Presentation of findings

Paper I: Steensen, B. M., Schulz, M., Theys, N., and Fagerli, H.: A model study of the pollution

effects of the first 3 months of the Holuhraun volcanic fissure: comparison with observations and air pollution effects, Atmos. Chem. Phys., 16, 9745-9760, doi:10.5194/acp-16-9745-2016, 2016.

This paper studies the impact of the first three months of the 2014-2015 Holuhraun volcanic fissure.

The eruption produced a total lava field of 85 km

²

over the Holuhraun plain (Pedersen et al., 2017) and released around 11 (±5) Tg of SO

2

(Gíslason et al., 2015). The daily emissions from the lava field were 4.5 times the daily anthropogenic emission from the 28 European Union countries, which for 2009 is estimated to be 13.9 kt d

^-1

(Kuenen et al., 2014; Schmidt et al., 2015). This is also the anthropogenic emission estimate used in this paper.

The main purpose of the study is to investigate the increase in pollution levels over Europe due to the eruption on the Holuhraun plain, by using the eEMEP model set up with chemistry and anthropogenic emissions. The model simulations are initiated with a constant emission estimate of 65 kt d

^-1

released for sensitivity testing in three different heights. Model results are compared to OMI satellite retrievals over the first two months (September and October 2014), to observations of SO

2

and PM

2.5

concentrations over three episodes when the volcanic emissions were transported to surface stations in Europe, as well as to observations of SO

X

wet deposition. For the satellite observation comparison, an averaging kernel is applied to the model data to correct for the height dependent sensitivity of the satellite UV detection of SO

2

. The base model simulations with emissions released from the ground up to 3 km match better with satellite retrievals than the other two model simulations with emissions released lower or higher in the atmosphere (0-1 km and 3-5 km). The comparison at ground stations shows that at times there are large discrepancies between the peak concentrations of model and observed concentrations. The timing of the peaks in concentration level is however good, and for most of the stations the model simulation with volcanic SO

2

released into a 0-3 km column height matches best with the observations. Both Schmidt et al. (2015) and Boichu et al. (2016) studied the Holuhraun eruption by use of dispersion model simulations in both Lagrangian and Eulerian modeling frames and found that there is too little exchange of pollutants to the PBL. The model surface concentrations of SO

2

are therefore too low for stations in the United Kingdom, Ireland and France in September 2014 explaining some of the discrepancies found here in Paper I.

Even though surface concentration stations measured higher-than-normal concentrations, exceedances of SO

2

concentrations were only measured frequently during the period on Iceland (Gíslason et al., 2015). Iceland is also found to be the region which is most sensitive to variations in emission height.

PM exceedances are calculated for Europe using a threshold of a 24 hour average for PM

2.5

concentration of 25 µg m

^-3

(WHO, 2005). By using the model calculations, the result shows that the

34

Barðarbunga eruption increased the number of PM exceedance days by up to two days over the three months studied for the already polluted Benelux region. Only one exceedance day due to the volcanic eruption were found by studying model calculations over Iceland, and none at the coast of Norway, even though these two regions experienced the largest percentage increase in PM concentrations. The model results also show high relative and absolute increases of SO

X

deposition over the coast of Northern Norway and Northern Scotland. These regions are under normal conditions among the least polluted regions over Europe, and the increase in pollution due to the Holuhraun volcanic fissure increased the SO

X

deposition levels to values similar to the most polluted regions in Europe. Overall the model results and observations show that Barðarbunga eruption had little effect on the average sulfur concentration levels in Europe outside Iceland over the three months, with only short periods exhibiting high concentrations.

Paper II: Steensen, B. M., Schulz, M., Wind, P., Valdebenito, Á., and Fagerli, H.: The operational

eEMEP model for volcanic SO

2

and ash forecasting, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-315, in review, 2017.

This paper presents the additions and developments for the EMEP MSC-W model to improve the transport calculations of volcanic emissions and especially ash in the model. To include volcanic emission from explosive eruptions with a high plume the model top is increased from the standard 16 km to a more flexible height based on the vertical levels available in the meteorological data driving the model. By increasing the number of vertical levels the resolution is also improved. Gravitational settling for ash tracers is newly included and added to all model layers. The operational set up of the model is presented.

An efficient dispersion model for forecasting volcanic emissions needs to balance both the complexity of the model and a sufficient high resolution. The inherent numerical diffusion in Eulerian models caused by the instant mixing of tracers within a grid box is studied to see the importance of resolution for simulations where peak concentrations need to be predicted for ash advisory decision making.

Dispersion forecasts are initiated over three days at the beginning of the 2014 Holuhraun fissure eruption, driven by ensemble meteorology members on three different horizontal resolutions.

