Abstract
AbstractFine 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.
Funder
Svenska Forskningsrådet Formas
Vetenskapsrådet
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
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