Rapid emergency assessment of ash and gas hazard for future eruptions at Santorini Volcano, Greece

Hazard assessments for long-dormant volcanoes, where information is rarely available, typically have to be made rapidly and in the face of considerable uncertainty and often poor information. A conditional (assuming an eruption), scenario-based probabilistic approach to such an assessment is presented here for Santorini volcano (Greece). The rapid assessment was developed and implemented in response to the 2011-2012 unrest crisis in order to inform emergency management and planning. This paper synthesises the results presented to the Greek National Committee and scientific community involved. Two plausible eruptions at Santorini were investigated, using multiple inputs and dispersal models, based on observations of historic eruptions and expert judgement. For ash hazard, a 'most likely' eruption scenario was developed, characterised by slow lava extrusion over periods of one to two years with weak but persistent explosions and ash venting up to 3 km. A second 'largest considered' sub-Plinian explosive scenario assumed a 12 km high column of 4-h duration. For gas hazard, constant fluxes of 200 and 800 tons/day SO2 were assumed for the duration of the eruption scenarios, noting that there is very little evidence to constrain SO2 flux from Santorini eruptions. Statistical models of likely wind conditions with height and season were developed from decadal reanalysis time series showing that consistent low-altitude winds were rarely maintained for more than a few days. Stochastic models of ash (TEPHRA2, VOL-CALPUFF) and gas (AERMOD) dispersal provided outputs in the form of probability maps and exceedance probability curves for key loading and concentration thresholds at important locations on the island. The results from the rapid assessments presented in this paper confirm that ash and gas hazard is likely to be of concern if an eruption of Santorini occurs. Higher hazard may be expected to the south and east of the volcano, notably at important tourist and transport hubs. Low hazard to the north and northwest suggests that these may be suitable locations for emergency response centres and emergency critical infrastructure. This approach may provide a blueprint for rapid ash and gas assessment for other long-dormant volcanoes and we provide suggestions for refining the methods used.</p

Composition of continental crust altered by the emergence of land plants

Acknowledgements This paper benefited greatly from discussions with B. Keller. C.J.S., X.W. and M.S. were supported by the Natural Sciences and Environment Research Council, Discovery Grant RGPIN-2020-05639. T.R.I.M. was supported by the Natural Sciences and Environment Research Council, Undergraduate Student Research Award 551207 – 2020 with additional funding provided by L. Godin. T.M.G. and T.H. were supported by the Turing Institute under the EPSRC grant EP/N510129/1. N.S.D. and W.J.M. were supported by NERC grant NE/T00696X. G.-M.L. acknowledges support from the State Scholarship Fund of China Scholarship Council (202006410023).Peer reviewedPostprin

Transient mobilization of subcrustal carbon coincident with Palaeocene–Eocene Thermal Maximum

Plume magmatism and continental breakup led to the opening of the northeast Atlantic Ocean during the globally warm early Cenozoic. This warmth culminated in a transient (170 thousand year, kyr) hyperthermal event associated with a large, if poorly constrained, emission of carbon called the Palaeocene–Eocene Thermal Maximum (PETM) 56 million years ago (Ma). Methane from hydrothermal vents in the coeval North Atlantic Igneous Province (NAIP) has been proposed as the trigger, though isotopic constraints from deep sea sediments have instead implicated direct volcanic carbon dioxide (CO2) emissions. Here we calculate that background levels of volcanic outgassing from mid-ocean ridges and large igneous provinces yield only one-fifth of the carbon required to trigger the hyperthermal. However, geochemical analyses of volcanic sequences spanning the rift-to-drift phase of the NAIP indicate a sudden ~220 kyr-long intensification of magmatic activity coincident with the PETM. This was likely driven by thinning and enhanced decompression melting of the sub-continental lithospheric mantle, which critically contained a high proportion of carbon-rich metasomatic carbonates. Melting models and coupled tectonic–geochemical simulations indicate that >104 gigatons of subcrustal carbon was mobilized into the ocean and atmosphere sufficiently rapidly to explain the scale and pace of the PETM

Probabilistic volcanic hazard and risk assessment

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Application of Bayes Network analysis to RWGD siting: expert estimation of geological barrier effects due to climate change

This chapter presents the main methods and findings of a pilot study to demonstrate potential applications for Bayes Networks (BNs) in the management of uncertainty in the long-term safety case for a radioactive waste geological repository. The study, carried out with experts from the Radioactive Waste Management Directorate of NDA, demonstrates a method for determining uncertainty distributions for a probabilistic analysis of potential effects on geological barriers due to climate-driven changes in related processes and factors. Two complementary, decision support approaches are applied: (1) the Classical Model for expert judgment elicitation (introduced in Chapter 20) provides a structured basis for eliciting and aggregating expert judgments in a formal and auditable way and (2) a graphical Bayes Network is employed to assess the evidential worth of uncertain data, including expert judgments.The BN was constructed by performing a systematic review of the key features, events, and processes relating specifically to the single issue of the extent to which climate change could affect biosphere radiological risks due to a release from a repository; in this exploratory exercise, the approach was applied to four different climate change scenarios over the next 1 million years. Although the model developed for this pilot study was necessarily highly simplified and considers a limited number of alternative climate scenarios, it demonstrates a methodology for identifying states and scenarios not currently captured by the reference case model in the post-closure performance assessment that could lead to significant increases in risk and/or uncertainty. An important outcome is the ability to evaluate relative changes in key risk factors, compared to a defined base climate scenario with a known level of risk

Oklahoma’s induced seismicity strongly linked to wastewater injection depth

The dramatic rise in Oklahoma seismicity since 2009 is due to wastewater injection. The role of injection depth is an open, complex issue, yet critical for hazard assessment and regulation. We developed an advanced Bayesian Network to model joint conditional dependencies between spatial, operational, and seismicity parameters. We found injection depth relative to crystalline basement most strongly correlates with seismic moment release. The joint effects of depth and volume are critical, as injection rate becomes more influential near the basement interface. Restricting injection depths to 200–500 m above basement could reduce annual seismic moment release by a factor of 1.4–2.8. Our approach enables identification of sub-regions where targeted regulation may mitigate effects of induced earthquakes, aiding operators and regulators in wastewater disposal regions

Application of Bayes Network analysis to RWGD siting: expert estimation of geological barrier effects due to climate change

This chapter presents the main methods and findings of a pilot study to demonstrate potential applications for Bayes Networks (BNs) in the management of uncertainty in the long-term safety case for a radioactive waste geological repository. The study, carried out with experts from the Radioactive Waste Management Directorate of NDA, demonstrates a method for determining uncertainty distributions for a probabilistic analysis of potential effects on geological barriers due to climate-driven changes in related processes and factors. Two complementary, decision support approaches are applied: (1) the Classical Model for expert judgment elicitation (introduced in Chapter 20) provides a structured basis for eliciting and aggregating expert judgments in a formal and auditable way and (2) a graphical Bayes Network is employed to assess the evidential worth of uncertain data, including expert judgments.The BN was constructed by performing a systematic review of the key features, events, and processes relating specifically to the single issue of the extent to which climate change could affect biosphere radiological risks due to a release from a repository; in this exploratory exercise, the approach was applied to four different climate change scenarios over the next 1 million years. Although the model developed for this pilot study was necessarily highly simplified and considers a limited number of alternative climate scenarios, it demonstrates a methodology for identifying states and scenarios not currently captured by the reference case model in the post-closure performance assessment that could lead to significant increases in risk and/or uncertainty. An important outcome is the ability to evaluate relative changes in key risk factors, compared to a defined base climate scenario with a known level of risk