Towards Mitigation of Volcanic Risks through Ultraviolet Remote Sensing

Student thesis: Phd

Abstract

Volcanic eruptions pose a significant risk to human health and infrastructure. With a growing population living in close proximity to historically active volcanoes, the capacity to mitigate these risks is essential. This is primarily achieved by monitoring volcanoes during eruptions and periods of quiescence. In recent decades, volcanic gas fluxes have been monitored using UV spectrometers and cameras both by short-term campaign measurements and in long-term automated monitoring networks, generating a wealth of expertise, instrumentation and data. The application of such instruments for risk reduction forms the central theme for this thesis, which asks two questions. Firstly, how can we utilise the existing infrastructure and instrumentation designed to measure volcanic gases to also investigate volcanic ash plumes and secondly, how can we improve the quality of the techniques already used to measure these volcanic gases? For the first question, I adapted existing UV cameras and spectrometers to measure volcanic ash through depolarisation imaging and application of spectral analysis techniques developed for UV satellite instruments to ground-based measurements. The results show that existing UV instrumentation can be adapted relatively easily to also measure volcanic ash, providing insights into ash plume dynamics and geometry. These techniques could be used in the future to help inform ash dispersal simulations, helping to mitigate the risks from ash rich eruptions. To improve current volcanic gas measurements, I developed and demonstrated two new tools, named iFit and OpenSO2. The first is a technique to easily retrieve absolute SO2 slant column densities from UV scattered sunlight spectra without a measured reference spectrum. This technique could help to improve the quality and reliability of future gas flux measurements, allowing volcanic processes to be better investigated. The second is an automated UV scanning system controlled by a Raspberry Pi, a low-cost single board computer, designed to be simpler and more adaptable than existing systems to allow volcano observatories more control over their monitoring instruments. The software for both these projects is written in Python and freely available online, making these methods highly accessible for maximum impact. These tools have been well received by the volcanological community. The iFit software has been utilised by several volcano monitoring agencies, including the Montserrat Volcano Observatory, the Istituto Nazionale di Geofisica e Vulcanologia in Italy and the Geological Survey of Japan. The OpenSO2 system has been installed on Montserrat to monitor long term SO2 fluxes from Soufriere Hills Volcano, with plans to install new instruments at La Soufriere in St Vincent and Volcan de Colima in Mexico. The tools and techniques developed in this thesis will help to improve future volcano monitoring of gas fluxes and ash plumes, helping to mitigate volcanic risks in the future.
Date of Award1 Aug 2021
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorHugh Coe (Supervisor) & Mike Burton (Supervisor)

Keywords

  • Sulphur Dioxide
  • Spectroscopy
  • Ultraviolet
  • Remote Sensing
  • Volcanic Ash
  • Volcanic Gas
  • Volcanology

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