TY - JOUR
T1 - Seasonal variation and source apportionment of Oxygenated Polycyclic Aromatic Hydrocarbons (OPAHs) and Polycyclic Aromatic Hydrocarbons (PAHs) in PM2.5 in Seoul, Korea
AU - Shin, Sun Min
AU - Lee, Ji Yi
AU - Shin, Hye Jung
AU - Kim, Yong Pyo
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/3/1
Y1 - 2022/3/1
N2 - Oxygenated polycyclic aromatic hydrocarbons (OPAHs) are of increasing interest due to their high toxicity. Thirteen particulate PAHs and ten particulate OPAHs were analyzed by Gas Chromatography/Mass Spectrometry (GC/MS) in atmospheric particulate matter with aerodynamic diameters less than or equal to a nominal 2.5 μm (PM2.5) for the period between May 2020 and January 2021 in Seoul, Republic of Korea. The mean concentration ten OPAHs (5.49 ± 2.40 ng/m3) was higher than that of thirteen PAHs (3.96 ± 3.36 ng/m3), respectively. The concentration of total OPAHs was high in winter (9.40 ± 2.50 ng/m3) and low in summer (3.58 ± 0.78 ng/m3), showing the same trend with PAHs (9.16 ± 3.30 ng/m3 in winter and 0.62 ± 0.15 ng/m3 in summer). When comparing this study results with the measurement results on 2006 in Seoul, PAHs concentration dropped by 68% while only 22% was reduced for OPAHs. It suggests either improvement of combustion technology, i.e., high temperature combustion process in the region or higher ambient oxidation reaction rates on 2020 than 2006. Major sources and their contributions of PAHs and OPAHs were identified based on correlation analysis and Positive Matrix Factorization (PMF) modeling. Two cases were carried. Case 1 is for source apportionment for PM2.5 and case 2 is for OPAHs and PAHs. The number of factors or sources in the two cases was determined as 7 and 4, respectively. The results of the PMF modeling using diagnostic ratios (DRs) in case 1 identified 7 factors; secondary nitrate (23%), secondary sulfate (21%), vehicles (20%), biomass burning (16%), coal combustion (12%), waste incineration (5%), and OPAHs (5,12-NAQ) emission-related (3%). The PMF modeling results in case 2 revealed 4 factors; vehicles (36%), coal combustion (30%), biomass burning (25%), and OPAHs (5,12-NAQ) emission related (9%). Significant correlation between OPAHs and indicators of primary emission sources, and high contribution from sources with emission characteristics implied that most sources of OPAHs were heavily influenced by primary emissions rather than secondary formation.
AB - Oxygenated polycyclic aromatic hydrocarbons (OPAHs) are of increasing interest due to their high toxicity. Thirteen particulate PAHs and ten particulate OPAHs were analyzed by Gas Chromatography/Mass Spectrometry (GC/MS) in atmospheric particulate matter with aerodynamic diameters less than or equal to a nominal 2.5 μm (PM2.5) for the period between May 2020 and January 2021 in Seoul, Republic of Korea. The mean concentration ten OPAHs (5.49 ± 2.40 ng/m3) was higher than that of thirteen PAHs (3.96 ± 3.36 ng/m3), respectively. The concentration of total OPAHs was high in winter (9.40 ± 2.50 ng/m3) and low in summer (3.58 ± 0.78 ng/m3), showing the same trend with PAHs (9.16 ± 3.30 ng/m3 in winter and 0.62 ± 0.15 ng/m3 in summer). When comparing this study results with the measurement results on 2006 in Seoul, PAHs concentration dropped by 68% while only 22% was reduced for OPAHs. It suggests either improvement of combustion technology, i.e., high temperature combustion process in the region or higher ambient oxidation reaction rates on 2020 than 2006. Major sources and their contributions of PAHs and OPAHs were identified based on correlation analysis and Positive Matrix Factorization (PMF) modeling. Two cases were carried. Case 1 is for source apportionment for PM2.5 and case 2 is for OPAHs and PAHs. The number of factors or sources in the two cases was determined as 7 and 4, respectively. The results of the PMF modeling using diagnostic ratios (DRs) in case 1 identified 7 factors; secondary nitrate (23%), secondary sulfate (21%), vehicles (20%), biomass burning (16%), coal combustion (12%), waste incineration (5%), and OPAHs (5,12-NAQ) emission-related (3%). The PMF modeling results in case 2 revealed 4 factors; vehicles (36%), coal combustion (30%), biomass burning (25%), and OPAHs (5,12-NAQ) emission related (9%). Significant correlation between OPAHs and indicators of primary emission sources, and high contribution from sources with emission characteristics implied that most sources of OPAHs were heavily influenced by primary emissions rather than secondary formation.
KW - Combustion technology change
KW - Diagnostic ratios (DRs)
KW - OPAHS sources
KW - PM source apportionment
KW - Positive matrix factorization (PMF)
UR - http://www.scopus.com/inward/record.url?scp=85122910503&partnerID=8YFLogxK
U2 - 10.1016/j.atmosenv.2022.118937
DO - 10.1016/j.atmosenv.2022.118937
M3 - Article
AN - SCOPUS:85122910503
SN - 1352-2310
VL - 272
JO - Atmospheric Environment
JF - Atmospheric Environment
M1 - 118937
ER -