p>graphical locations. In total, fabric production and confectioning jointly</p><p>cause 49 % of all respiratory inorganic impacts. In addition, in the catego-</p><p>ries of acidification and climate change impacts, a relatively high share of</p><p>the impacts is caused by fabric manufacturing and confectioning (39 % of</p><p>acidification impacts and 36 % of climate change impacts).</p><p>More detailed LCA results for the other individual scenarios (S2-S7), in-</p><p>cluding contribution analysis across the chosen environmental impact cate-</p><p>gories, are listed in Appendix B.</p><p>4.1.2. Comparison of scenarios</p><p>Normalized results for each impact category and scenario are visualized</p><p>in Fig. 4. S7 clearly performs best out of all scenarios across all impact</p><p>EF 2.0 method. Contribution of life cycle stages.</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>categories,which is logical considering the fact that all benefits provided by</p><p>individual scenarios are cumulative. By combining all CE strategies, the im-</p><p>pacts are reduced substantially across all impact categories, between</p><p>−52 % (eutrophication, marine) and − 77 % (resource depletion).</p><p>By taking a look at the individual scenarios, S6 (reduce) emerged as the</p><p>single most beneficial option. The scenario considers that the use phase of</p><p>the garment is made more efficient, as it will be washed less often and</p><p>not tumble dried. The reduction inwashing and dryingwill substantially re-</p><p>duce the impacts, in particular on climate change and resource depletion,</p><p>due to less energy use of the equipment. The recycling-related scenarios</p><p>(S4 and S5) reduce the impacts less, on average by−5 % to−10 % across</p><p>the different impact categories. Recycling processes consume energy, and</p><p>the recycling of fabrics requires virgin materials to be added, which dimin-</p><p>ishes the achieved benefits. The scenarios increasing the number of uses (S2</p><p>and S3) can reduce the total environmental impacts between −13 %</p><p>and − 27 %, but as the number of uses increase, so does the amount of</p><p>washing and drying, which also lowers the benefits.</p><p>Within the selected, most relevant impact categories, the order of prior-</p><p>ity between the scenarios remains similar. S1 causes the most environmen-</p><p>tal impacts in all categories. S4 is better than S1, closely followed by S5,</p><p>except in respiratory inorganics, where S5 is better than S4. S2 and S3 are</p><p>very close to each other, with S2 being slightly better in all impact catego-</p><p>ries. Finally, S6 is in all other impact categories the best individual option,</p><p>apart from respiratory inorganics, where it is slightly worse than S2 and S3.</p><p>S7, which is the combination of all, is clearly the best option across all im-</p><p>pact categories.</p><p>The weighted analysis results are presented in Fig. 5. The weighting di-</p><p>minishes the transparency behind the individual impact categories but con-</p><p>denses the information across impact categories and across the different</p><p>scenarios into a more simplified format. This condensed result presentation</p><p>Fig. 4.Normalized LCA results by impact category and scenario with EF 2.0 method and</p><p>between S1 (baseline) and S7.</p><p>7</p><p>will allow for a clearer view of the absolute order of priority between the</p><p>scenarios, with the percentage-based improvement potentials. Commonly,</p><p>if there are tradeoffs between impact categories, this approach would be</p><p>able to determine the overall best and worse options. In our case, there</p><p>are only a few such tradeoffs, so the order of priority remains very similar</p><p>to the individual impact</p><p>categories presented above. S5 and S4 are able to</p><p>reduce overall environmental impacts by 8% and 9%, respectively, in com-</p><p>parison to the baseline. Both S3 and S2 can reduce the impacts by 18%. The</p><p>most reduction from the individual CE strategies can be gained by S6,</p><p>reaching a 37 % reduction merely by washing and drying less. A combina-</p><p>tion of the different CE strategies (S7) decreases the weighted impact of S1</p><p>by 70 %.