TY - JOUR
T1 - Comparative analysis of organic chemical compositions in airborne particulate matter from Ulaanbaatar, Beijing, and Seoul using UPLC-FT-ICR-MS and artificial neural network
AU - Son, Seungwoo
AU - Park, Moonhee
AU - Jang, Kyoung Soon
AU - Lee, Ji Yi
AU - Wu, Zhijun
AU - Natsagdorj, Amgalan
AU - Kim, Young Hwan
AU - Kim, Sunghwan
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/11/25
Y1 - 2023/11/25
N2 - This paper presents comparative study on the composition and sources of PM2.5 in Ulaanbaatar, Beijing, and Seoul. Ultrahigh performance liquid chromatography (UPLC) combined with ultrahigh resolution mass spectrometry (UHR-MS) were employed to analyze 85 samples collected in winter. The obtained 340 spectra were interpreted with artificial neural network (ANN). PM2.5 mass concentrations in Ulaanbaatar were significantly higher than those in Beijing and Seoul. ANN based interpretation of UPLC UHR-MS data showed that aliphatic/lipid derived organo‑sulfur compounds, polycyclic aromatic and organo‑oxygen compounds were characteristic to Ulaanbaatar. Whereas, aliphatic/lipid-derived organo‑oxygen compounds were major components in Beijing and Seoul. Aromatic organo‑nitrogen compounds were the main contributors to differentiating the spectra obtained from Beijing from the other cities. Based on two-dimensional gas chromatography/high resolution mass spectrometric (GCxGC/HRMS) data, it was determined that the concentrations of the polycyclic aromatic hydrocarbon (PAH) and polycyclic aromatic sulfur heterocycle (PASH) containing sulfur were highest in Ulaanbaatar, followed by Beijing and Seoul. Coal/biomass combustion was identified as the primary source of contamination in Ulaanbaatar, while petroleum combustion was the main contributor to PM2.5 in Beijing and Seoul. The conclusion that diesel-powered heavy-duty trucks and buses are the main contributors to NOx emissions in Beijing is consistent with previous reports. This study provides a more comprehensive understanding of the composition and sources of PM2.5 in the three cities, with a focus on the differences in their atmospheric pollution profiles based on the UPLC UHR-MS and ANN analysis. It is notable that this study is the first to utilize this method on a large-scale sample set, providing a more detailed and molecular-level understanding of the compositional differences among PM2.5. Overall, the study contributes to a better understanding of the sources and composition of PM2.5 in Northeast Asia, which is essential for developing effective strategies to reduce air pollution and improve public health.
AB - This paper presents comparative study on the composition and sources of PM2.5 in Ulaanbaatar, Beijing, and Seoul. Ultrahigh performance liquid chromatography (UPLC) combined with ultrahigh resolution mass spectrometry (UHR-MS) were employed to analyze 85 samples collected in winter. The obtained 340 spectra were interpreted with artificial neural network (ANN). PM2.5 mass concentrations in Ulaanbaatar were significantly higher than those in Beijing and Seoul. ANN based interpretation of UPLC UHR-MS data showed that aliphatic/lipid derived organo‑sulfur compounds, polycyclic aromatic and organo‑oxygen compounds were characteristic to Ulaanbaatar. Whereas, aliphatic/lipid-derived organo‑oxygen compounds were major components in Beijing and Seoul. Aromatic organo‑nitrogen compounds were the main contributors to differentiating the spectra obtained from Beijing from the other cities. Based on two-dimensional gas chromatography/high resolution mass spectrometric (GCxGC/HRMS) data, it was determined that the concentrations of the polycyclic aromatic hydrocarbon (PAH) and polycyclic aromatic sulfur heterocycle (PASH) containing sulfur were highest in Ulaanbaatar, followed by Beijing and Seoul. Coal/biomass combustion was identified as the primary source of contamination in Ulaanbaatar, while petroleum combustion was the main contributor to PM2.5 in Beijing and Seoul. The conclusion that diesel-powered heavy-duty trucks and buses are the main contributors to NOx emissions in Beijing is consistent with previous reports. This study provides a more comprehensive understanding of the composition and sources of PM2.5 in the three cities, with a focus on the differences in their atmospheric pollution profiles based on the UPLC UHR-MS and ANN analysis. It is notable that this study is the first to utilize this method on a large-scale sample set, providing a more detailed and molecular-level understanding of the compositional differences among PM2.5. Overall, the study contributes to a better understanding of the sources and composition of PM2.5 in Northeast Asia, which is essential for developing effective strategies to reduce air pollution and improve public health.
KW - Airborne particulate matter
KW - Artificial neural network
KW - FT-ICR MS
KW - GCxGC/HRMS
KW - Organo‑nitrogen
KW - Organo‑sulfur
UR - http://www.scopus.com/inward/record.url?scp=85166468554&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2023.165917
DO - 10.1016/j.scitotenv.2023.165917
M3 - Article
C2 - 37527716
AN - SCOPUS:85166468554
SN - 0048-9697
VL - 901
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 165917
ER -
