A comparative study of PM2.5 source apportionment and toxicological effects based on differences in heavy metal analysis methods

Ultrafine dust research is being conducted using the Positive Matrix Factorization (PMF) model to identify receptor-centered pollutants. Among the various chemical components used in the PMF model, trace elements such as heavy metals serve as indicators of pollutants emitted by industries. ICP-MS and XRF are used to analyze these trace elements. ICP-MS is the most widely used method for analyzing heavy metals and has a low detection limit, allowing it to analyze even trace concentrations. However, there are limits to reanalysis because it requires a complex sample pretreatment process and consumes samples. On the other hand, XRF has the advantage of being able to analyze samples without pretreatment and that reanalysis is possible at any time because the samples are not consumed. However, compared to ICP-MS, the detection limit is relatively high and the uncertainty increases when the amount is small. In this study, we sought to determine whether these differences in analysis methods affect the identification of industrial pollutants. The PMF model was performed by analyzing 107 PM_2.5 filters collected at 4-day intervals from November 2021 to December 2022. The same analysis method was used for carbon and ion components, excluding trace elements. Through this study, we will be able to find out what differences the model results obtained through different analysis methods have in deriving industrial pollution sources. Additionally, it is expected that more reliable results will be obtained in accurate pollutant source estimation and weight determination.

Acknowledgement

This research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI) funded by the Ministry of Environment (MOE).