</p><p>4.1.3. Data uncertainty</p><p>The baseline scenario (S1) is the currently prevalent scenario and, in</p><p>terms of data availability, the only scenario for which primary data is avail-</p><p>able. This scenario, as well the other scenarios, contains considerable data</p><p>gaps and related uncertainties, especially related to the production of</p><p>fiber and fabric, the use phase, end-of-life processes, and chemicals used</p><p>throughout the life cycle. The sourced data was of different quality and</p><p>contained considerable uncertainties, stemming from the lack of data,</p><p>lack of representative data, or data inaccuracies (Huijbregts et al., 2001).</p><p>In some cases, the data also contained natural variability that cannot</p><p>be omitted. These data issues are taken into account using Monte Carlo</p><p>analysis.</p><p>Based on theMonte Carlo analysis, almost all of the result uncertainty is</p><p>caused by the use phase data uncertainty, covering both the number of</p><p>T-shirt uses and the washing frequency. Fluctuation of these factors be-</p><p>tween different scenarios may cause differences in the scenario order</p><p>from the least to the most impactful. Less frequent washing, and hence a</p><p>normalization factors from PEFCR. Percentages are the maximum impact decreases</p><p>Fig. 5.Weighted LCA results by scenario with EF 2.0 method and weighting factors from PEFCR. Percentages describe the total weighted impact decreases compared to S1</p><p>(baseline).</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>lower contribution to the total impact by the use phase of the T-shirt, causes</p><p>lower result uncertainty in scenarios S6 and S7, and even with uncertainty</p><p>considered, S7 remains the best performing scenario.</p><p>The 90%confidence intervals and the resultmean values for theweighted</p><p>scenario results from the Monte Carlo analysis are presented in Fig. 6.</p><p>4.2. Risks to the environment and human health</p><p>4.2.1. Potential critical contaminants and consequent risks</p><p>The environmental and health risks are highly dependent on case-</p><p>specific factors related to contaminants, surrounding environment and</p><p>Fig. 6. Results of Monte Carlo analysis presenting 90 % confiden</p><p>8</p><p>potential recipients. Such detailed, primary data were not available in our</p><p>case, hence the results merely imply the possible threats arising from the</p><p>toxicity of the potential and most critical substances (identified on the</p><p>basis of a literature survey) that may emerge during the T-shirts life cycle</p><p>phases (Table 1). A compilation of the toxicity reference values of these crit-</p><p>ical substances is presented in Table C.1 in Appendix C. It is worth noting</p><p>that toxicity data was not available for all the identified key contaminants.</p><p>The environmental risks caused by crude oil extraction, refining, and</p><p>related transports are mainly caused by spills and accidents that result</p><p>in the contamination of terrestrial and aquatic ecosystems. The adverse ef-</p><p>fects of oil contamination on marine biota are well known and multifold</p><p>ce intervals and mean values for weighted scenario 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><p>ua</p><p>ti</p><p>c</p><p>an</p><p>d</p><p>te</p><p>rr</p><p>es</p><p>tr</p><p>ia</p><p>lb</p><p>io</p><p>ta</p><p>an</p><p>d</p><p>st</p><p>ar</p><p>va</p><p>ti</p><p>on</p><p>)</p><p>A</p><p>va</p><p>gy</p><p>an</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>15</p><p>,K</p><p>är</p><p>kk</p><p>äi</p><p>ne</p><p>n</p><p>an</p><p>d</p><p>Si</p><p>lla</p><p>np</p><p>ää</p><p>,2</p><p>02</p><p>1,</p><p>Si</p><p>lla</p><p>np</p><p>ää</p><p>an</p><p>d</p><p>Sa</p><p>in</p><p>io</p><p>,</p><p>20</p><p>17</p><p>,B</p><p>ro</p><p>ad</p><p>he</p><p>ad</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>21</p><p>,M</p><p>or</p><p>ai</p><p>s</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>16</p><p>,L</p><p>im</p><p>,2</p><p>02</p><p>1,</p><p>Ta</p><p>na</p><p>ka</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>20</p><p>,P</p><p>al</p><p>ac</p><p>io</p><p>s-</p><p>M</p><p>at</p><p>eo</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>21</p><p>C</p><p>on</p><p>ta</p><p>m</p><p>in</p><p>an</p><p>ts</p><p>:T</p><p>PA</p><p>,e</p><p>th</p><p>yl</p><p>en</p><p>e</p><p>gl</p><p>yg</p><p>ol</p><p>,n</p><p>an</p><p>op</p><p>ar</p><p>ti</p><p>cl</p><p>es</p><p>,a</p><p>nt</p><p>im</p><p>on</p><p>y,</p><p>az</p><p>od</p><p>ye</p><p>s,</p><p>qu</p><p>in</p><p>ol</p><p>in</p><p>e,</p><p>ac</p><p>ri</p><p>di</p><p>ne</p><p>,B</p><p>PA</p><p>G</p><p>en</p><p>er</p><p>al</p><p>pu</p><p>bl</p><p>ic</p><p>(i</p><p>nc</p><p>l.