Dixon, William J. (2018) Quantitative analysis of secondary organic aerosol using a high-resolution mass spectral database. PhD thesis, University of York.
Abstract
Organic aerosol is an important factor in the atmospheric pollution, contributing up to 90% of the total aerosol. The complex system of sources and pathways of functionalisation these compounds can undergo, lead to a large number of compounds which exist in the organic fraction. The state of this organic fraction is in flux, due to the varying contributions of sources and the oxidative aging of the air mass.
A purpose-built, UPLC-MS2 method, combined with a semi-targeted automated processing software was developed to compliment large datasets required for high temporal resolution. This method was validated using previous analysis of organic aerosol from London and Birmingham.
The organic fraction in Beijing, China was observed from high resolution off-line filter samples during two field campaigns during winter 2016 and summer 2017. In total 646 compounds were identified during these campaigns, of which, the nitrophenolics and organosulfates were observed to be the most important groups. Hierarchical cluster analyses were applied to these two groups to determine the most important clusters within these heteroatom groups.
43 nitrophenolics were observed in the organic aerosol and 191 organosulfates. Nitrophenolics observed by this method show very high variation in ionisation efficiency based on structural isomerism, with ionisation efficiency varying of factors up to three orders of magnitude. The most significant organosulfates are more locally sourced to the Beijing area.
Metadata
Supervisors: | Hamilton, Jacqui and Rickard, Andrew and Pereira, Kelly |
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Related URLs: | |
Awarding institution: | University of York |
Academic Units: | The University of York > Chemistry (York) |
Identification Number/EthosID: | uk.bl.ethos.808714 |
Depositing User: | Mr William J. Dixon |
Date Deposited: | 26 Jun 2020 23:43 |
Last Modified: | 21 Jul 2020 09:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:27120 |
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