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Titel |
Source characterization of ambient fine aerosol in Singapore during a haze episode in 2015 |
VerfasserIn |
Sri Hapsari Budisulistiorini, Matthieu Riva, Michael Williams, Takuma Miyakawa, Yuichi Komazaki, Jing Chen, Jason Surratt, Mikinori Kuwata |
Konferenz |
EGU General Assembly 2017
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 19 (2017) |
Datensatznummer |
250147720
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Publikation (Nr.) |
EGU/EGU2017-11923.pdf |
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Zusammenfassung |
Recurring transboundary haze from Indonesia peatland fires in the previous decades has
significantly elevated particulate matter (PM) concentration in Southeast Asia, particularly
during the 2015 El Niño event. Previous studies have investigated chemical composition of
particles emitted during haze episodes; however, they were limited to time-integrated samples
and the number of identified compounds. Low time-resolution measurement results
in co-variance of PM sources; therefore, higher time-resolution measurement is
important in PM source apportionment. Between October 10-31, 2015, Aerodyne
Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) was deployed for
real-time chemical characterization of ambient submicron PM (NR-PM1) in Singapore.
Simultaneously, PM2.5 filter samples were collected for molecular-level organic aerosol (OA)
constituents, organic carbon (OC), elemental carbon (EC) and water-soluble OC (WSOC)
analyses. OA constituents were quantified by gas chromatography interfaced to electron
ionization mass spectrometry (GC/EI-MS) and ultra-performance liquid chromatography
interfaced to electrospray ionization high-resolution quadrupole time-of-flight mass
spectrometer operated in the negative ion mode (UPLC/(-)ESI-HR-Q-TOFMS). OA and
SO42− are dominant components of the haze particles, accounting for ∼77% and
∼12% of the total NR-PM1 mass, respectively. OC/EC ratio of 4.8 might indicate
formation of secondary OA (SOA) and aerosols from biomass burning, including those
from peat burning. OA fraction from ToF-ACSM measurements was analyzed for
source apportionment using a bilinear model through multi-linear engine algorithm
(ME-2) in graphical user interface SoFi (Source Finder). Five OA factors were
identified: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), peat burning OA
(PBOA), low-volatility oxygenated OA (LV-OOA), and semi-volatile oxygenated OA
(SV-OOA). The HOA factor shows a distinct diurnal profile peaking in the morning and
evening, suggesting traffic influences. The BBOA factor was identified based on factor
profile of wood burning particles and correlated with known biomass burning tracers
(i.e. levoglucosan and mannosan). The PBOA factor was identified based on factor
profile of laboratory-generated peat burning particles. This factor would be further
identified with OA constituents in peat burning particles, such as brown carbon
constituents. The LV-OOA and SV-OOA factors peak in the afternoon indicating they were
likely formed through photochemistry. The LV-OOA factor might be a product of
biomass burning aerosol aging as indicated by temporal trend correlations with
BBOA and PBOA factors (r2 = 0.7–0.8). Contributions of the HOA and SV-OOA
factors to OA mass are ∼12% and ∼21%, respectively. The biomass burning-related
factors (BBOA and PBOA) account for ∼29% of OA mass, which likely indicates a
lower-bound estimate of the transboundary impacts of primary emissions from peatland
fires. The transboundary impacts of secondary aerosol from peatland fires might be
represented by the LV-OOA factor accounting for ∼37% of OA mass. Overall, the
transboundary haze could contribute to ∼66% of OA concentration, suggesting
the strong influence of Indonesia peatland fires on the air quality of Singapore. |
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