What is it about?
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
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Why is it important?
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
Perspectives
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
Professor Mohammad Mansoob Khan
Universiti Brunei Darussalam
Microplastics are now recognized as pervasive contaminants across environmental and biological systems, yet their accurate detection particularly at the micro- to nanoscale remains a major analytical challenge. This study highlights that while techniques such as microscopy, FTIR, Raman spectroscopy, hyperspectral imaging, and mass spectrometry have significantly advanced our ability to identify and quantify microplastics, each method carries inherent limitations in sensitivity, selectivity, and real-world applicability. A key insight from this work is the growing importance of integrating artificial intelligence with conventional analytical tools to enhance detection accuracy, reduce human bias, and enable high-throughput analysis. Moving forward, the field must prioritize the development of standardized protocols, validated multi-technique workflows, and portable detection systems capable of real-time monitoring. Strengthening these analytical capabilities is essential not only for improving scientific understanding but also for enabling effective risk assessment and evidence-based environmental policymaking.
Mohd Fazal Ur Rehman
Read the Original
This page is a summary of: From Microplastics to Nanoplastics: Critical Advances and Persistent Challenges in Detection and Quantification, Critical Reviews in Analytical Chemistry, April 2026, Taylor & Francis,
DOI: 10.1080/10408347.2026.2658239.
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Resources
From Microplastics to Nanoplastics: Critical Advances and Persistent Challenges in Detection and Quantification
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
From Microplastics to Nanoplastics: Critical Advances and Persistent Challenges in Detection and Quantification
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
From Microplastics to Nanoplastics: Critical Advances and Persistent Challenges in Detection and Quantification
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
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