Molten-Volcanic-Ash-Phobic Thermal Barrier Coating based on Biomimetic Structure

Volcanic ash is a major threat to aviation safety. The softening/melting temperatures of volcanic ash lie far below typical aero-engine operating temperatures. Thus, molten ash can accelerate the failure of thermal barrier coatings (TBCs). Here, inspired by natural superhydrophobic surfaces (e.g., the lotus leaf), a molten-volcanic-ash-phobic TBC, which provides a large possibility to eliminate molten ash issues of TBCs, is developed. A hierarchically structured surface is first prepared on a (Gd_0.9 Yb_0.1 )₂ Zr₂ O₇ (GYbZ) pellet by ultrafast laser direct writing technology, aiming to confirm the feasibility of the biomimetic microstructure to repel molten volcanic ash wetting. Then biomimetic-structured GYbZ TBCs are successfully fabricated using plasma spray physical vapor deposition, which reveals "silicate" phobicity at high temperatures. The exciting molten-volcanic-ash-phobic attribute of the designed surfaces is attributed to the lotus-leaf-like dual-scale microstructure, emulating in particular the existence of nanoparticles. These findings may be an important step toward the development of next-generation aviation engines with greatly reduced vulnerability to environmental siliceous debris.

A Near-Real-Time Method for Estimating Volcanic Ash Emissions Using Satellite Retrievals

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions.

The fate of volcanic ash: premature or delayed sedimentation?

A large amount of volcanic ash produced during explosive volcanic eruptions has been found to sediment as aggregates of various types that typically reduce the associated residence time in the atmosphere (i.e., premature sedimentation). Nonetheless, speculations exist in the literature that aggregation has the potential to also delay particle sedimentation (rafting effect) even though it has been considered unlikely so far. Here, we present the first theoretical description of rafting that demonstrates how delayed sedimentation may not only occur but is probably more common than previously thought. The fate of volcanic ash is here quantified for all kind of observed aggregates. As an application to the case study of the 2010 eruption of Eyjafjallajökull volcano (Iceland), we also show how rafting can theoretically increase the travel distances of particles between 138-710 μm. These findings have fundamental implications for hazard assessment of volcanic ash dispersal as well as for weather modeling.

The Impact of Ensemble Meteorology on Inverse Modeling Estimates of Volcano Emissions and Ash Dispersion Forecasts: Grímsvötn 2011

Volcanic ash can interact with the earth system on many temporal and spatial scales and is a significant hazard to aircraft. In the event of a volcanic eruption, fast and robust decisions need to be made by aviation authorities about which routes are safe to operate. Such decisions take into account forecasts of ash location issued by Volcanic Ash Advisory Centers (VAACs) which are informed by simulations from Volcanic Ash Transport and Dispersion (VATD) models. The estimation of the time-evolving vertical distribution of ash emissions for use in VATD simulations in real time is difficult which can lead to large uncertainty in these forecasts. This study presents a method for constraining the ash emission estimates by combining an inversion modeling technique with an ensemble of meteorological forecasts, resulting in an ensemble of ash emission estimates. These estimates of ash emissions can be used to produce a robust ash forecast consistent with observations. This new ensemble approach is applied to the 2011 eruption of the Icelandic volcano Grímsvötn. The resulting emission profiles each have a similar temporal evolution but there are differences in the magnitude of ash emitted at different heights. For this eruption, the impact of precipitation uncertainty (and the associated wet deposition of ash) on the estimate of the total amount of ash emitted is larger than the impact of the uncertainty in the wind fields. Despite the differences that are dominated by wet deposition uncertainty, the ensemble inversion provides confidence that the reduction of the unconstrained emissions (a priori), particularly above 4 km, is robust across all members. In this case, the use of posterior emission profiles greatly reduces the magnitude and extent of the forecast ash cloud. The ensemble of posterior emission profiles gives a range of ash column loadings much closer in agreement with a set of independent satellite retrievals in comparison to the a priori emissions. Furthermore, airspace containing volcanic ash concentrations deemed to be associated with the highest risk (likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85%. Such improvements could have large implications in emergency response situations. Future research will focus on quantifying the impact of uncertainty in precipitation forecasts on wet deposition in other eruptions and developing an inversion system that makes use of the state-of-the-art meteorological ensembles which has the potential to be used in an operational setting.

