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Final Copy 2019 11 28 Saxby This electronic thesis or dissertation has been downloaded from Explore Bristol Research, http://research-information.bristol.ac.uk Author: Saxby, Jennifer Title: From needles to plates extreme volcanic ash shapes and implications for dispersion modelling General rights Access to the thesis is subject to the Creative Commons Attribution - NonCommercial-No Derivatives 4.0 International Public License. A copy of this may be found at https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode This license sets out your rights and the restrictions that apply to your access to the thesis so it is important you read this before proceeding. Take down policy Some pages of this thesis may have been removed for copyright restrictions prior to having it been deposited in Explore Bristol Research. However, if you have discovered material within the thesis that you consider to be unlawful e.g. breaches of copyright (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please contact [email protected] and include the following information in your message: •Your contact details •Bibliographic details for the item, including a URL •An outline nature of the complaint Your claim will be investigated and, where appropriate, the item in question will be removed from public view as soon as possible. FROM NEEDLES TO PLATES:EXTREME VOLCANIC ASH SHAPES AND IMPLICATIONS FOR DISPERSION MODELLING Jennifer Saxby Supervisors: Katharine Cashman, Alison Rust, Frances Beckett A dissertation submitted to the University of Bristol in accordance with the requirements for award of the degree of Doctor of Philosophy in the Faculty of Science School of Earth Sciences Word Count: 30636 ABSTRACT Volcanic ash is hazardous to aircraft and can remain in the atmosphere for days or longer after an eruption. The rate of removal depends on meteorology and particle terminal fall velocity, which is sensitive to particle shape. However, most volcanic ash forecasts assume spherical particles; shape is difficult to quantify, and while the velocity of spheres can be determined analytically, modelling non-spheres relies on empirical drag laws. I assess the accuracy of drag laws for non-spheres for the range of flow regimes anticipated for volcanic ash falling in air, determine ash particle shape ranges, and assess the sensitivity of ash forecasts to shape. Measurements of ash from Icelandic eruptions show that shape descriptors based on surface area are highly sensitive to imaging resolution and the particle size fraction used. I compare calculated terminal velocities to those measured in a settling column for volcanic ash and analogues; shape- dependent drag laws produce more accurate results than a spherical approximation. Particle shape also impacts the method of size measurement, as size for non-spherical particles can be measured in several ways. Using the NAME model, I determine the sensitivity of ash forecasts to particle shape. Model particle trajectories are sensitive to shape where sedimentation velocities exceed atmospheric vertical velocities; a non-spherical 100 µm particle can travel 44% further than an equivalent- volume sphere. Therefore, the sensitivity of ash concentration forecasts to particle shape is dependent on the input particle size distribution. I use these insights on measuring and modelling particle shape to discuss how best to parameterise shape in operational dispersion modelling systems; I identify drag laws which are accurate for the whole range of flow regimes expected for volcanic ash falling in air and compile particle shape data in order to recommend default values for use with these laws. Author’s Declaration I declare that the work in this dissertation was carried out in accordance with the requirements of the University’s Regulations and Code of Practice for Research Degree Programmes and that it has not been submitted for any other academic award. Except where indicated by specific reference in the text, the work is the candidate’s own work. Work done in collaboration with, or with the assistance of, others, is indicated as such. Any views expressed in the dissertation are those of the author. ............................................ Jennifer Saxby September 18, 2019 ii Acknowledgments Firstly I would like to thank my supervisors. Kathy Cashman, Alison Rust and Frances Beckett have provided a huge amount of advice, guidance and feedback over the last 4 years. I’d also like to thank my other co-authors, Elly Tennant and Hannah Rodger. Supervising your Master’s projects was a highlight of my PhD work, so thank you for being so enthusiastic and a pleasure to work with. Special thanks must go to Frances Boreham for camping and sharing a truck with me during 3 weeks of fieldwork in Iceland; her stream-fording skills are exceptional. Thanks also to Frances, Nick and David for the daily coffee breaks and general office fun over the last 4 years. Thank you Tom Davies for all your help with X-ray tomography and data processing, and to Charles Clapham for your enthusiastic help with building lab equipment and for accommodating my sometimes last-minute requests. Thank you to Stefan Wastegard˚ and Simon Larsson from the University of Stockholm for showing Kathy and I around your wonderful city and for sharing your tephra. Thanks also to Jan Mangerud from the University of Bergen for taking the time to send me samples. Finally I’d like to thank the whole Atmospheric Dispersion and Air Quality group at the Met Office for all of your invaluable help over the last 4 years and for being so welcoming whenever I visit - it’s been a pleasure working with you all and I will miss it very much! iii Contents Abstract i Author’s Declaration ii Acknowledgments iii Table of Contents iv List of Figures ix List of Tables xi 1 Introduction1 1.1 Motivations......................................1 1.2 Overview of research methods............................4 1.2.1 Field campaign................................4 1.2.2 Particle settling in the lab...........................8 1.2.3 Ash dispersion modelling.......................... 12 1.3 Thesis overview.................................... 14 1.3.1 Chapter2: The impact of particle shape on fall velocity: Implications for volcanic ash dispersion modelling...................... 14 1.3.2 Chapter3: The importance of grain size and shape in controlling the dispersion of the Vedde cryptotephra..................... 15 1.3.3 Chapter4: How to measure the shape of volcanic ash, and recommendations for dispersion modelling................. 16 1.3.4 Chapter5: Conclusions............................ 16 iv 2 The impact of particle shape on fall velocity: implications for volcanic ash dispersion modelling 17 2.1 Introduction...................................... 19 2.2 Background...................................... 20 2.2.1 Modelling sedimentation........................... 21 2.2.2 Volcanic ash forecasting........................... 22 2.2.3 The plume and ash cloud phases of ash transport and their representation in ash dispersion models........................... 24 2.2.4 Quantifying ash morphology......................... 25 2.3 Evaluation of sedimentation schemes and shape descriptors for non-spherical particles........................................ 27 2.3.1 Particle settling data............................. 31 2.4 Quantifying volcanic ash shape............................ 35 2.4.1 2D shape analysis using scanning electron microscopy (SEM)....... 35 2.4.2 3D shape analysis using X-ray computed microtomography (CT)..... 35 2.4.3 Volcanic ash shape data........................... 36 2.5 Sensitivity of dispersion model forecasts to particle shape.............. 37 2.5.1 Sensitivity of vertical velocity........................ 38 2.5.2 Sensitivity of particle travel distance..................... 44 2.5.3 Sensitivity of atmospheric ash loading.................... 45 2.6 Discussion....................................... 49 2.6.1 Shape and sedimentation schemes...................... 49 2.6.2 Quantifying volcanic ash shape....................... 51 2.6.3 Operational volcanic ash forecasting..................... 53 2.6.4 Beyond the days after eruption........................ 54 3 The importance of grain size and shape in controlling the dispersion of the Vedde cryptotephra 56 3.1 Introduction...................................... 58 3.1.1 Particle shape and tephra transport...................... 59 3.1.2 The Vedde ash................................ 59 3.2 Methods........................................ 62 v 3.2.1 Determining particle size, shape and density................. 62 3.2.2 Dispersion modelling............................. 64 3.3 Results......................................... 68 3.3.1 Particle size and shape............................ 68 3.3.2 Modelled travel distance........................... 70 3.3.3 Cryptotephra sampling strategies....................... 73 3.4 Discussion....................................... 75 4 How to measure the shape of volcanic ash, and recommendations for dispersion modelling 79 4.1 Introduction...................................... 81 4.2 Modelling the terminal velocity of non-spherical ash................ 82 4.3 Tephra samples.................................... 83 4.4 Measurements..................................... 84 4.4.1 Particle velocities............................... 84 4.4.2 Density.................................... 86 4.4.3
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