In this study SO2 total columns from OMI and OMPS satellite instruments are used to monitor the volcanic emissions during the Holuhraun fissure eruption in September 2014. OMI is an UV-VIS spectrometer launched on-board EOS-Aura spacecraft in 2004 . The nominal pixel size of OMI is 13km×24km at nadir and 28km×150km at the swath ends. The OMI swath contains 60 cross-track pixels. The current local Equator crossing time is about 13:45. OMI covers the spectral range from 270 to 500 nm with a resolution of about 0.5 nm. The global coverage is achieved in 2 days. Since 2007 the so-called row-anomaly (see http://www.knmi.nl/omi/research/product/rowanomaly-background.php) has reduced the amount of valid pixels for volcanic clouds monitoring. Despite this anomaly, OMI data have been used in numerous studies for monitoring volcanic eruptions and anthropogenic pollution e.g.. In this work, the OMI data corresponding to pixel number from 23 to 56 are not taken into account.

OMPS is an UV spectrometer flying on-board Suomi National Polar-orbiting Partnership spacecraft since 2011 , with local Equator crossing time at 13:30. OMPS is a suite of three instruments: a nadir mapper, a nadir profiler and a limb profiler. In this paper the acronym OMPS refers to the nadir mapper instrument only. OMPS measures backscattered UV radiance spectra in the 300–380 nm wavelength range (resolution of 1 nm) with daily global coverage. OMPS is built on a TOMS heritage and its pixel size (50km×50km at nadir and 190km×50km at the edge of the swath) is bigger than OMI, but it is still suitable for anthropogenic SO2 monitoring, as shown by . The OMPS swath contains 36 cross-track pixels. Recently, reported the first volcanic SO2 measurements using OMPS data.

In order to obtain the total SO2 columns from OMI and OMPS measurements, the same retrieval techniques are applied to both instruments and four different SO2 total column estimates are provided, based on different assumptions of the SO2 vertical profile. The assumed SO2 profile shape is represented by its centre of mass altitude (CMA), defining the vertical region where SO2 is predominantly distributed. The products are (1) planetary boundary layer (PBL) SO2 column, corresponding to CMA of 0.9 km, (2) lower tropospheric (TRL) SO2 column, corresponding to CMA of 2.5 km, (4) upper tropospheric and stratospheric (STL) SO2 column, corresponding to CMA of 17 km. The TRL, TRM (mid-troposphere) and STL data products are processed using the linear fit (LF) algorithm designed for large volcanic SO2 loads and the PBL product is retrieved using the band residual difference (BRD) algorithm . Both BRD and LF algorithms take the residual after the ozone retrieval (SO2 assumed zero) as an input. In the current OMI PBL standard product, the BRD algorithm has been replaced with the recently developed principal component analysis (PCA) algorithm . The SO2 retrieval algorithm information are summarised in Table .

In this study, OMI SO2 standard products (SP, available at http://mirador.gsfc.nasa.gov) and the OMI and OMPS direct-broadcast data products are used. The direct-broadcast data are received through the ground-based antennas located in Sodankylä, northern Finland. OMI and OMPS DB images are available from SAMPO (http://sampo.fmi.fi) website. Note that OMPS operational data are not yet distributed and they are not included in this study. Thus, the OMPS data correspond here to the direct-broadcast data set, while OMI data are available as both standard product and direct-broadcast data sets. The DB algorithm uses the “latitude band average” as residual correction method, while the operational algorithm uses the “sliding median” technique, which requires a complete orbit to perform the correction seefor details. Because of these different methods and the observed difference of L1B data between DB and routine processing, differences between SO2 DB and SP products are expected. Assessing the quality of the DB retrievals is also important as they are used for volcanic emission real-time services and aviation hazard mitigation (e.g. SACS).

The accuracy and precision of the retrieved SO2 column depend on various factors like CMA, SO2 column amount, measurement geometry, ozone slant column density, solar zenith angle (SZA) and viewing zenith angle (VZA). For OMI, the SO2 README file v.1.2.0 (available at http://so2.gsfc.nasa.gov/Documentation/OMSO2Readme_V120_20140926.htm) discusses the error estimates of the standard products. One way to study the error estimates is to study SO2 retrievals in a pristine, presumably SO2-free location, like the Equatorial Pacific. A recent study by reports standard deviations (STDs) of about 0.5 and 1 DU for PBL PCA and PBL BRD algorithms, respectively. For TRL, TRM and STL algorithms the STDs are reported in the README file as 0.7, 0.3 and 0.2 DU, respectively.

