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Atmospheric Dispersion Modellingof Volcanic Emissions
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.ORCID iD: 0000-0001-7909-0640
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Gases and particles released by volcanoes pose a serious hazard to humans and society. Emis-sions can be transported over long distances before being reduced to harmless concentrations.Knowing which areas are, or will be, exposed to volcanic emissions is an important part inreducing the impact on human health or society. In this thesis, the dispersion of volcanic emis-sions is studied using a set of atmospheric models. Two case studies have been performed, onestudying potential ash emission from future eruptions on Iceland, and a second covering SO2 emissions from Mt. Nyiragongo in D.R. Congo

The first study covers long range (∼1,000 km) dispersion of fine ash from explosive erup-tions. Three years of meteorological data are used to repeatedly simulate five eruption scenarios.The resulting concentrations of airborne ash at different times relative the onset of each eruptionis compared to current and previous threshold concentrations used by air traffic controllers. Theash hazard showed a seasonal variation, with a higher probability of efficient eastward transportin winter, compared to summer; summer eruptions pose a more persistent hazard.

In the second study, emissions of SO2 from passive degassing at Mt. Nyiragongo is studiedover a one–year period. The meteorological impact on the dispersion is studied by assigninga fixed emission source. Furthermore, flux measurements from the remote sensing data areused to improve the description of the emission source. Gases are generally transported to thenorth-west in June–August and to the south-west in December–January. A diurnal variation dueto land breeze around lake Kivu contributes to high concentrations of SO2 along the northernshore during the night. Daily averaged concentrations in the city of Goma (∼15 km SW of thesource) exceeded the European Union’s air quality standard (125 μg/m 3 ) for 120-210 days overa one year period.

Abstract [sv]

Gas- och partikelutsl ̈app fr ̊an vulkaner utg ̈or en fara för människor och för vårt samhälle. Utsläppen kan transporteras över långa avstånd innan de reduceras till ofarliga halter. Att kännatill vilka områden som utsätts, eller kommer utsättas, för utsläppen är ett viktigt verktyg för att minska påverkan påv folkhälsa och samhället. I den här avhandlingen studeras spridningen av utsläpp från vulkaner med hjälp av en uppsättning atmosfärsmodeller. Två fallstudier har utförts,en fokuserar på vulkanaska från potentiella framtida utbrott på Island, den andra studerar SO2 -ustl äpp fr ̊an Nyiragongo i Demokratiska Republiken Kongo.

Den f ̈orsta studien beskriver l ̊angv ̈aga (∼1,000 km) transport av aska från explosiva utbrott.Tre är av meteorologiska data används för att modellera spridningen från fem olika utbrotts-scenarier för varierande vädersituationer. Koncentrationen av luftburen aska studeras vid olikatidpunkter relativt utbrottens starttid och j ̈amf ̈ors med tidigare samt befintliga gränsvärden för flygtrafik. Sannolikheten för skadliga halter aska varierar med årstid, med en högre sannolikhetför effektiv transport österut under vintermånaderna, jämfört med sommarmånaderna; sommar-utbrott är istället mer benägna att orsaka långvariga problem över specifika områden.

I den andra studien modelleras utsl ̈app av SO 2 från passiva utsläpp vid Nyiragongo över en ettårsperiod. Den meteorologiska effekten på spridningen studeras genom att använda en konatant utsläppskälla. Dessutom studeras spridningen mer i detalj genom att använda fjärranalysdata för att bättre uppskatta utsläppen. Gaserna transporteras i regel mot nordväst i juni–augusti ochmot sydväst i december–februari. En sjö-/landbriscirkulation runt Kivusjön orsakar höga halterav SO2 längs sjöns norra strand nattetid. Dygnsmedelkoncentrationer av SO2 i provinshuvud-staden Goma (∼15 km sydväst om Nyiragongo) överskred EU-riktlinjer (125 μg/m3 ) under 120-210 dagar under en ettårsperiod.

Place, publisher, year, edition, pages
Uppsala universitet, 2015.
National Category
Meteorology and Atmospheric Sciences
Research subject
URN: urn:nbn:se:uu:diva-263081OAI: oai:DiVA.org:uu-263081DiVA: diva2:856803
2015-10-09, Småland Dm235, Geocentrum, Villavägen 16, Uppsala, 10:15 (English)
Available from: 2015-10-12 Created: 2015-09-25 Last updated: 2016-02-12Bibliographically approved
List of papers
1. Estimating volcanic ash hazard in European airspace
Open this publication in new window or tab >>Estimating volcanic ash hazard in European airspace
2014 (English)In: Journal of Volcanology and Geothermal Research, ISSN 0377-0273, Vol. 286, 55-66 p.Article in journal (Refereed) Published
Abstract [en]

The widespread disruption of European air traffic in late April 2010, during the eruption of Eyjafjallajökull,showed the importance of early assessment of volcanic hazard from explosive eruptions. In this study, wefocus on the short-term hazard of airborne ash from a climatological perspective, focusing on eruptions onIceland. By studying eruptions of different intensity and frequency, we estimate the overall probability that ashconcentration levels considered hazardous to aviation are exceeded over different parts of Europe.

