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David Jessop

Publications and source records attributed to David Jessop.

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Post-traumatic stress disorder in adult population of La Palma (Spain) after the 2021 Tajogaite eruption: Environmental and sociodemographic predictors

The adverse mental health effects of exposure to disasters have long been recognized, with earthquakes, floods, tsunamis, and volcanoes (among others) contributing to anxiety, depression, and post-traumatic stress disorder (PTSD). Concerning PTSD and volcanic eruptions specifically, most studies have highlighted risk factors related to demographic and social factors (e.g., gender, age, and education), mental health, and those associated with the experience of the volcanic eruption (e.g., having evacuated). Establishing the demographic scope of those more likely to suffer PTSD following volcanic eruptions as well as understanding the aggravating factors is key to best tailor precautionary measurements and psychological interventions. In this study, we supplement these analyses by investigating the role of environmental contaminants (specifically, exposure to tephra falls and degraded air quality) together with demographic, health, and hazard experiences in contributing to PTSD. We focus on data collected after the 2021 eruption of the Tajogaite volcano (Cumbre Vieja, La Palma, Spain). Our results show that in addition to sex, education, distance from the volcano, evacuation status, health issues related to the eruption, and mental health antecedents, exposure to volcanic gas but not tephra is associated with higher PTSD scores. Our findings establish a picture of the prevalence of PTSD symptoms in various demographics groups and aggravating factors following the 2021 eruption of the Tajogaite volcano. We further call for an extended investigation (and potentially, ultimately, a mechanistic explanation) of the role of air quality (as a potential synergic hazard) in shaping mental health following exposure to a primary hazard, such as a volcanic eruption.

Canary Islands, Island of La Palma

The Independent Volcanic Eruption Source Parameter Archive (IVESPA, version 1.0): A new observational database to support explosive eruptive column model validation and development

Eruptive column models are powerful tools for investigating the transport of volcanic gas and ash, reconstructing past explosive eruptions, and simulating future hazards. However, the evaluation of these models is challenging as it requires independent estimates of the main model inputs (e.g. mass eruption rate) and outputs (e.g. column height). There exists no database of independently estimated eruption source parameters (ESPs) that is extensive, standardized, maintained, and consensus-based. This paper introduces the Independent Volcanic Eruption Source Parameter Archive (IVESPA, ivespa.co.uk), a community effort endorsed by the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) Commission on Tephra Hazard Modelling. We compiled data for 134 explosive eruptive events, spanning the 1902-2016 period, with independent estimates of: i) total erupted mass of fall deposits; ii) duration; iii) eruption column height; and iv) atmospheric conditions. Crucially, we distinguish plume top versus umbrella spreading height, and the height of ash versus sulphur dioxide injection. All parameter values provided have been vetted independently by at least two experts. Uncertainties are quantified systematically, including flags to describe the degree of interpretation of the literature required for each estimate. IVESPA also includes a range of additional parameters such as total grain size distribution, eruption style, morphology of the plume (weak versus strong), and mass contribution from pyroclastic density currents, where available. We discuss the future developments and potential applications of IVESPA and make recommendations for reporting ESPs to maximize their usability across different applications. IVESPA covers an unprecedented range of ESPs and can therefore be used to evaluate and develop eruptive column models across a wide range of conditions using a standardized dataset.

Journal of Volcanology and Geothermal Research