</p><p>co</p><p>ns</p><p>um</p><p>er</p><p>s)</p><p>:d</p><p>er</p><p>m</p><p>al</p><p>ex</p><p>po</p><p>su</p><p>re</p><p>an</p><p>d</p><p>in</p><p>ha</p><p>la</p><p>ti</p><p>on</p><p>(n</p><p>an</p><p>op</p><p>ar</p><p>ti</p><p>cl</p><p>es</p><p>),</p><p>in</p><p>ge</p><p>st</p><p>io</p><p>n</p><p>vi</p><p>a</p><p>dr</p><p>in</p><p>ki</p><p>ng</p><p>w</p><p>at</p><p>er</p><p>an</p><p>d</p><p>fo</p><p>od</p><p>(e</p><p>.g</p><p>.m</p><p>ic</p><p>ro</p><p>pl</p><p>as</p><p>ti</p><p>cs</p><p>)</p><p>(v</p><p>ar</p><p>yi</p><p>ng</p><p>to</p><p>xi</p><p>c</p><p>re</p><p>sp</p><p>on</p><p>se</p><p>s,</p><p>e.</p><p>g.</p><p>ca</p><p>nc</p><p>er</p><p>,d</p><p>is</p><p>ru</p><p>pt</p><p>io</p><p>n</p><p>of</p><p>ho</p><p>rm</p><p>on</p><p>al</p><p>sy</p><p>st</p><p>em</p><p>,</p><p>m</p><p>ut</p><p>at</p><p>io</p><p>ns</p><p>,l</p><p>un</p><p>g</p><p>in</p><p>fl</p><p>am</p><p>m</p><p>at</p><p>io</p><p>n,</p><p>he</p><p>ar</p><p>tp</p><p>ro</p><p>bl</p><p>em</p><p>s)</p><p>Si</p><p>ng</p><p>h</p><p>an</p><p>d</p><p>Bh</p><p>al</p><p>la</p><p>,2</p><p>01</p><p>7,</p><p>Bi</p><p>ve</p><p>r</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>21</p><p>,C</p><p>ar</p><p>ls</p><p>so</p><p>n</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>22</p><p>,L</p><p>uo</p><p>ng</p><p>o</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>16</p><p>,R</p><p>ov</p><p>ir</p><p>a</p><p>an</p><p>d</p><p>D</p><p>om</p><p>in</p><p>go</p><p>,</p><p>20</p><p>19</p><p>,L</p><p>iu</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>17</p><p>,F</p><p>re</p><p>ir</p><p>e</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>19</p><p>,P</p><p>rü</p><p>st</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>20</p><p>a,</p><p>20</p><p>20</p><p>b,</p><p>Za</p><p>ru</p><p>s</p><p>et</p><p>al</p><p>.,</p><p>20</p><p>21</p><p>a,</p><p>20</p><p>21</p><p>b</p><p>In</p><p>ci</p><p>ne</p><p>ra</p><p>ti</p><p>on</p><p>N</p><p>R</p><p>N</p><p>R</p><p>A</p><p>A</p><p>=</p><p>ar</p><p>om</p><p>at</p><p>ic</p><p>am</p><p>in</p><p>es</p><p>;A</p><p>M</p><p>R</p><p>=</p><p>A</p><p>nt</p><p>im</p><p>ic</p><p>ro</p><p>bi</p><p>al</p><p>R</p><p>es</p><p>is</p><p>ta</p><p>nc</p><p>e;</p><p>BP</p><p>A</p><p>=</p><p>Bi</p><p>sp</p><p>he</p><p>no</p><p>lA</p><p>;B</p><p>TE</p><p>X</p><p>=</p><p>be</p><p>nz</p><p>en</p><p>e,</p><p>to</p><p>lu</p><p>en</p><p>e,</p><p>et</p><p>hy</p><p>lb</p><p>en</p><p>ze</p><p>ne</p><p>,x</p><p>yl</p><p>en</p><p>e</p><p>D</p><p>EH</p><p>P</p><p>=</p><p>Bi</p><p>s(</p><p>2-</p><p>et</p><p>hy</p><p>lh</p><p>ex</p><p>yl</p><p>)p</p><p>ht</p><p>ha</p><p>la</p><p>te</p><p>;D</p><p>M</p><p>A</p><p>=</p><p>D</p><p>im</p><p>et</p><p>hy</p><p>lte</p><p>re</p><p>ph</p><p>th</p><p>al</p><p>at</p><p>e;</p><p>N</p><p>P</p><p>=</p><p>no</p><p>ny</p><p>lp</p><p>he</p><p>no</p><p>ls</p><p>;N</p><p>PE</p><p>O</p><p>=</p><p>no</p><p>ny</p><p>lp</p><p>he</p><p>no</p><p>le</p><p>th</p><p>ox</p><p>yl</p><p>at</p><p>e;</p><p>PM</p><p>=</p><p>pa</p><p>rt</p><p>ic</p><p>le</p><p>m</p><p>at</p><p>te</p><p>r;</p><p>TP</p><p>A</p><p>=</p><p>Te</p><p>re</p><p>ph</p><p>th</p><p>al</p><p>ic</p><p>A</p><p>ci</p><p>d;</p><p>V</p><p>O</p><p>C</p><p>=</p><p>vo</p><p>la</p><p>til</p><p>e</p><p>or</p><p>ga</p><p>ni</p><p>c</p><p>ca</p><p>rb</p><p>on</p><p>.</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>9</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>(e.g. Saadoun 2014). Besides the direct toxic effects, drilling causes habitat</p><p>loss and disturbance arising from noise (e.g. Rosa and Koper, 2022).</p><p>Johnston et al. (2019) concluded in their review, that upstream oil</p><p>extraction also leads to human health effects through exposure to toxic</p><p>substances.</p><p>In manufacturing, workers can be exposed to various contaminants, e.g.