A similar study can be conducted at high latitudes too. The results of this analysis are shown in Sect. .

The SO2 total columns from the Brewer spectrophotometer MK II #037 located in Sodankylä (67.42∘ N, 26.59∘ E), Finland, are compared to the satellite retrievals. The SO2 total columns are calculated from direct solar (DS) irradiances at the wavelengths of 306.3, 316.8 and 320.1 nm using the total ozone retrievals derived from the same instrument. The calibrations have been performed on regular basis. During the calibration, the extraterrestrial constant is determined using the Langley extrapolation method as described by . Since the measurements at short wavelengths are affected by stray light effects, the DS measurements corresponding to high air mass values (after 14:20 UT) are not provided. No significant bias has been estimated during the calibration. The normal SO2 values in Sodankylä are close to zero with an estimated detection limit of about 1 DU, similarly to the values reported by for Hohenpeissenberg. found that the average SO2 column values at most of the European Brewer sites are typically less than about 1 DU. Higher values of column SO2 have been measured by Brewer instruments at sites affected by volcanic eruptions. For example, reported observations of column SO2 amounts of more than 20 DU over Kagoshima (located close to a very active volcano, Sakurajima) as related to volcanic activity.

For this study, the atmospheric composition measurements were also available at four ground-level air quality monitoring stations located in northern Finland: Sammaltunturi (67.98∘ N, 24.12∘ E; 566 m), Kevo (69.76∘ N, 27.02∘ E; 107 m), Raja-Jooseppi (68.48∘ N, 28.30∘ E; 262 m), Oulanka (66.32∘ N, 29.42∘ E; 310 m). These remote rural-background monitoring sites have no significant SO2 emission sources in the vicinity, but are occasionally affected by the industrial SO2 emissions from the Kola Peninsula, Russia (about 10–15 kt in 2012 as reported in EMEP (European Monitoring and Evaluation Programme) database, http://www.ceip.at). The surface SO2 concentrations were measured using online trace level gas analysers based on the ultraviolet fluorescence method (i.e. European reference method). Measurement height is 4–5 m. The concentrations are recorded at 1 min intervals and, in this study, the hourly average values are used.

On 16 August 2014 the first indications of increasing seismic activity close to the Bárðarbunga (64.60∘ N, -17.50∘ E) volcano were reported by the Icelandic Met Office (see http://en.vedur.is/earthquakes-and-volcanism/articles/nr/2947). On 31 August the eruption started in the Holuhraun fissure, located northeast from Bárðarbunga. It was a continuous effusive fissure eruption, without explosive activity.

Figure  shows the time evolution of the OMI TRL SO2 maps over northern Europe during selected days after the volcanic eruption. The first enhanced SO2 signal from satellite observations was detected over Iceland on 1 September (Fig. a). During the next days the SO2 plume moved eastward toward Scandinavia (Fig. b). According to the satellite observations, the plume reached the first time northern Finland on 5 September (Fig. c). After that, high SO2 total column values over large areas in northern Finland were observed on 10, 27 and 29 September (Fig. d–f). Figure S1 in the Supplement shows the respective OMPS TRL SO2 maps. The SO2 map for 11 September is included instead of 28 September, when no OMPS observations are available. Despite similar algorithm assumptions and overpass times, the difference between OMI and OMPS SO2 total columns can be quite large, especially on the northern part of the Atlantic Ocean on 4 and 10 September. On the other hand, the spatial distributions of the SO2 plume from the two instruments are similar.

The end of Holuhraun fissure eruption was declared on 28 February 2015. This study has been limited to September 2014, in order to avoid extremely challenging observing conditions for the satellite retrievals occurring during fall-winter. In fact, the sensitivity of the satellite measurements to atmospheric trace gases in the lower troposphere is significantly reduced for large solar and/or viewing angles or when the field of view is affected by the clouds. Furthermore, no observations are available during the deepest winter time because of the reduced sun light hours at high latitudes.

