The 2014–2015 Bárðarbunga‐Veiðivötn fissure eruption at Holuhraun produced about 1.5 km3 of lava, making it the largest eruption in Iceland in more than 200 years. Over the course of the eruption, ...daily volcanic sulfur dioxide (SO2) emissions exceeded daily SO2 emissions from all anthropogenic sources in Europe in 2010 by at least a factor of 3. We present surface air quality observations from across Northern Europe together with satellite remote sensing data and model simulations of volcanic SO2 for September 2014. We show that volcanic SO2 was transported in the lowermost troposphere over long distances and detected by air quality monitoring stations up to 2750 km away from the source. Using retrievals from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), we calculate an average daily SO2 mass burden of 99 ± 49 kilotons (kt) of SO2 from OMI and 61 ± 18 kt of SO2 from IASI for September 2014. This volcanic burden is at least a factor of 2 greater than the average SO2 mass burden between 2007 and 2009 due to anthropogenic emissions from the whole of Europe. Combining the observational data with model simulations using the United Kingdom Met Office's Numerical Atmospheric‐dispersion Modelling Environment model, we are able to constrain SO2 emission rates to up to 120 kilotons per day (kt/d) during early September 2014, followed by a decrease to 20–60 kt/d between 6 and 22 September 2014, followed by a renewed increase to 60–120 kt/d until the end of September 2014. Based on these fluxes, we estimate that the eruption emitted a total of 2.0 ± 0.6 Tg of SO2 during September 2014, in good agreement with ground‐based remote sensing and petrological estimates. Although satellite‐derived and model‐simulated vertical column densities of SO2 agree well, the model simulations are biased low by up to a factor of 8 when compared to surface observations of volcanic SO2 on 6–7 September 2014 in Ireland. These biases are mainly due to relatively small horizontal and vertical positional errors in the simulations of the volcanic plume occurring over transport distances of thousands of kilometers. Although the volcanic air pollution episodes were transient and lava‐dominated volcanic eruptions are sporadic events, the observations suggest that (i) during an eruption, volcanic SO2 measurements should be assimilated for near real‐time air quality forecasting and (ii) existing air quality monitoring networks should be retained or extended to monitor SO2 and other volcanic pollutants.
Key Points
The 2014–2015 Icelandic fissure eruption at Bárðarbunga affected air quality in far field
Satellite‐derived average daily SO2 burden of 99 ± 49 kt (OMI) and 61 ± 18 kt (IASI) in September 2014
We calculate a total release of 2.0 ± 0.6 Tg of SO2 for September 2014 and fluxes up to 120 kt/d
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The 2014-15 Holuhraun eruption in Iceland was the largest fissure eruption in over 200 years, emitting prodigious amounts of gas and particulate matter into the troposphere. Reykjavík, the capital ...area of Iceland (250 km from eruption site) was exposed to air pollution events from advection of (i) a relatively young and chemically primitive volcanic plume with a high sulphur dioxide gas (SO
) to sulphate PM (SO
) ratio, and (ii) an older and chemically mature volcanic plume with a low SO
/SO
ratio. Whereas the advection and air pollution caused by the primitive plume were successfully forecast and forewarned in public advisories, the mature plume was not. Here, we show that exposure to the mature plume is associated with an increase in register-measured health care utilisation for respiratory disease by 23% (95% CI 19.7-27.4%) and for asthma medication dispensing by 19.3% (95% CI 9.6-29.1%). Absence of public advisories is associated with increases in visits to primary care medical doctors and to the hospital emergency department. We recommend that operational response to volcanic air pollution considers both primitive and mature types of plumes.
Unrest began in July 2021 at Askja volcano in the Northern Volcanic Zone (NVZ) of Iceland. Its most recent eruption, in 1961, was predominantly effusive and produced ∼0.1 km3 lava field. The last ...plinian eruption at Askja occurred in 1875. Geodetic measurements between 1983 and 2021 detail subsidence of Askja, decaying in an exponential manner. At the end of July 2021, inflation was detected at Askja volcano, from GNSS observations and Sentinel‐1 interferograms. The inflationary episode can be divided into two periods from the onset of inflation until September 2023. An initial period until 20 September 2021 when geodetic models suggest transfer of magma (or magmatic fluids) from within the shallowest part of the magmatic system (comprising an inflating and deflating source), potentially involving silicic magma. A following period when one source of pressure increase at shallow depth can explain the observations.
