Atmospheric chemistry of organic aerosols : a Singapore case study
Organic aerosols (OA) influence the climate by interacting with light and water in the atmosphere. To understand the climatic impacts of OA, light absorption and hygroscopic properties of OA are investigated. PM2.5 filter samples collected in Singapore during March-May of 2019 were analysed using at...
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Format: | Thesis-Doctor of Philosophy |
Language: | English |
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Nanyang Technological University
2022
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Online Access: | https://hdl.handle.net/10356/155432 https://doi.org/10.21979/N9/CNHTJL |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Organic aerosols (OA) influence the climate by interacting with light and water in the atmosphere. To understand the climatic impacts of OA, light absorption and hygroscopic properties of OA are investigated. PM2.5 filter samples collected in Singapore during March-May of 2019 were analysed using atmospheric pressure chemical ionization-mass spectrometry (APCI-MS), time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and ultraviolet-visible spectroscopy (UV-Vis). Firstly, by employing a soft-ionization mass spectrometric approach, I identified that major light-absorbing OA were likely emitted from a methane-rich combustion source in Singapore. Secondly, I provided a framework of the relationship among volatility, water-solubility, and molecular weight (MW) of OA. APCI-MS data confirmed the polarity and MW distributions for OM in the framework. Through factor analyses of APCI-MS and UV-Vis data, an inter-relationship of polarity, MW and light absorption properties was established. Lastly, I propose 1-octanol water partition coefficient (KOW) as a new predictor of liquid-liquid phase separation (LLPS) in OA induced by hygroscopic changes. By analysing datasets from literature, a decision boundary is found at log KOW = 0. LLPS tends to occur for organic compounds with log KOW > 0, while LLPS is likely inhibited for other cases (i.e., log KOW < 0). Experimental results have shown positive trends between LLPS and log KOW as well. |
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