From Target-Nontarget to Nontarget Screening: A Review on Screening Methods for Organic Pollutants Based on
Runmin Yuan1,2, Hongrui Zhang1,2, Jiyan Liu1,2,3
1State Key Laboratory of Environmental Chemistry and Toxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China.
Nontarget screening (NTS) is crucial for environmental analysis. This review proposes a new workflow using high-resolution mass spectrometry (HRMS) characteristics for comprehensive and reliable environmental contaminant detection.
Area of Science:
- Environmental Chemistry
- Analytical Chemistry
Background:
- Trace environmental substances pose significant ecological risks.
- High-resolution mass spectrometry (HRMS) has advanced nontarget screening (NTS) capabilities.
- NTS is vital for identifying unknown environmental contaminants.
Purpose of the Study:
- To review principles and methodologies of mass spectrometry (MS) characteristics for NTS.
- To propose an integrated target-nontarget to nontarget screening workflow.
- To highlight advancements in MS characteristics and machine learning for NTS.
Main Methods:
- Review of existing MS characteristics (mass defect, isotope patterns, fragments).
- Proposal of a novel workflow linking different MS characteristics.
- Overview of machine learning for MS characteristics mining and prediction.
Main Results:
- A prioritized workflow for comprehensive NTS is presented.
- Integration of various analytical steps expands screening coverage and reliability.
- Machine learning aids in mining and predicting MS characteristics.
Conclusions:
- The proposed workflow enhances NTS by linking diverse MS characteristics.
- Machine learning offers powerful tools for NTS data analysis.
- Future perspectives address challenges in transitioning to advanced NTS workflows.
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