Operational Response to Volcanic Ash Risks Using HOTVOLC Satellite-Based System and MOCAGE-Accident Model at the Toulouse VAAC

In 2010, the Eyjafjallajökull volcano erupted, generating an ash cloud causing unprecedented disruption of European airspace. Despite an exceptional situation, both the London and Toulouse Volcanic Ash Advisory Centres (VAAC) provided critical information on the location of the cloud and on the concentration of ash, thus contributing to the crisis management. Since then, substantial efforts have been carried out by the scientific community in order to improve remote sensing techniques and numerical modeling. Satellite instruments have proven to be particularly relevant for the characterization of ash cloud properties and a great help in the operational management of volcanic risk. In this study, we present the satellite-based system HOTVOLC developed at the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC) using Meteosat geostationary satellite and designed for real-time monitoring of active volcanoes. After a brief presentation of the system we provide details on newly developed satellite products dedicated to the ash cloud characterization. This includes, in particular, ash cloud altitude and vertical column densities (VCD). Then, from the Stromboli 2018 paroxysm, we show how HOTVOLC can be used in a timely manner to assist the Toulouse VAAC in the operational management of the eruptive crisis. In the second part of the study, we provide parametric tests of the MOCAGE-Accident model run by the Toulouse VAAC from the April 17 Eyjafjallajökull eruption. For this purpose, we tested a range of eruption source parameters including the Total Grain Size Distribution (TGSD), the eruptive column profile, the top plume height and mass eruption rate (MER), as well as the fine ash partitioning. Finally, we make a comparison on this case study between HOTVOLC and MOCAGE-Accident VCD.

Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits

The size distribution of volcanic ash is rarely measured in real time and Volcanic Ash Advisory Centres (VAACs) often rely on a default particle size distribution (PSD) to initialise their dispersion models when forecasting the movement of ash clouds. We conducted a sensitivity study to investigate the impact of PSD on model output and consider how best to apply default PSDs in operational dispersion modelling. Compiled grain size data confirm that, when considering particles likely to be in the distal ash cloud (< 125 µm diameter), magma composition and eruption size are the dominant controls on grain size distribution. Constraining the PSD is challenging but we find that the grain size of deposits from large hydromagmatic eruptions remains relatively constant with distance, suggesting that total (whole-deposit) grain size distributions (TGSDs) for these eruptions could be estimated from a few samples. We investigated the sensitivity of modelled ash mass loadings (in the air and on the ground) to input PSDs based on coarse to fine TGSDs from our dataset. We found clear differences between modelled mass loadings and the extent of the plume. Comparing TGSDs based on ground-only and ground-plus-satellite data for the Eyjafjallajökull 2010 eruption, we found that basing input PSDs on TGSDs from deposits alone (likely missing the finest particles) led to lower modelled peak ash concentrations and a smaller plume.

Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.

Using Satellite Data to Determine Empirical Relationships between Volcanic Ash Source Parameters

Poor knowledge of dispersion model source parameters related to quantities such as the total fine ash mass emission rate, its effective spatial distribution, and particle size distribution makes the provision of quantitative forecasts of volcanic ash a difficult problem. To ameliorate this problem, we make use of satellite-retrieved mass load data from 14 eruption case studies to estimate fine ash mass emission rates and other source parameters by an inverse modelling procedure, which requires multidimensional sampling of several thousand trial simulations with different values of source parameters. We then estimate the dependence of these optimal source parameters on eruption height. We show that using these empirical relationships in a data assimilation procedure leads to substantial improvements to the forecasts of ash mass loads, with the use of empirical relationships between parameters and eruption height having the added advantage of computational efficiency because of dimensional reduction. In addition, the use of empirical relationships, which encode information in satellite retrievals from past case studies, implies that quantitative forecasts can still be issued even when satellite retrievals of mass load are not available in real time due to cloud cover or other reasons, making it especially useful for operations in the tropics where ice and water clouds are ubiquitous.

Operational Modelling of Umbrella Cloud Growth in a Lagrangian Volcanic Ash Transport and Dispersion Model

Large explosive eruptions can result in the formation of an umbrella cloud which rapidly expands, spreading ash out radially from the volcano. The lateral spread by the intrusive gravity current dominates the transport of the ash cloud. Hence, to accurately forecast the transport of ash from large eruptions, lateral spread of umbrella clouds needs to be represented within volcanic ash transport and dispersion models. Here, we describe an umbrella cloud parameterisation which has been implemented into an operational Lagrangian model and consider how it may be used during an eruption when information concerning the eruption is limited and model runtime is key. We examine different relations for the volume flow rate into the umbrella, and the rate of spreading within the cloud. The scheme is validated against historic eruptions of differing scales (Pinatubo 1991, Kelud 2014, Calbuco 2015 and Eyjafjallajökull 2010) by comparing model predictions with satellite observations. Reasonable predictions of umbrella cloud spread are achieved using an estimated volume flow rate from the empirical equation by Bursik et al. and the observed eruption height. We show how model predictions can be refined during an ongoing eruption as further information and observations become available.

Low efficiency of large volcanic eruptions in transporting very fine ash into the atmosphere

Volcanic ash clouds are common, often unpredictable, phenomena generated during explosive eruptions. Mainly composed of very fine ash particles, they can be transported in the atmosphere at great distances from the source, having detrimental socio-economic impacts. However, proximal settling processes controlling the proportion (ε) of the very fine ash fraction distally transported in the atmosphere are still poorly understood. Yet, for the past two decades, some operational meteorological agencies have used a default value of ε = 5% as input for forecast models of atmospheric ash cloud concentration. Here we show from combined satellite and field data of sustained eruptions that ε actually varies by two orders of magnitude with respect to the mass eruption rate. Unexpectedly, we demonstrate that the most intense eruptions are in fact the least efficient (with ε = 0.1%) in transporting very fine ash through the atmosphere. This implies that the amount of very fine ash distally transported in the atmosphere is up to 50 times lower than previously anticipated. We explain this finding by the efficiency of collective particle settling in ash-rich clouds which enhance early and en masse fallout of very fine ash. This suggests that proximal sedimentation during powerful eruptions is more controlled by the concentration of ash than by the grain size. This has major consequences for decision-makers in charge of air traffic safety regulation, as well as for the understanding of proximal settling processes. Finally, we propose a new statistical model for predicting the source mass eruption rate with an unprecedentedly low level of uncertainty.

