Papazian, S and DAgostino, LA and Sadiktsis, I and Froment, J and Bonnefille, B and Sdougkou, K and Xie, H and Athanassiadis, I and Budhavant, K and Dasari, S and Andersson, A and Gustafsson, Ã and Martin, JW (2022) Nontarget mass spectrometry and in silico molecular characterization of air pollution from the Indian subcontinent. In: Communications Earth and Environment, 3 (1).
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Abstract
Fine particulate-matter is an important component of air pollution that impacts health and climate, and which delivers anthropogenic contaminants to remote global regions. The complex composition of organic molecules in atmospheric particulates is poorly constrained, but has important implications for understanding pollutant sources, climate-aerosol interactions, and health risks of air pollution exposure. Here, comprehensive nontarget high-resolution mass spectrometry was combined with in silico structural prediction to achieve greater molecular-level insight for fine particulate samples (n = 40) collected at a remote receptor site in the Maldives during January to April 2018. Spectral database matching identified 0.5 of 60,030 molecular features observed, while a conservative computational workflow enabled structural annotation of 17 of organic structures among the remaining molecular dark matter. Compared to clean air from the southern Indian Ocean, molecular structures from highly-polluted regions were dominated by organic nitrogen compounds, many with computed physicochemical properties of high toxicological and climate relevance. We conclude that combining nontarget analysis with computational mass spectrometry can advance molecular-level understanding of the sources and impacts of polluted air. © 2022, The Author(s).
| Item Type: | Journal Article |
|---|---|
| Publication: | Communications Earth and Environment |
| Publisher: | Nature Publishing Group |
| Additional Information: | The copyright for this article belongs to the Authors. |
| Department/Centre: | Division of Mechanical Sciences > Divecha Centre for Climate Change |
| Date Deposited: | 05 Jun 2022 05:57 |
| Last Modified: | 05 Jun 2022 05:57 |
| URI: | https://eprints.iisc.ac.in/id/eprint/73095 |
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