Ensemble meteorology consists of forecast simulations with several members that have differences caused by small changes in the initial conditions and different physical model descriptions. The goal of ensemble forecasts is to quantify the uncertainty of the forecast and to produce probability forecasts for certain events based on the occurrence of the events in the different members. Frequency change over the thresholds dependent on the different resolutions is therefore studied.

High resolution dispersion simulations have members with high concentrations further into the

forecast and also a larger spread between the members. Forecast simulations with the lowest resolution

35

show more agreement and therefore gain little from ensemble forecasting. High resolution also matches slightly better with observations, but have a much higher computational cost. Less information is found to be lost between the high and mid resolution than between the mid and low model resolution, and therefore the mid resolution setup (20x20km) is found to be sufficient when it is critical to obtain results in time. To perform an even quicker forecast of dispersion from volcanic eruptions, where peak concentration calculations are not crucial, a low resolution is found to be sufficient.

To study the effect of gravitational settling in the calculations, two model simulations with and without gravitational settling of ash particles are compared to lidar observations of the ash layer over central European stations during the 2010 Eyjafjollajökull eruption (Pappalardo et al., 2013). The model simulations use the same emission estimate from Stohl et al. (2011) and the same meteorology.

Gravitational settling causes the center of mass to be about 1 km closer to the ground than the model simulation with no gravitational settling included. However, the descending layer caused by a high pressure system over Europe in the studied time interval has a larger effect. The height variations of the ash layer caused by real weather situations are not captured perfectly well by either of the two simulations, playing down the role of gravitation parameterization imperfections. The eEMEP model result of ash center of mass calculated with gravitational settling show higher correlation with those from the lidar observations compared to the results from the model simulation with no gravitational settling at four of the six stations studied used in the study. Although a physical correct model

description of volcanic ash and SO

2

dispersion is advantageous, other factors such as model resolution, details of the source term and the model setup, whether it includes assimilation or not, are evaluated as more important for safety assessments.

Paper III: Steensen, B. M., Kylling, A., Kristiansen, N. I., and Schulz, M.: Uncertainty assessment

and applicability of an inversion method for volcanic ash forecasting, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-1075, in review, 2017.

This paper presents the applicability of an inversion method to find an optimized source term to

forecast ash dispersion for two periods during the 2010 Eyjafjallajökull eruption. The first period in

April is characterized by narrow ash clouds with high concentrations visible in the satellite data, while

for the period in May the observed ash clouds are more extensive with lower concentrations. The

inversion is performed with four different satellite data sets with different assumptions for the size

distribution. The effect of weighting the uncertainties associated with the a priori emissions and the

mass load uncertainties for the satellite retrievals on the a posteriori results is also studied. The

inversion technique is at last tested in a forecasting environment where more satellite observations are

added gradually as it would happen during a real volcanic eruption.

36

The default fine ash fraction of 0.4 for silicate-type standard volcanoes like Eyjafjollajökull given in Mastin et al. (2009) used in an operational setting and in this study to calculate the a priori emissions, is found to be too high for this eruption. All the a posteriori solutions calculated with the different satellite sets and uncertainties are therefore reduced compared to the a priori source term. This is in agreement with Stohl et al. (2011) and Kristiansen et al. (2012) where a lower fine ash fraction of 0.1 is used. The reductions are dependent on the ash column loads retrieved in the satellite data set used as input for the calculations. The spread in a posteriori results found by changing the uncertainty

connected to the a priori is found to be larger than by changing the satellite mass load uncertainty.

The quality of using the inversion in a forecasting environment is tested by adding gradually, with time, more observations to improve the estimated height versus time evolution of Eyjafjallajökull ash emissions. We show that the initially too high a priori emissions are reduced effectively when using just 12 hours of satellite observations. More satellite observations (>12h), in the Eyjafjallajökull case, place the volcanic injection at higher altitudes. Adding additional satellite observations (>36h) changes the a posteriori emissions to only a small extent for May and minimal for the April period, because the ash is transported effectively out of the domain during this period. A forecast emission term is tested where the last 12 hours of the a posteriori term are averaged and released over the forecast period. Using this emission the forecast simulations show better results than forecasts with a zero emission estimate for periods with a continued volcanic activity.

Compared to using only the a priori emissions the forecast simulations with the a posteriori emission

have column loads more comparable to observed ash, and with loads more confined to regions where

satellite observations show ash to be present. Because of undetected ash in the satellite retrieval and

diffusion in the model, the forecast simulations still generally contain more ash than the observed

fields and the model ash is more spread out. Overall, using the a posteriori emissions in our model

reduces the uncertainties connected to both the satellite observations and the a priori estimate to

perform a more confident forecast in both amount of ash released and emission heights.

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In document Modelling and optimized forecasting of volcanic ash and SO2 dispersion (sider 33-37)