Plain Language Summary
Askja volcano, situated in the Northern Volcanic Zone in Iceland, has been quiet since its last eruption in 1961, with surface deformation measurements from 1983 to 2021 displaying a decaying subsidence signal within the Askja caldera. However, at the end of July 2021, the volcano began to inflate. This was detected on both GNSS and satellite observations. As of September 2023, ∼65 cm of uplift had been measured at GNSS station OLAC. Modeling of surface deformation measurements indicates that the inflation was triggered by upward migration of melt (or magmatic fluids).
Key Points
At the end of July 2021, Askja volcano began to inflate—detected on both GNSS and satellite observations, ending 1983–2021 subsidence
Geodetic modeling indicates upward migration of magma, feeding a magma body at an inferred depth of 2.5–3.1 km under the main Askja caldera
Start of unrest was associated with magma transfer within the upper part of the system, followed by possible additional influx from depth
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The Holuhraun fissure eruption (Iceland) in 2014–2015, which originated from the Bárðarbunga volcanic system, was exceptional in several respects. It lasted 6 months and, throughout its duration, it ...released up to 9.6 Mt of SO
2
in the atmosphere. The main recorded hazard affecting the entire country over the 6 months was the constant presence of a low-level gas cloud that led to recurrent air pollution episodes. The Icelandic Meteorological Office responded to this human health hazard by (1) setting up a forecasting system to anticipate the distribution of SO
2
over Iceland and (2) preparing probabilistic hazard maps to support the decisions taken by the Icelandic Civil Protection in demarcating the accessible area around the eruption site. This paper introduces some technical aspects of the application of the CALPUFF numerical model to this eruption like the SO
2
dispersal forecasting setup, the volcanic source numerical description, and the Monte Carlo procedure adopted for the creation of the probabilistic hazard maps. CALPUFF-based maps were created in January 2015, when the eruption was still ongoing, with the assumption that the eruption would be continuing with the same intensity. Maps for the entire country and for a smaller domain were produced, the latter showing the likelihood to exceeding an hourly concentration of 2600 μg/m
3
(1 ppm) of SO
2
for the spring season, a level chosen by the Icelandic Civil Protection for the delineation of the area of restricted access around the eruption site. As during the eruption there was no time for a rigorous evaluation of the model accuracy, we then undertook a retrospective analysis of CALPUFF model performance comparing the forecasted hourly SO
2
concentration with real-time measurements at key-sites. The model did reproduce the hourly observations (the maximum within a 24-running window) with a level of agreement of 50.6% in Mývatn (85 km from the eruption site) and 50.4% in Reykjavík (258 km), when instances of null pairs have been removed. In Mývatn, the model overestimated the concentration more than 22% of the time. In Höfn (104 km), the model accuracy is 81.7% and occurrences of underestimation are higher than 11% of the time. In Reyðarfjörður (at 124 km), the model accuracy is assessed to be 82.7% and the model overestimates occurring 15.1% of the time. Possible explanations for the observed mismatch between model results and measurements include the spatial resolution of meteorological data field, the capability into reproducing chemical reactions of SO
2
in atmosphere, and the reduced extension of the numerical domain. In addition, the model performance is strongly dependent on the source descriptors (e.g., strength of the SO
2
flux and injection height) that, in this contribution, have been kept constant over long periods—neglecting, in this way, the natural variability of a dynamic emission of SO
2
. This consideration points toward the need of frequent and high-quality observation data for the initialization of dispersal numerical model. In light of this retrospective analysis, the probabilistic hazard maps possibly over-estimated the area exposed to high level of SO
2
concentration. All the same, this paper reports on how quantitative probabilistic hazard mapping can be used for mitigating the health risk of volcanic SO
2
emissions during a volcanic crisis to the benefit of operational hazard monitoring in support an effective crisis response.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Volcano observatories (VOs) around the world are required to maintain surveillance of their volcanoes and inform civil protection and aviation authorities about impending eruptions. They often work ...through consolidated procedures to respond to volcanic crises in a timely manner and provide a service to the community aimed at reducing the potential impact of an eruption. Within the International Airways Volcano Watch (IAVW) framework of the International Civil Aviation Organisation (ICAO), designated State Volcano Observatories (SVOs) are asked to operate a colour coded system designed to inform the aviation community about the status of a volcano and the expected threats associated. Despite the IAVW documentation defining the different colour-coded levels, operating the aviation colour code in a standardised way is not easy, as sometimes, different SVOs adopt different strategies on how, when, and why to change it. Following two European VOs and Volcanic Ash Advisory Centres (VAACs) workshops, the European VOs agreed to present an overview on how they operate the aviation colour code. The comparative analysis presented