</p><p>chemicals and synthetic fiber dust (Gallagher et al., 2015; Wernli et al.,</p><p>2006a, 2006b). Manufacturing also creates emissions that can be detrimen-</p><p>tal to the environment if not properly managed. The impact of emissions in</p><p>wastewater discharge varies with location and used processes. However,</p><p>several studies confirm the high aquatic toxicity of wastewater generated</p><p>in the Chinese textile industry (e.g. Wang et al., 2021; Ayed et al., 2021)</p><p>and, according to Chen et al. (2020), discharges into water bodies also</p><p>pose a serious risk to human health and aquatic ecosystems. Yuan et al.</p><p>(2020) found high levels of chlorobenzenes (CB) in the influents and efflu-</p><p>ents from typical Chinese plants that treat textile wastewaters. The risks to</p><p>the aquatic biota in the receiving water body were judged as moderate. Ho</p><p>andWatanabe (2017) report the use of highly toxic nonylphenol ethoxylate</p><p>(NPEO) surfactants in the finishing stage of garments, particularly in Asia.</p><p>In Vietnam, the high levels of nonylphenol (NP), a toxic metabolite of</p><p>NPEO and also an endocrine disruptor in the effluents of garment factories,</p><p>has led to NP concentrations in water bodies that exceed the corresponding</p><p>EU's regulatory limit value (Hanh et al., 2012, ref. in Ho and Watanabe,</p><p>2017).</p><p>Textile production also emitsmicroparticles such asmicroplastics (Zhou</p><p>et al., 2020) that end up in the aquatic environment as current wastewater</p><p>treatment processes are unable to fully remove them. High levels of</p><p>microplastics were found in China in the surface waters receiving effluents</p><p>from the textile industry (Deng et al., 2020). While China currently has na-</p><p>tional standards for wastewater discharge from the textile industry (Chen</p><p>et al., 2021), these are not exhaustive and fail to cover many of the critical</p><p>chemicals. Also, the concentration of antimony in the effluents of some tex-</p><p>tile manufacturing plants were reported to exceed the national regulatory</p><p>limit value (Li et al., 2021).</p><p>When polyester is manufactured from recycled PET bottles, these can</p><p>bring along some contaminants, such as bisphenol A (BPA) (Wang et al.,</p><p>2020; Fan et al., 2014) and antimony (Fan et al., 2014). However, Filella</p><p>(2020) concludes that the levels in PET bottles are usually below the regu-</p><p>latory standards. The release of antimony and BPA from PET bottles in-</p><p>creases with increasing temperature (Fan et al., 2014), and hence the</p><p>emissions might be relevant in the manufacturing stage.</p><p>Several studies have reported significant concentrations of chemicals</p><p>used in the manufacture, such as aromatic amines from azo dyes</p><p>(e.g., Luongo et al., 2016; Liu et al., 2017, Brüschweiler and Merlot,</p><p>2017), BPA (e.g. Freire et al., 2019; Xue et al., 2017), antimony (Biver</p><p>et al., 2021), anti-microbial biocides (e.g. triclosan), and nanoparticles</p><p>(Gulati et al., 2022), in the garments. From the garments, the contaminants</p><p>can end up in the human body by dermal uptake, inhalation, or ingestion.</p><p>Iadaresta et al. (2018) reported significant release of and consequent</p><p>potential dermal exposure to benzothiazole (used e.g. in some dyes).</p><p>Rovira et al. (2015) assessed that the dermal exposure to antimony from</p><p>the studied garments exceeded the acceptable level for non-carcinogenic</p><p>health effects. Biver et al. (2021) showed that only 2% of the polyester gar-</p><p>ments' total antimony,</p><p>at maximum, is released into sweat.</p><p>In the use phase, the manufacturing chemicals can cause more serious</p><p>manifestations besides allergic skin reactions (see Table 1), due to sweating</p><p>and mechanical stress (particles and fibers). Mouthing behavior can be an</p><p>important exposure mechanism for young children. In addition, washing</p><p>has been found to be a major source of microplastics ending up in the envi-</p><p>ronment (e.g. Hernandez et al., 2017; Kärkkäinen and Sillanpää, 2021; De</p><p>Falco et al., 2019). Microplastics are also known to act as transporters of</p><p>hazardous chemicals (e.g. Ogata et al., 2009) and growth media for antibi-</p><p>otic resistant microbes present in the surrounding medium (e.g. Sathicq</p><p>et al., 2021). In addition, domestic driers act as a source of airborne</p><p>microplastics from synthetic textiles (O'Brien et al., 2020). Washing also re-</p><p>leases chemicals used in themanufacture of garments (Luongo et al., 2016).