Prioritization strategies aim to highlight contaminants of highest concern among hundreds or thousands of features detected with high-resolution mass spectrometry in environmental samples. Online prioritization techniques allow real-time analysis of low-energy mass spectrum to trigger molecular dissociation of isolated precursors, thereby overcoming challenges with discrete duty cycle times. Offline prioritization techniques, in contrast, do not require a priori knowledge for the chemicals of interest. Alternatively, information from the sample analysis can be used to highlight features based on their relative profile, or the predicted structure, toxicity and concentration. These techniques were applied to the analysis of emerging contaminants in recycled textiles, containing cotton, elastane, polyester, and polyamide substrates. Suspect and non-targeted analysis was performed on approximately 9000 high-quality features. MS1 peaks were initially matched with a list of chemicals associated with textile production by the Swedish Chemical Agency (KEMI) for further interrogation. Simultaneously, all detected features highlighted by online and offline prioritization strategies were ranked based on their relative intensity and predicted acute aquatic toxicity. Results of textile related substances annotated with respective confidence, including their associated risk of exposure, will be discussed in the presentation.