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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Stefanos Papagiannis | en |
| dc.date.accessioned | 2026-03-05T08:53:09Z | - |
| dc.date.available | 2026-03-05T08:53:09Z | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/39831 | - |
| dc.rights | CC0 1.0 Universal | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.subject | X-ray fluorescence (XRF), Atmospheric aerosols, Quantitative and qualitative analysis, Source apportionment, Atmospheric aerosol source identification, Particle-induced X-ray emission (PIXE) | en |
| dc.title | Characterization of atmospheric aerosol composition and sources of pollution with Χ- ray spectrometry techniques | en |
| dc.title | Χαρακτηρισμός των συστατικών ατμοσφαιρικού αερολύματος και των πηγών ρύπανσης με τεχνικές φασματομετρίας ακτίνων-Χ | el |
| dc.type | doctoralThesis | * |
| heal.type | doctoralThesis | el |
| heal.type.en | Doctoral thesis | en |
| heal.type.el | Διδακτορική διατριβή | el |
| heal.classification | Analytical atomic spectrometry and environmental physics | |
| heal.dateAvailable | 2026-03-05T08:54:09Z | - |
| heal.language | en | el |
| heal.access | free | el |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Πολυτεχνική Σχολή | el |
| heal.publicationDate | 2026-02-24 | - |
| heal.abstract | The primary objective of this doctoral dissertation is to advance and validate non-destructive X-ray analytical techniques for the quantitative chemical characterization of atmospheric aerosol filters. While traditional air quality monitoring relies heavily on bulk mass concentrations (PM₁₀, PM₂.₅), this work addresses the critical need for detailed elemental data by optimizing a suite of complementary spectroscopic methods—ranging from Energy-Dispersive X-ray Fluorescence (ED-XRF), Wavelength-Dispersive X-ray Fluorescence (WD-XRF), micro-XRF Imaging, Near Real-Time XRF (NRT-XRF), and Particle-Induced X-ray Emission (PIXE). A central contribution of this research is the rigorous development of analytical protocols that overcome existing limitations regarding calibration, spatial heterogeneity, and instrument intercomparability. By systematically cross-validating these techniques, the study establishes a robust framework for obtaining reliable and high-resolution chemical data essential for understanding aerosol composition. Beyond methodological innovation, the research aims to bridge the gap between instrumental development and practical environmental application through determining the sources of particulate pollution in diverse and under-studied environments. The optimized analytical protocols were applied to real-world case studies, enabling a harmonized source identification across six diverse sites in Greece and the first multi-year source apportionment in a heavily polluted city in Central Asia. These applications demonstrate the capability of the developed methods to identify specific anthropogenic drivers, such as residential biomass burning and industrial emissions, thereby providing the scientifically grounded evidence required for policymakers to design effective, targeted air quality mitigation strategies. Airborne particulate matter (PM) remains one of the most pressing environmental challenges and threats to public health worldwide. Fine and coarse particles not only degrade air quality and visibility but also contribute to adverse health effects, including respiratory and cardiovascular diseases. The chemical composition of PM reflects a complex mixture of natural and anthropogenic sources, atmospheric processes, and long-range transport; therefore, its characterization is fundamental for understanding impacts and supporting mitigation policies. Despite significant progress, major challenges remain in the quantitative chemical analysis of aerosol samples. Traditional monitoring networks provide information on mass concentrations (PM₁₀, PM₂.₅); however, these data are insufficient for source identification and process understanding. Instead, detailed elemental and compositional data are required. In this context, non-destructive, multi-element techniques such as X-ray fluorescence (XRF) and particle-induced X-ray emission (PIXE) have become essential tools in atmospheric sciences. Nevertheless, the application of these techniques to thin aerosol deposits collected on filters requires careful calibration, rigorous uncertainty estimation, and systematic intercomparison. This Doctoral Dissertation addresses these challenges by combining advanced X-ray fluorescence (XRF) methods with ion-beam analysis (PIXE) for the chemical characterization of atmospheric aerosols. To this end, several complementary spectrometers were employed, including a secondary-target ED-XRF, a high-resolution WD-XRF, a portable ED-XRF (HH-XRF), a micro-XRF scanner for spatially resolved analysis of multi-stage impactor filters, a near real-time XRF spectrometer (NRT-XRF) evaluated through direct comparison with a laboratory ED-XRF, as well as a dedicated PIXE setup at the Institute of Nuclear and Particle Physics (INPP) of NCSR “Demokritos”. Through careful optimization and cross-validation, these methodologies were adapted to deliver reliable quantitative analysis of aerosol filters. The central objective of this dissertation is twofold: (a) the advancement and application of non-destructive analytical techniques for the quantitative determination of aerosol elemental composition, and (b) the use of these techniques to improve the understanding of particulate pollution sources in diverse environments. The work contributes both to the optimization of analytical protocols and to the broader effort of investigating pollution sources, with the aim of providing accurate public information and supporting effective mitigation strategies. The first part of the dissertation (Chapters 1–7) provides the scientific foundation for studying atmospheric particulate matter (PM). It begins with the definition and physical characteristics of aerosols, highlighting their size range, formation mechanisms, and ability to undergo transformations and long-range transport. It