Face mask littering: environmental impacts, regulatory challenges, and AI-driven waste management strategies for the postpandemic era
Turkish Journal of Medical Sciences, cilt.56, sa.4, ss.909-930, 2026 (SCI-Expanded, Scopus, TRDizin)
- Yayın Türü: Makale / Derleme
- Cilt numarası: 56 Sayı: 4
- Basım Tarihi: 2026
- Doi Numarası: 10.55730/1300-0144.6336
- Dergi Adı: Turkish Journal of Medical Sciences
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE, TR DİZİN (ULAKBİM), Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO)
- Sayfa Sayıları: ss.909-930
- Anahtar Kelimeler: COVID-19, environment, face mask, pollution, postpandemic, toxicity
- Gazi Üniversitesi Adresli: Evet
Özet
The widespread use of polypropylene-based face masks during the COVID-19 pandemic created a significant and persistent source of plastic pollution. This review aims to provide an integrative assessment of the environmental, toxicological, and public health implications of face mask litter and evaluate current waste management challenges and emerging technological solutions in the postpandemic context. A narrative review approach was employed, synthesizing literature published between 2020 and 2025 and indexed in major scientific databases including Web of Science, Scopus, and PubMed. Studies were selected based on their relevance to the issues of environmental contamination, microplastic generation, toxicological effects, regulatory frameworks, and artificial intelligence (AI)-based waste management strategies. The findings indicate that discarded face masks are a major source of microplastics and hazardous chemical additives, contributing to environmental contamination across terrestrial, aquatic, and atmospheric systems. These materials may enter human exposure pathways through inhalation, ingestion, and dermal contact, with potential implications for respiratory health, systemic toxicity, and endocrine disruption. In addition, current waste management systems are shown to be insufficient for handling personal protective equipment-related waste, particularly under pandemic conditions. While AI-driven technologies can improve waste detection, sorting, and monitoring efficiency, their real-world scalability remains constrained by data limitations, infrastructure requirements, and environmental trade-offs. Overall, this review emphasizes that face mask pollution constitutes a multidimensional environmental and public health challenge requiring integrated responses. Strengthening regulatory frameworks, advancing sustainable material design, and combining AI-based tools with robust waste management systems are essential for mitigating long-term risks and improving preparedness for future global health crises.