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DispAtlas: A flexible tool for the automated construction of seasonal dispersal pathways and exposure of volcanic emissions

Alexandros Panagiotis Poulidis1, Nikos Daskalakis1, Maria Kanakidou1,2,3, Mihalis Vrekoussis1,4,5

  • Affiliations: 1Laboratory for Modeling and Observation of the Earth System (LAMOS), University of Bremen, Germany 2Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Greece 3Center of the Study of Air Quality & Climate Change (C-STACC), ICE-HT, Foundation for Research and Technology -- Hellas (FORTH), Patras, Greece 4Center of Marine Environmental Sciences (MARUM), University of Bremen, Germany 5Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Cyprus 

  • Presentation type: Poster

  • Presentation time: Tuesday 16:30 - 18:30, Room Poster Hall

  • Poster Board Number: 65

  • Programme No: 6.3.24

  • Theme 6 > Session 3

Abstract

The significant impact of volcanic emissions on atmospheric composition and climate has highlighted the need for comprehensive monitoring of volcanic emissions from active volcanoes worldwide. Protection of human health requires better knowledge of local and regional characteristics of volcanic plume dispersal. This study addresses the issue of transport dynamics of volcanic emissions by developing an automated algorithm to study the seasonality of common dispersal pathways from major degassing volcanoes; here applied to volcanoes covered by the NOVAC (Network for Observation of Volcanic and Atmospheric Change) network, as captured in the CAMS Volcano database. For each volcano, ERA5 reanalysis data were used to drive the FLEXPART lagrangian transport model to simulate the dispersion of volcanic plumes from passive degassing. A quasi-realistic reduction of volcanic emissions amounts in the FLEXPART model was achieved by applying an exponential first order decay, based on representative lifetime calculations accounting for both gas-phase oxidation and deposition processes. Pathways were identified using the k-means clustering algorithm, which led to robust groupings that reflect climatological and topographic phenomena and exhibit strong seasonality. Finally, the potential exposure to volcanic emissions was estimated using population density data from the Global Human Settlement Layer (GHSL). While this study focuses on NOVAC network volcanoes, the methodology can easily be extended to additional volcanic systems and can be used to carry out hypothetical studies to aid in hazard assessment and emergency response planning for regions with significant volcanic activity.