then examines filter-based sampling methodologies, emphasizing the advantages and limitations of different substrates and their implications for subsequent chemical analysis. A detailed overview of the chemical composition of atmospheric PM follows, covering crustal, marine, secondary inorganic, carbonaceous components, and trace elements, linking them to environmental and health impacts. Finally, Positive Matrix Factorization (PMF), the main receptor model used in this dissertation, is presented, focusing on its mathematical framework, treatment of uncertainty, and diagnostic tools. The second part (Chapters 8–10) is dedicated to the analytical foundations of the applied X-ray methods. It introduces the physical principles of X-ray fluorescence (XRF), including excitation processes, attenuation, and quantification strategies, with particular emphasis on thin targets such as aerosol filters. Complementarily, the fundamental principles of particle-induced X-ray emission (PIXE) are described, outlining ion–matter interactions, geometries, and calibration requirements for aerosol analysis. Together, these chapters establish the theoretical basis for the quantitative interpretation of spectra obtained with different instruments and provide the framework necessary to adapt XRF and PIXE techniques to the specific challenges of environmental aerosol research. The third part (Chapters 11–12) presents the experimental setups used. These include the secondary-target ED-XRF spectrometer (Epsilon 5, PANalytical), the portable HH-XRF analyzer (Tracer 5i, Bruker), the large-area μ-XRF scanner (M6 Jetstream, Bruker), the WD-XRF spectrometer (ZSX Primus IV, Rigaku), and the near real-time XRF spectrometer (NRT-XRF) (Xact 625i, SailBri Cooper) for automated hourly elemental monitoring. In addition, the specialized external-beam PIXE facility of the Institute of Nuclear and Particle Physics (INPP), NCSR “Demokritos”, is described. The fourth part of the dissertation (Chapters 13–19) presents the experimental results, beginning with the X-ray analytical methodologies (Chapters 13–17) and continuing with their application in source apportionment studies (Chapters 18–19). Initially, the methodological performance of the new analytical tools was investigated. The portable HH-XRF spectrometer (Tracer 5i, Bruker) was optimized for aerosol filter analysis, calibrated against thin-film standards, and compared with the laboratory ED-XRF system (Epsilon 5, PANalytical). The results demonstrate strong performance across 24 elements. Additionally, an analytical protocol using μ-XRF (M6 Jetstream, Bruker) was developed for filters from a multi-stage impactor, providing spatially resolved quantification of elements across different particle size fractions. In this context, the spatial heterogeneity of aerosol deposition on filters was systematically examined. Further enhancement of laboratory instrumentation was achieved through the calibration of a WD-XRF spectrometer (ZSX Primus IV, Rigaku). Using thin-film standards and reference filters, the WD-XRF proved to be a reliable and complementary tool, offering superior energy resolution. An additional methodological contribution is the development of a quantitative external-beam PIXE protocol. Using two SDD detectors, calibration for aerosol filters was successfully achieved. Finally, an intercomparison was performed between the benchtop ED-XRF spectrometer (Epsilon 5, PANalytical) and the NRT-XRF instruments (Xact 625i and Xact 625, SailBri Cooper) in three European cities. The study highlights the complexity of intercomparisons between different XRF instrument types and substrates. After the development and evaluation of the X-ray methodologies, they were applied to real-world case studies in different geographical contexts. The first study focuses on Central Asia, presenting the first multi-year PM₂.₅ source apportionment in Dushanbe, Tajikistan. Using gravimetric elemental analysis with ED-XRF and black carbon (BC) measurements, the results reveal persistently high PM₂.₅ levels, far exceeding European standards and World Health Organization (WHO) guidelines. The Positive Matrix Factorization (PMF) model identified eight pollution sources, including coal burning, biomass burning, emissions from cement industries, crustal dust, secondary aerosols, and emissions from power plants. Strong seasonality in source contributions was observed, with residential coal burning dominating in winter and power-plant emissions increasing during warmer months. In the European context, a comprehensive study was conducted in Greece within the PANACEA project. Six stations representing urban, suburban, and rural environments were monitored using ED-XRF, carbon analyses (OC and EC), and ion chromatography. The resulting source apportionment highlights the interplay among traffic emissions, biomass burning, secondary aerosols, and natural sources, with site-specific contributions reflecting local conditions and meteorology. This work establishes a coherent national dataset that can inform targeted mitigation strategies. Finally, the fifth part summarizes the main conclusions of the dissertation, emphasizing the successful bridging of instrumental development and environmental application. | en |
| heal.advisorName | Dimitrios Anagnostopoulos | en |
| heal.committeeMemberName | Andreas-Germanos Karydas | en |
| heal.committeeMemberName | Evangelia Diapouli | en |
| heal.committeeMemberName | Mihalis Karakasidis | en |
| heal.committeeMemberName | Nikolaos Zafeiropoulos | en |
| heal.committeeMemberName | Konstantinos Spyrou | en |
| heal.committeeMemberName | Konstantinos Eleftheriadis | en |
| heal.academicPublisher | Πανεπιστήμιο Ιωαννίνων. Πολυτεχνική Σχολή. Τμήμα Μηχανικών Επιστήμης Υλικών | el |
| heal.academicPublisherID | uoi | el |
| heal.numberOfPages | 305 | el |
| heal.fullTextAvailability | true | - |
| Appears in Collections: | Διδακτορικές Διατριβές - ΜΕΥ | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| PhDThesisStefanosPapagiannis.pdf | 12.72 MB | Adobe PDF | View/Open |
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