TY  - JOUR
AU  - Tang, Kuok Ho Daniel
PY  - 2025
DA  - 2025/11/19
TI  - The Role of Artificial Intelligence in Microplastic Pollution Studies and Management
JO  - Recent Progress in Science and Engineering
SP  - 016
VL  - 01
IS  - 04
AB  - Artificial intelligence (AI) is reshaping microplastic research by enabling faster, more accurate, and scalable detection, characterization, and modeling. Deep learning automates the identification and classification of microplastics from microscopy images, while machine learning accelerates the recognition of polymers from Raman and infrared spectra. AI-based clustering and segmentation improve the analysis of complex samples, and source-apportionment models learn morphological and chemical features to trace emissions from various activities and land uses. AI also enhances predictions of microplastic interactions and impacts, modeling pollutant adsorption, leaching behaviors, and biological toxicity responses. Large language models are increasingly used to streamline quality assurance/control (QA/QC) and support exposure and risk assessments. Emerging AI-enabled sensors and real-time control systems can be integrated into manufacturing and wastewater treatment processes, enabling continuous monitoring and adaptive process adjustments to reduce microplastic release. Collectively, AI provides powerful tools for advancing microplastic detection, understanding their ecological and health risks, and supporting proactive pollution mitigation.
SN  - 3067-4573
UR  - https://doi.org/10.21926/rpse.2504016
DO  - 10.21926/rpse.2504016
ID  - Tang2025
ER  -