</p><p>10</p><p>According to the study by Tian et al. (2020), heavy metals comprise the</p><p>group of chemicals that pose the highest potential health and ecological</p><p>hazards in textile industry waste waters. Cadmium, chromium (VI)</p><p>and mercury pose particularly occupational risks. The calculated CTUhs</p><p>and CTUFs of organic chemicals such as azo dyes, chlorinated benzenes</p><p>and phthalates were orders of magnitude lower. The characteristics of</p><p>USEtox model (focus on long term effects) and measurement practices</p><p>were explained to cause some bias regarding the assessment of organic</p><p>chemicals.</p><p>4.2.2. Risks caused by contaminants in different circularity scenarios</p><p>Even though it is not possible to determine the actual health and envi-</p><p>ronmental risks arising during the studied T-shirts life cycle on a truly</p><p>quantitative basis, their structured evaluation covering each life cycle</p><p>phase enables to determine how the CE strategies can mitigate the risks.</p><p>Such an evaluation (Table 2) shows that the CE strategies S2-S5 are efficient</p><p>in reducing the health and environmental risks arising from the raw mate-</p><p>rial extraction. In fact, substituting oil with recycled materials (S4 and S5)</p><p>enables the elimination of these risks. The scenarios that extend the life</p><p>cycle (S2 and S3) are expected to reduce overall production and due to</p><p>this, reduce related environmental and health risks. Since the major envi-</p><p>ronmental risks arise from the discharge of the production phase waste wa-</p><p>ters to waterbodies, these scenarios result in the highest reduction of risks</p><p>to biota. Emissions to soil are expected to be low during the whole life</p><p>cycle even in the baseline case (S1), and therefore, different CE strategies</p><p>have a negligible effect on their reduction. The scenarios that utilize</p><p>recycling (S4, S5) reduce the raw materials related emissions and conse-</p><p>quently, the environmental risks. Reducedwashing (S6) in the use phase ef-</p><p>ficiently reduces the release of microplastics and chemicals to wastewater</p><p>and hence, environmental risks. However, the health risks arising from an</p><p>old T-shirt increase for the same reason, i.e., prolonged attachment of</p><p>chemicals leading to increased dermal exposure. The risks related to the</p><p>end-of-life stage would not be affected by any of the strategies due to the</p><p>fact that, in Finland, where the textile waste treatment would occur, both</p><p>occupational risks and emissions to the environment aremanaged to the ex-</p><p>tent that no significant risks are posed to the environment or human health,</p><p>as per the regulations. It is evident that a combination of various CE strate-</p><p>gies (S7) results in the highest reduction of health and environmental risks</p><p>compared to the baseline case.</p><p>5. Discussion</p><p>While the implementation of CE strategies and the introduction of polit-</p><p>ical and financial steering mechanisms to support CE are becoming stan-</p><p>dard practice, it is becoming increasingly important to develop analytical</p><p>capabilities to prioritize different CE actions (Potting et al., 2017) and to be-</p><p>come aware of their potential to reduce environmental impacts (Ghisellini</p><p>et al., 2016; Stahel, 2017). Munasinghe et al. (2021) concluded that even</p><p>though the best way to reduce the textile sector's adverse impacts is to re-</p><p>duce consumption, production cannot be reduced to zero, and instead,</p><p>pro-environmental decision-making by stakeholders in the fashion indus-</p><p>try, such as designers and consumers, should be supported. Data issues</p><p>for novel products, processes, or business models play a crucial role, as</p><p>there is seldom reliable and transparent data available (Zhang et al.,</p><p>2020b; Galatola and Pant, 2014). These data gaps often relate to the use</p><p>phase of garments (van der Velden et al., 2014).