Dust mass concentrations from the UK volcanic ash lidar network compared with in-situ aircraft measurements

The Met Office has recently established a series of 10 lidar / sun-photometer installations across the UK, consolidating their ash / aerosol remote sensing capabilities [1]. In addition to this network, the Met Office have acquired the Civil Contingency Aircraft (MOCCA) which allows airborne in-situ measurements of ash / aerosol scattering and size-distributions. Two case studies are presented in which mass concentrations of Saharan dust are obtained remotely using lidar returns, and are then compared with those obtained in-situ. A thorough analysis of the mass concentration uncertainty will be provided at the conference.

Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply

Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt), causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents ^1-11 . Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research ^12-14 . We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high air-borne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum) ^10,15 , and regions with genetic similarities in related pathogen populations ^16,17 . We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as 'Ug99' ^5,6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time ³ .

Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa's largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different 'what-if' scenarios of disease outbreaks in potential source countries in different months of the wheat season.

Volcanic ash leaching as a means of tracing the environmental impact of the 2011 Grímsvötn eruption, Iceland

The Grímsvötn volcanic eruption, from 21 to 28 May, 2011, was the largest eruption of the Grímsvötn Volcanic System since 1873, with a Volcanic Explosivity Index (VEI) of magnitude 4. The main geochemical features of the potential environmental impact of the volcanic ash-water interaction were determined using two different leaching methods as proxies (batch and vertical flow-through column experiments). Ash consists of glass with minor amounts of plagioclase, clinopyroxene, diopside, olivine and iron sulphide; this latter mineral phase is very rare in juvenile ash. Ash grain morphology and size reflect the intense interaction of magma and water during eruption. Batch and column leaching tests in deionised water indicate that Na, K, Ca, Mg, Si, Cl, S and F had the highest potential geochemical fluxes to the environment. Release of various elements from volcanic ash took place immediately through dissolution of soluble salts from the ash surface. Element solubilities of Grímsvötn ash regarding bulk ash composition were <1 %. Combining the element solubilities and the total estimated mass of tephra (7.29 × 10(14) g), the total inputs of environmentally important elements were estimated to be 8.91 × 10(9) g Ca, 7.02 × 10(9) g S, 1.10 × 10(9) g Cl, 9.91 × 10(8) g Mg, 9.91 × 10(8) g Fe and 1.45 × 10(8) g P The potential environmental problems were mainly associated with the release of F (5.19 × 10(9) g).

Uncertainty analysis of a model of wind-blown volcanic plumes

Mathematical models of natural processes can be used as inversion tools to predict unobserved properties from measured quantities. Uncertainty in observations and model formulation impact on the efficacy of inverse modelling. We present a general methodology, history matching, that can be used to investigate the effect of observational and model uncertainty on inverse modelling studies. We demonstrate history matching on an integral model of volcanic plumes that is used to estimate source conditions from observations of the rise height of plumes during the eruptions of Eyjafjallajökull, Iceland, in 2010 and Grímsvötn, Iceland, in 2011. Sources of uncertainty are identified and quantified, and propagated through the integral plume model. A preliminary sensitivity analysis is performed to identify the uncertain model parameters that strongly influence model predictions. Model predictions are assessed against observations through an implausibility measure that rules out model inputs that are considered implausible given the quantified uncertainty. We demonstrate that the source mass flux at the volcano can be estimated from plume height observations, but the magmatic temperature, exit velocity and exsolved gas mass fraction cannot be accurately determined. Uncertainty in plume height observations and entrainment coefficients results in a large range of plausible values of the source mass flux. Our analysis shows that better constraints on entrainment coefficients for volcanic plumes and more precise observations of plume height are required to obtain tightly constrained estimates of the source mass flux.

Volcanic Ash versus Mineral Dust: Atmospheric Processing and Environmental and Climate Impacts

This review paper contrasts volcanic ash and mineral dust regarding their chemical and physical properties, sources, atmospheric load, deposition processes, atmospheric processing, and environmental and climate effects. Although there are substantial differences in the history of mineral dust and volcanic ash particles before they are released into the atmosphere, a number of similarities exist in atmospheric processing at ambient temperatures and environmental and climate impacts. By providing an overview on the differences and similarities between volcanic ash and mineral dust processes and effects, this review paper aims to appeal for future joint research strategies to extend our current knowledge through close cooperation between mineral dust and volcanic ash researchers.