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Ambient particulate matter with a size of less than 2.5 μm (PM2.5) is associated with adverse effects on human health, and its chemical composition is very complicated. High-resolution mass spectrometry (HR-MS)-based non-targeted analysis is applied to analyze the mixtures of organic components of PM2.5 in this work. Soluble chemicals are essential for internal exposure of PM2.5 in humans, but chemical species that induce toxic effects in humans are not fully known. Excluding well-known toxins such as heavy metals and PAHs, this work focuses on detecting emerging soluble organic chemicals of PM2.5. PM2.5 samples were collected daily during two different sampling campaigns, January 15 to 21, 2018, and December 1 to 7, 2018, at Air Pollution Research Center in Seoul, Korea. A portion of each collected PM2.5 sample was extracted with water using sonication, followed by evaporation to bring the volume down to 34 times of concentration. The concentrated samples were then injected into UPLC-QToF-MS using the data-independent MS/MS (DIA) method. MS-Dial was used for in silico prediction of structural annotation and identification of the chemicals. About 14,000 chemical features were found in each sample, and all data were statistically analyzed by multi-variate analysis to show differences in different sampling campaigns. All of the results from principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and sparse partial least squares discriminant analysis (sPLS-DA) revealed differences between the two sampling campaigns. All chemical features were filtered by peak shape and MS/MS patterns compared to theoretical data for the chemical annotation. Peak intensity was also compared to filter the data by comparing quality control (QC) samples, pooling all samples for each sampling campaign, respectively, and filter blank samples. Consequently, 23 soluble chemicals were identified, and these chemicals were grouped into five groups: pharmaceuticals and personal care products (PPCPs) related, biocide-related, traffic-related, tobacco-related, and others, as its usage. Concentrations of all chemicals in each sample were estimated based on their peak areas, and the relative quantification results of all chemicals for each sampling campaign were compared. Relative concentration for most of the chemicals was higher in January than in December, similar to the other characteristics of PM2.5, such as PM2.5 mass. There was an event of severe smog in January 2018 compared to December 2018, and the event, like air pollution, could be a factor of these soluble chemicals in PM2.5. Interestingly, 1,3-diphenyl guanidine (DPG) has an opposite result, showing lower in January and higher in December. Based on the possible source of this substance, factors like the amount of traffic on roads could be critical because its main source would be tires and tire wear particles due to its usage as a linker for polymers in tire manufacturing. This substance is of concern as one of the emerging chemicals in the environment, but this is the first report to find it as one of the components in PM2.5. Among these 23 chemicals, 13 chemicals were selected, and their absolute quantification analysis by LC-MS-based multiple reaction monitoring (MRM) method with their reference standard materials for all samples will be performed to verify the quantification results in future works.
References
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| Keywords | Ambient PM2.5, Non-target analysis, Emerging chemicals, Human health, Exposure |
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