SO2 total columns from Brewer observations in Sodankylä during 6 days on September 2014 are presented in Fig.  (black dots). Only selected days with a sufficient amount of Brewer DS measurements are considered. For comparison, SO2 total columns from both OMI SP and OMPS overpasses over Sodankylä are shown in Fig. . OMI DB SO2 data are also available but they are not included in Fig.  since several orbits were missing on the second half of September due to processing anomaly. For completeness, the OMI DB data (when available) are reported in Table , and their agreement with the ground-based observations will be discussed later in this section. The central pixels (5–55 for OMI and 4–33 for OMPS) are highlighted in Table . The satellite data sets include four SO2 products with different a priori profile assumptions as described in Sect. . In OMI SP, the PBL data are processed using both the PCA (blue circles in Fig. ) and the BRD (pink stars in Fig. ) algorithms. OMI and OMPS DB data sets are processed using the BRD algorithm. An overview of the satellite overpasses over Sodankylä (during the same days shown in Fig. ) are presented in Table , together with the Brewer SO2 observations closest (within 30 min) to the satellite overpass time.

The best agreement between ground-based and satellite SO2 total columns is generally found for the PBL product (blue circles and crosses, and pink stars in Fig. ). In general, for high-latitudes cloud-free observation conditions, the PBL products are expected to underestimate SO2, since much smaller solar and viewing zenith angles are assumed in the retrievals (see Sect. ). Furthermore, one must note that the satellite retrievals are expected to be lower than the Brewer values due to dilution, as the average SO2 columns derived within the relatively large satellite pixel are compared to the local point measurements from ground-based observations. Overall, OMI retrievals are closer to the Brewer observations than OMPS. The results of the comparison are analysed day-by-day below.

5 September 2014 – The volcanic plume reaching Finland produces SO2 total column values up to about 6 DU in Sodankylä as observed from the Brewer measurements. The best agreement with the SO2 satellite products is achieved for OMI PBL data from the BRD algorithm. OMI SO2 total column at 09:57 is 2.49 DU for the SP BRD data set and 2.85 DU for the DB data set, and the closest Brewer measurement is 3.7 DU. This overpass corresponds to favourable measuring conditions i.e. small OMI pixel (number 16), small distance between the pixel centre and the ground-based station (7.7 km), relatively small SZA (60.6∘) and cloud fraction CF (0.21) smaller than 0.3. Overall the satellite retrieval gives smaller SO2 vertical columns than the Brewer. Some of the possible reasons are discussed in Sect. .

6 September 2014 – Only OMI data are available because OMPS observations on Saturdays are dedicated to high resolution mode. One clear-sky overpass from OMI is available. Also in this case the satellite PBL product gives the best agreement with the corresponding Brewer retrieval. PCA and BRD algorithms give very similar results: SO2 total column at 09:03 is 2.59 DU from BRD algorithm and 2.79 DU for PCA, while the closest Brewer measurement gives 4.4 DU. Also OMI PBL SO2 total column value (3.86 DU) from direct broadcast is close to the ground-based observations. As on 5 September, this overpass corresponds to relatively good observation conditions (pixel number = 6, distance = 8 km, CF = 0.24 and SZA = 62.1∘). As for 5 September satellite retrievals are smaller than Brewer measurements.

10 September 2014 – Two overpasses are available from both OMI and OMPS, but only one OMI overpass is under clear-sky conditions. Brewer data show again their best agreement with the PBL products. OMI SO2 total column at 10:16 is 4.4 DU for PCA, 3.31 DU for BRD and 2.73 DU for the direct-broadcast BRD data set. The closest Brewer observation gives SO2 total column value of 2.6 DU. OMPS data are very similar to OMI except for the PBL products.

27 September 2014 – From now on, the satellite overpasses correspond to SZA about 70∘ or larger. Only OMI overpasses are available, and only one is under clear-sky conditions. For this clear-sky overpass, OMI BRD PBL data are much closer than PCA to the ground-based observation. Also OMI TRL product is larger than PCA and closer to the ground-based observations. Very large SO2 total column values (up to more than 10 DU) are observed by the Brewer. The largest satellite SO2 total column (9.99 DU) is derived from the BRD algorithm from the standard product and it is very close to the Brewer values. OMI PBL product from direct broadcast gives a similar result (SO2 total column is 9.50 DU).

28 September 2014 – The Brewer observations show SO2 total column values up to about 2 DU, thus, much smaller than the previous days. Two clear-sky overpasses for both OMI and OMPS are available. Both OMI PBL PCA data and OMPS PBL are missing for the their first overpass of the day. For the second overpass, the PBL products are again very close to the ground-based observations, except for the OMI PBL product from the BRD algorithm which produces negative values. No OMI data from direct broadcast are available for this day.

