Discovery of emerging organic pollutants in the atmosphere through an omics approach

Highlights

● We review the framework of discovering emerging pollutants through an omics approach.

● High-resolution MS can digitalize atmospheric samples to full-component data.

● Chemical features and databases can help to translate untargeted data to compounds.

● Biological effect-directed untargeted analyses consider both existence and toxicity.

Abstract

Ambient air pollution, containing numerous known and hitherto unknown compounds, is a major risk factor for public health. The discovery of harmful components is the prerequisite for pollution control; however, this raises a great challenge on recognizing previously unknown species. Here we systematically review the analytical techniques on air pollution in the framework of an omics approach, with a brief introduction on sample preparation and analysis, and in more detail, compounds prioritization and identification. Through high-resolution mass spectrometry (HRMS, typically coupled with chromatography), the complicated environmental matrix can be digitalized into “full-component” data. A key step to discover emerging compounds is the prioritization of compounds from massive data. Chemical fingerprints, suspect lists and biological effects are the most vital untargeted strategies for comprehensively screening critical and hazardous substances. Afterward, compressed data of compounds can be identified at various confidence levels according to exact mass and the derived molecular formula, MS libraries, and authentic standards. Such an omics approach on full-component data provides a paradigm for discovering emerging air pollutants; nonetheless, new technological advancements of instruments and databases are warranted for further tracking the environmental behaviors, hence to evaluate the health risk of key pollutants.

Graphical abstract

Keywords

Air pollution / Emerging pollutants / Full-component / High-resolution mass spectrometry / Omics approach

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (Nos. 41961134034 and 21876002), the 111 Project of Urban Air Pollution and Health Effects (China) (B20009), and the International Joint Laboratory for Regional Pollution Control, Ministry of Education (China). The authors acknowledge the technical support from Agilent Technologies.

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