Lava Volume from Remote Sensing Data: Comparisons with Reverse Petrological Approaches for Two Types of Effusive Eruption
Artikel i vetenskaplig tidskrift, 2022

Five effusive eruptions of Piton de la Fournaise (La Réunion) are analyzed to investigate temporal trends of erupted mass and sulfur dioxide (SO2) emissions. Daily SO2 emissions are acquired from three ultraviolet (UV) satellite instruments (the Ozone Monitoring Instrument (OMI), the Ozone Mapping and Profiler Suite (OMPS), and the Tropospheric Monitoring Instrument (TROPOMI)) and an array of ground-based UV spectrometers (Network for Observation of Volcanic and Atmospheric Change (NOVAC)). Time-averaged lava discharge rates (TADRs) are obtained from two automatic satellite-based hot spot detection systems: MIROVA and MODVOLC. Assuming that the lava volumes measured in the field are accurate, the MIROVA system gave the best estimation of erupted volume among the methods investigated. We use a reverse petrological method to constrain pre-eruptive magmatic sulfur contents based on observed SO2 emissions and lava volumes. We also show that a direct petrological approach using SO2 data might be a viable alternative for TADR estimation during cloudy weather that compromises hot spot detection. In several eruptions we observed a terminal increase in TADR and SO2 emissions after initial emission of evolved degassed magma. We ascribe this to input of deeper, volatile-rich magma into the plumbing system towards the end of these eruptions. Furthermore, we find no evidence of volatile excess in the five eruptions studied, which were thus mostly fed by shallow degassed magma.


Effusion rate



Plumbing system

Sulfur dioxide

Piton de la Fournaise


Scanning DOAS


Pauline Verdurme

Université Clermont Auvergne

Simon Carn

Michigan Technological University

Andrew J.L. Harris

Université Clermont Auvergne

D. Coppola

Universita degli Studi di Torino

A. Di Muro

Institut de Physique du Globe de Paris

Université Paris Descartes

Santiago Arellano

Chalmers, Rymd-, geo- och miljövetenskap, Geovetenskap och fjärranalys

L. Gurioli

Université Clermont Auvergne

Remote Sensing

2072-4292 (ISSN)

Vol. 14 2 323






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