The method involves setting up a range of eruption scenarios based on the eruptive history of Icelandic volcanoes,and repeated simulation of these scenarios for 2 years' worth of meteorological data. Simulations are conducted using meteorological data from the ERA-Interim reanalysis set, which is downscaled using the Weather Researchand Forecasting (WRF) model. The weather data are then used to drive the Lagrangian particle dispersion model FLEXPART-WRF for each of the eruption scenarios. A set of threshold values, commonly used in Volcanic Ash Advisories, are used to analyze concentration data from the dispersion model.

We see that the dispersion of ash is highly dominated by the mid-latitude westerlies and mainly affect northern UK and the Scandinavian peninsula. The occurrence of high ash levels from Icelandic volcanoes is lower over con-tinental Europe but should not be neglected for eruptions when the release rate of fine ash (<16 μm) is in theorder of 107 kg s−1 or higher.

There is a clear seasonal variation in the ash hazard. During the summer months, the dominating dispersiondirection is less distinct with some plumes extending to the northwest and Greenland. In contrast, during thewinter months, the strong westerly winds tend to transport most of the emissions eastwards. The affected area of a winter-time eruption is likely to be larger as high concentrations can be found at a further distance downwind from the volcano, effectively increasing the probability of hazardous levels of ash reaching the European continent.

The concentration thresholds for aviation, which were adopted after the Eyjafjallajökull eruption in 2010, havestrong influence on the hazard estimates for weaker eruptions but is less important for larger eruptions; thusash forecasts for weaker eruptions are likely more uncertain in comparison to larger eruptions.

Dispersion modelling, FLEXPART, Aviation safety, Climatology Hazard, Iceland
National Category
Meteorology and Atmospheric Sciences Geosciences, Multidisciplinary
urn:nbn:se:uu:diva-233386 (URN)10.1016/j.jvolgeores.2014.08.022 (DOI)000346551400006 ()
Available from: 2014-10-02 Created: 2014-10-02 Last updated: 2016-09-27Bibliographically approved
2. Seasonal and diurnal patterns in the dispersionof SO2 from Mt. Nyiragongo
Open this publication in new window or tab >>Seasonal and diurnal patterns in the dispersionof SO2 from Mt. Nyiragongo
Show others...
2016 (English)In: Atmospheric Environment, ISSN 1352-2310, E-ISSN 1873-2844, Vol. 132, 19-29 p.Article in journal (Refereed) Published
Abstract [en]

Mt. Nyiragongo is an active volcano located in the Democratic Republic of Congo, close to the border of Rwanda and about 15 km north of the city of Goma (similar to 1,000,000 inhabitants). Gases emitted from Nyiragongo might pose a persistent hazard to local inhabitants and the environment. While both ground- and satellite-based observations of the emissions exist, prior to this study, no detailed analysis of the dispersion of the emissions have been made. We have conducted a dispersion study, using a modelling system to determine the geographical distribution of SO2. A combination of a meteorological model (WRF), a Lagrangian particle dispersion model (FLEXPART-WRF) and flux data based on DOAS measurements from the NOVAC-network is used. Since observations can only be made during the day, we use random sampling of fluxes and ensemble modelling to estimate night-time emissions. Seasonal variations in the dispersion follows the migration of the Inter Tropical Convergence Zone. In June-August, the area with the highest surface concentrations is located to the northwest, and in December-February, to the southwest of the source. Diurnal variations in surface concentrations were determined by the development of the planetary boundary layer and the lake-/land breeze cycle around lake Kivu. Both processes contribute to low surface concentrations during the day and high concentrations during the night. However, the strong northerly trade winds in November-March weakened the lake breeze, contributing to higher daytime surface concentrations along the northern shore of Lake Kivu, including the city of Goma. For further analysis and measurements, it is important to include both seasonal and diurnal cycles in order to safely cover periods of high and potentially hazardous concentrations.

Dispersion modelling; Volcanic degassing; Nyiragongo; Sulfur dioxide; FLEXPART-WRF
National Category
Earth and Related Environmental Sciences Meteorology and Atmospheric Sciences
Research subject
urn:nbn:se:uu:diva-264437 (URN)10.1016/j.atmosenv.2016.02.030 (DOI)000374614500003 ()
EU, European Research Council, 18354Sida - Swedish International Development Cooperation Agency, SWE-2008-064Swedish National Infrastructure for Computing (SNIC), p2011191
Available from: 2015-10-12 Created: 2015-10-12 Last updated: 2016-09-27Bibliographically approved

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