here reveals that not all VOs in Europe use this system as part of their operational response, mainly because of a lack of volcanic eruptions since the aviation colour code was officially established, or the absence of a formal designation as an SVO. We also note that the VOs that do regularly use aviation colour code operate it differently depending on the frequency and styles of eruptions, the historical eruptive activity, the nature of the unrest, the monitoring level, institutional norms, previous experiences, and on the agreement they may have with the local Air Transport Navigation providers. This study shows that even though the aviation colour code system was designed to provide a standard, its usage strongly depends on the institutional subjectivity in responding to volcano emergencies. Some common questions have been identified across the different (S)VOs that will need to be addressed by ICAO to have a more harmonised approach and usage of the aviation colour code.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
MIROVA (Middle Infrared Observation of Volcanic Activity) is an automatic volcano hot spot detection system, based on the analysis of MODIS data (Moderate Resolution Imaging Spectroradiometer). The ...system is able to detect, locate and quantify thermal anomalies in near real-time, by providing, on a dedicated website (www.mirovaweb.it), infrared images and thermal flux time-series on over 200 volcanoes worldwide. Thanks to its simple interface and intuitive representation of the data, MIROVA is currently used by several volcano observatories for daily monitoring activities and reporting. In this paper, we present the architecture of the system and its use for operational volcano monitoring and research. Particular emphasis will be given to the contribution that the thermal data has provided in order to detect volcanic unrest, to forecast eruptions and to depict trends and patterns during eruptive crisis. The current limits and requirements to improve the quality of the data, their distribution and interpretation are also discussed, in the light of the experience gained in recent years within the volcanological community. The results presented clearly demonstrate how the open access of satellite data and the sharing of derived products allow a better understanding of ongoing volcanic phenomena, and therefore constitute an essential requirement for the assessment of volcanic hazards.
For active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- and long-term emergency plans, for which ...probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth;
www.cheese-coe.eu
), an effort was made to generate exascale-suitable codes and workflows to collect and process in some hours the large amount of data that a quality PVHA requires. To this end, we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop PVHA for a volcano. This tool uses the Bayesian event tree methodology to calculate eruption probabilities, vent-opening location(s), and eruptive source parameters (ESPs) based on volcano history, monitoring system data, and meteorological conditions. Then, the tool interacts with the chosen hazard model, performing a simulation for each ESP set or volcanic scenario (VS). Finally, the resulting information is processed by proof-of-concept-subjected high-performance data analytics (HPDA) scripts, producing the hazard maps which describe the probability over time of exceeding critical thresholds at each location in the investigated geographical domain. Although PVHA_HPC-WF can be adapted to other hazards, we focus here on tephra (i.e., lapilli and ash) transport and deposition. As an application, we performed PVHA for Campi Flegrei (CF), Italy, an active volcano located in one of the most densely inhabited areas in Europe and under busy air traffic routes. CF is currently in unrest, classified as being in an attention level by the Italian Civil Protection. We consider an approximate 2,000 × 2,000 × 40 km computational domain with 2 km grid resolution in the horizontal and 40 vertical levels, centered in CF. To explore the natural variability and uncertainty of the eruptive conditions, we consider a large number of VSs allowing us to include those of low probability but high impact, and simulations of tephra dispersal are performed for each of them using the FALL3D model. Results show the potential of HPC to timely execute a vast range of simulations of complex numerical models in large high-resolution computational domains and analyze great volumes of data to obtain quality hazard maps.
The Icelandic Meteorological Office maintains a national network of webcams designed and built in house for environmental monitoring. During the 2021 Fagradalsfjall eruption these cameras, along with ...a temporary near-field network of commercial cameras installed by the Department of Civil Protection and Emergency Management, were used to estimate the height of the
S
O
2
plume and lava fountain. Here we present the webcam designs, the techniques used to calibrate them, and the messaging system and web interface that allow near real time measurements to be made from the images. With this system we were able to make estimates of heights with an accuracy on the order of tens to a few hundreds of meters with a lag typically of five to ten minutes at up to ten minute intervals when weather conditions were favorable. The plume heights were then used to constrain the performance of the
S
O
2
dispersion model used for air quality forecasts while fountain heights were used to delineate danger zones where visitors at the eruption site were in danger of being hit by ballistic clasts.
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