29 September 2014 – The largest SO2 total column (13.9 DU) from Brewer measurements in September is recorded. SZA values up to 74–75∘ are reached during this last day of comparison. Most of the overpasses are available under cloudy conditions and the only clear-sky overpass corresponds to a very large OMPS pixel (number 1) and large SZA (75.1∘). No OMI PBL products from PCA algorithm are available. Despite these limitations, the satellite observations are able to follow the daily evolution of SO2 total column shown by the ground-based measurements. Both OMI and OMPS PBL products (the lightest shade of grey in Fig.  – lower right panel) show larger values around 09:00 UTC and decreasing during the day.

The amount of satellite data included in the comparison can be increased considering all pixels within 60 km from Sodankylä. Figures S2 and S3 in the Supplement show the comparison between Brewer observations and this extended overpass data set for OMI and OMPS PBL products, respectively. In this case several overpasses correspond to almost the same time of the day. Because of the narrow structure of the SO2 plume, this range of values corresponds to both in-plume and background pixels. For example, on 10 September, the large total column values from satellite retrievals agree with the Brewer observations obtained later in the afternoon, suggesting that the volcanic plume with higher SO2 content (the blue-green narrow structure visible West from Sodankylä in Fig. d) reached Sodankylä after the overpass time. The largest difference between BRD and PCA algorithms can be observed on 27 September for SZA = 70∘; because the PCA algorithm uses the entire spectrum in the SO2 fitting to reduce interferences from instrumental or geophysical effects in general it was found PCA SO2 results to be smaller than BRD, particularly for high latitudes. Furthermore, Sodankylä is often at the edge of the SO2 plume, which is not optimal for comparisons. In Fig. S2 and S3 the data are separated according to the sky conditions and the pixels size, helping in visualising the results reported in Table . Satellite retrievals corresponding to large pixels are sometimes much smaller than Brewer observations (see, e.g. light blue markers on 5 and 29 September in Fig. S3, where negative values are reported). Under cloudy conditions, the satellite retrievals are expected to underestimate the SO2 columns, since part of the column is below the cloud. This behaviour it is not clearly visible from Figs. S2 and S3, because several factors are affecting the analysis.

In order to to get an idea about the precision (or noise) of the satellite data at northern high latitudes, STDs for different products are derived from the box (10∘ E, 30∘ E) × (60∘ N, 70∘ N) for a presumably SO2-free day (1 September 2014). For TRL, TRM and STL products, the obtained standard deviation values are very similar to those reported in the README file (see Sect. ). For the PBL products, STDs of about 1.6 DU, 0.8 DU and 0.5 DU are obtained for OMI BRD, OMI PCA and OMPS BRD products, respectively. On 3 October 2014, with solar zenith angles about 70∘ or higher, the STD values are about 2.7 and 2.1 DU for OMI and OMPS PBL BRD products and about 1.1 DU for OMI PCA PBL data product. In addition, TRL STDs grow up to about 1.2 DU. This confirms that the quality of the satellite retrieval is lower for high solar zenith angles. The overpasses shown in Fig.  are sometimes close or below the detection limit (defined as twice the precision), especially during the last days of comparison. Assuming that the PBL products better represent the actual SO2 profile distribution, the differences between satellite and ground-based observations are mostly within these uncertainties.

One of the main source of error in the BRD product is due to the fact that the vertical column density is obtained dividing the slant column density by a constant AMF of 0.36, which is derived for SZA = 30∘ and VZA = 0∘. The same settings are used in the PCA algorithm. The radiative transfer calculation shows (Fig. S4 in the Supplement) that the AMF decreases by about 30 % from 30∘ to 65∘ SZA, leading to an underestimation of the SO2 vertical column. There is also less pronounced dependence on the VZA. The operational vertical column can be corrected by multiplying by the ratio between the assumed AMF (0.36) and the AMF calculated for larger values of SZA and VZA . For example, when correcting the operational retrievals for SZA = 60∘ (as for example on 5 September) with AMF about 0.3, the resulting SO2 vertical column is 20 % larger than the operational value.

The AMF also depends on the slant column ozone (SCO). To the first approximation the dependence can be approximated as a linear regression with SCO amount as described in Fig. 4 in . For SCO values larger than 1500 DU (high ozone and/or high solar zenith and viewing angles, as at high latitudes) the AMF decreases by more than 30 %.

