This title appears in the Scientific Report :
2012
Please use the identifier:
http://hdl.handle.net/2128/4957 in citations.
Experimental determination of the partitioning coefficient of nopinone as a marker substance in organic aerosol
Experimental determination of the partitioning coefficient of nopinone as a marker substance in organic aerosol
Atmospheric aerosols have a significant influence on the radiation budget and chemical processes in the atmosphere. Thus, they have an impact on climate. They are relevant in many environmental processes and influence human health. In many regions, secondary organic aerosol (SOA) makes a major contr...
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Personal Name(s): | Steitz, Bettina (Corresponding author) |
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Contributing Institute: |
Troposphäre; IEK-8 |
Imprint: |
Jülich
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
2013
|
Physical Description: |
132 p. |
Dissertation Note: |
Dissertation, Universität Wuppertal, 2012 |
ISBN: |
978-3-89336-862-4 |
Document Type: |
Book Dissertation / PhD Thesis |
Research Program: |
Trace gas and aerosol processes in the troposphere |
Series Title: |
Schriften des Forschungszentrums Jülich : Energie & Umwelt / Energy & Environment
169 |
Subject (ZB): | |
Link: |
OpenAccess |
Publikationsportal JuSER |
Atmospheric aerosols have a significant influence on the radiation budget and chemical processes in the atmosphere. Thus, they have an impact on climate. They are relevant in many environmental processes and influence human health. In many regions, secondary organic aerosol (SOA) makes a major contribution to the total aerosol mass. Therefore, SOA significantly influences aerosol properties. The complex and versatile chemical composition of SOA makes the analysis of its formation and chemical behavior difficult and thus complicates global and local climate modeling. One major issue in current models is the prediction of the organic matter in the atmosphere. For this, a detailed understanding of SOA formation from volatile organic compounds (VOCs) is of importance. VOCs undergo oxidation in the atmosphere which results in the formation of semivolatile organic compounds. These partition between the gas and the particle phase. The compoundspecific gas-to-particle partitioning can be described with the temperature-dependent partitioning coefficient. This work is dedicated to its experimental determination. To this end, a new measurement technique for compound-specific analysis of organic aerosol was used. The Aerosol Collection Module (ACM) is a newly developed instrument which collects aerosol particles, converts them into the gas phase via thermal desorption and transfers them to a gas phase detector for further analysis. In this work, the ACM was coupled to a high-resolution Proton Transfer Reaction-Time of Flight-Mass Spectrometer (PTR-ToF-MS)for the first time and used in $\alpha$ -, and $\beta$-pinene ozonolysis experiments at the AIDA chamber of the Karlsruhe Institute of Technology (KIT). For the data analysis, routines were developed based on Aerosol Mass Spectrometer (AMS) data analysis. The partitioning coefficient of nopinone, as the major $\beta$-pinene ozonolysis product, and its temperature dependence was determined. For this purpose, two experimental approaches were employed: the coupling of ACM and PTR-ToF-MS, and measurements using the PTRToF- MS with and without particle filter. The temperature dependence of the partitioning coefficient derived from ACM and PTR-ToF-MS was comparable to the theoretical temperature dependence found in literature. A comparison with calculated partitioning coefficients following theory showed that the experimental partitioning coefficients of this work were about one order of magnitude higher. This leads to the conclusion that the amount of nopinone in the aerosol particle phase is underestimated by theory. As literature on experimentally derived partitioning coefficients is sparse, further investigations of the partitioning coefficient of other substances with the combination of ACM and PTR-ToF-MS could help to improve the understanding of SOA formation and, thus, SOA prediction. |