</p><p>In this study, we calculated the different environmental impacts of a</p><p>polyester T-shirts life cycle and assessed the magnitude of benefits to be</p><p>achieved by adopting various CE strategies. The environmental consider-</p><p>ations have often been restricted to climate impact or energy consumption</p><p>(Munasinghe et al., 2021), which is why it was considered beneficial to</p><p>cover a wider spectrum of environmental categories, with a specific focus</p><p>on the impacts defined as most relevant according to the PEF guidance</p><p>for T-shirts (Pesnel and Payet, 2019). Uncertainty of the LCA results was</p><p>also studied, due to the above-mentioned primary data gaps and data qual-</p><p>ity issues. 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Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>11</p><p>S. Horn et al. Science of the Total Environment 884 (2023) 163821</p><p>environmental risks related to the different life cycle options. However,</p><p>only secondary literature data was available for assessing risks and thus a</p><p>semi-quantitative scoring approach could be utilized. The scale used in</p><p>the scoring of risks enables only the ranking of the different CE scenarios</p><p>from the viewpoint of their contribution to risk reduction but not the deter-</p><p>mination of the factual reduction percentage.</p><p>5.1.1. Most LCA-based impacts from the use phase</p><p>Due to data availability, most robust conclusions can be drawn from the</p><p>LCA results. The most significant LCA-based environmental impacts from a</p><p>T-shirts full life cycle in the linear baseline case include the climate change</p><p>impacts (0.03 kg CO2e/ use) and resource depletion of energy carriers</p><p>(0.55 MJ/ use), with the use phase causing the major share of the</p><p>impacts. Compared to the results concerning a cotton T-shirt studied by</p><p>Sandin et al. (2019), our results indicate 67 % lower climate impacts and</p><p>70 % lower energy use, mainly due to the choice of rawmaterial and a sub-</p><p>stantially higher number of uses of the garment in our study. Consequently,</p><p>the results of Sandin et al. showed that the production stages were respon-</p><p>sible for nearly 80 % of the climate impacts and for 70 % of energy con-</p><p>sumption, whereas our results clearly indicated the dominance of the use</p><p>phase. In addition, the study byWu (2020) on a polyester T-shirt concluded</p><p>that the use phase caused the majority of impacts, even though the assump-</p><p>tions were based on 52 washes in comparison to our 150 washes (when</p><p>used 200 times). The fact that it is, indeed, very difficult to obtain direct</p><p>data regarding the use phase partially explains these differences, in addi-</p><p>tion to the differing number of uses between different types of garments.</p><p>5.1.2. Different CE strategies offer unequal benefits</p><p>By introducing various CE strategies, which alter the life cycle in differ-</p><p>ent ways, all environmental impacts (quantified in the LCA), as well as en-</p><p>vironmental and health risks arising from chemicals and other harmful</p><p>elements, can be reduced. However, the potential of different CE strategies</p><p>to reduce the environmental impacts varies significantly, which is a finding</p><p>in line with Potting et al. (2017) statement that certain CE actions can be</p><p>prioritized over others. Alternative CE strategies also have a different po-</p><p>tential to reduce the health and environmental risks. In the case of a partic-</p><p>ular product, as in this study, the order of priority is not straightforward</p><p>(Roos Lindgreen et al., 2021). The aim of this study was not to contest</p><p>Potting et al. (2017) results as such, but rather to make a data-based,</p><p>product-specific assessment of selected CE strategies and to study the im-</p><p>portance and uncertainties behind the assumptions made in the LCA.</p><p>The recycling (S5) and repurpose (S4) scenarios, meaning using</p><p>recycled PET bottles as raw material or recycling the garment as material</p><p>at the end of its life cycle, emerged as the least beneficial CE strategies</p>