Figure S5 in the Supplement includes the comparison between Brewer SO2 columns and OMI and OMPS PBL products corrected for a range of possible AMF values (0.2–0.4, considering SZA = 60∘–75∘, VZA = 0∘–45∘, SCO = 800–1600 DU). The resulting SO2 columns range from 80 % larger and 10 % smaller than the operational values. Because satellite retrievals often underestimate the ground-based observations, the results of the comparison are generally improved using a smaller AMF values. In some cases (e.g. OMI BRD product on 27 September), correcting for a smaller value of AMF, does not improve the results of the comparison. Because the AMF correction is a multiplicative factor, the variability of the SO2 column value depends on the original value. Thus, SO2 column values close to zero or negative will have very small variability or will become more negative when changing the AMF value. It must be also pointed out that the “error bars” presented in Fig. S5 include only the variability due to different AMF values, but not other sources of uncertainty.

On the other hand, the LF algorithm accounts for the actual observation conditions and has no inherent bias under high solar/viewing zenith angles.

Another source of error in the satellite retrievals is due to the difference between the assumed profiles and the actual SO2 layer height. The averaging kernels represent the height-dependent sensitivity of the satellite observations to changes in the SO2 amount. Considering for example the LF averaging kernels (Fig. S6 in the Supplement and ), the retrieved SO2 column can be further adjusted with the actual layer height. For instance, for an SO2 layer centred at 1 km, the LF TRL retrieval underestimates the column amount: the actual SO2 column is twice as large as TRL columns for a cloud-free scene. Also, the averaging kernels show similar dependence on altitude for various viewing and solar zenith angles (different line colours in Fig. S6), especially for altitudes below the assumed CMA. Thus, no significant changes are expected for high latitude observations. The PBL retrievals are characterised by a similar altitude dependence as for the LF algorithm.

Overall, the SO2 retrieval at high latitudes is challenging due to low earthshine radiance received from the satellite; thus large impacts of instrumental effects (such as stray lights and other spectral artifacts) are expected on the retrieval results. This leads to biases which can exceed those from measurement noises and retrieval errors due to algorithmic assumptions described above.

Since the volcanic SO2 plume was located at low altitudes, elevated concentrations of SO2 were detected also at the surface. Figure  (right panel) shows the time evolution of the SO2 concentrations observed during September 2014 at four air quality stations in northern Finland: Sammaltunturi, Kevo, Raja-Jooseppi and Oulanka. The locations of these sites are shown as triangles in Fig.  (left panel). Elevated SO2 concentration values were measured starting on 5 September 2014, when also the SO2 plume was observed over northern Finland for the first time after the volcanic eruption (Fig. c). The highest hourly mean (about 180 µgm-3) was found at Sammaltunturi during the night between 7 and 8 September 2014. The largest daytime peak at Sammaltunturi was observed on 10 September. During the same day concentration peaks were observed also at Raja-Jooseppi and Kevo stations. For comparison, the map of OMI PBL PCA product on 10 September is shown in Fig.  (left panel): the three northernmost stations (Sammaltunturi, Kevo and Raja-Jooseppi) were inside the SO2 plume. This corresponds to the SO2 concentration peaks observed in Fig.  (right panel) on 10 September. On the other hand, Oulanka was outside the plume during the same day and large SO2 concentrations were only observed the morning after, 11 September 2014, because the plume was transported eastward (as seen in Fig. S1). The SO2 concentration peak in Kevo was smaller than in the other sites probably due to the lower altitude of the station.

Large SO2 concentrations were measured during 13–19 September 2014 (up to about 50 µgm-3 on 15 September), corresponding to SO2 total column values up to about 1.5 DU measured from Brewer during the same period (not shown here). Because only sparse Brewer DS measurements are available during this period, these data are not included in the comparison shown in Fig. . Elevated SO2 concentrations (up to about 50 µgm-3) were observed also on 27 and 29 September, when also the Brewer and the satellite measurements showed high SO2 total column values. These concentrations were not as elevated as in the first half of September. This suggests that the SO2 plume was located at higher altitudes during these 2 last days, thus only partially affecting the SO2 concentration levels at the surface.

Despite satellite vertical columns and ground-based surface concentrations are not quantitatively comparable, the observed spatiotemporal link between high SO2 concentration values at surface and large total columns from satellite adds confidence in using satellite-based observations for volcanic emission monitoring during such kind of events, with the SO2 plume located at quite low altitudes. In particular, in this case the satellite instruments showed their capability to detect the position of the volcanic plume as compared to independent ground-based observations.