Dataset Information

Short-term detection of volcanic unrest at Mt. Etna by means of a multi-station warning system.

ABSTRACT: Early-warning assessment of a volcanic unrest requires that accurate information from monitoring is continuously gathered before volcanic activity starts. Seismic data are an optimal source of such information, overcoming safety problems due to dangerous conditions for field surveys or cloud cover that may hinder visibility. We designed a multi-station warning system based on the classification of patterns of the background seismic radiation, so-called volcanic tremor, by using Self-Organizing Maps (SOM) and fuzzy clustering. The classifier automatically detects patterns that are typical footprints of volcanic unrest. The issuance of the SOM colors on DEM allows their geographical visualization according to the stations of detection; this spatial location makes it possible to infer areas potentially impacted by eruptive phenomena. Tested at Mt. Etna (Italy), the classifier forecasted in hindsight patterns associated with fast-rising magma (typical of lava fountains) as well as a relatively long lead time of the outburst (lava flows from eruptive fractures). Receiver Operating Characteristics (ROC) curves gave an Area Under the Curve (AUC) ∼0.8 indicative of a good detection accuracy that cannot be achieved from a mere random choice.

SUBMITTER: Spampinato S

PROVIDER: S-EPMC6482307 | biostudies-other | 2019 Apr

REPOSITORIES: biostudies-other

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Short-term detection of volcanic unrest at Mt. Etna by means of a multi-station warning system.

Spampinato Salvatore S Langer Horst H Messina Alfio A Falsaperla Susanna S

Scientific reports 20190424 1

Early-warning assessment of a volcanic unrest requires that accurate information from monitoring is continuously gathered before volcanic activity starts. Seismic data are an optimal source of such information, overcoming safety problems due to dangerous conditions for field surveys or cloud cover that may hinder visibility. We designed a multi-station warning system based on the classification of patterns of the background seismic radiation, so-called volcanic tremor, by using Self-Organizing M ...[more]

PMID: 31019208

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Project description:Inhalation of ash can be of great concern for affected communities, during and after volcanic eruptions. Governmental and humanitarian agencies recommend and distribute a variety of respiratory protection (RP), commonly surgical masks but, also, industry-certified N95-style masks. However, there is currently no evidence on how wearable they are within affected populations or how protective wearers perceive them being against volcanic ash (which will influence the likelihood of uptake of recommended interventions). Volunteers living near Mt. Sinabung, Sumatra, Indonesia, participated in a field wearability study, which included a high-efficiency mask certified to industry standards (N95-equiv.); a standard, pleated surgical mask (Surgical); a Basic flat-fold mask (Flat-fold), and the surgical mask plus a scarf tied over the top (Surgical Plus) to improve fit. These types of RP had all performed well during earlier laboratory filtration efficiency tests. The N95-equiv. mask had performed significantly better than the other RP in the subsequent total inward leakage volunteer trials, whilst the Flat-fold and Surgical masks performed poorly, letting in a third of PM2.5 particles (data published elsewhere). Thirty volunteers wore each mask for a 15-min walk before being asked to rate the comfort, breathability and perceived protection and fit of each. After wearing all of the masks, volunteers compared and identified their preferred type of protection. The feedback received from the volunteers suggested that the Surgical Plus and N95-equiv. masks were rated as being significantly hotter and more humid than other masks. The Flat-fold was rated to have better breathability than the other masks. The N95-equiv. mask was ranked as providing the best level of effectiveness of the four masks tested. Ultimately, when asked which type of mask they would choose to wear during ashfall, 33% selected the Flat-fold mask due to its comfort and simplicity, with the Surgical Plus being the least likely to be chosen of the four tested. The study findings are of benefit to agencies who need to make informed decisions on the procurement and distribution of RP for use by those affected in future eruptions and the provision of advice to communities on their usage.

Dataset Information

Short-term detection of volcanic unrest at Mt. Etna by means of a multi-station warning system.

Publications

Short-term detection of volcanic unrest at Mt. Etna by means of a multi-station warning system.

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