Introduction
Atmospheric sulfur dioxide (SO2) has significant impacts on the
environment and climate. SO2 is oxidised to form sulphate aerosols,
which in turn participate to the stratospheric ozone destruction
and cause Earth surface cooling , by
reflecting the incoming solar radiation. SO2 is generated by natural
sources (e.g. degassing and eruptions of volcanoes, sea spray) and
anthropogenic sources (e.g. combustion processes). SO2 is toxic when
present in high concentrations at the surface and negatively affects human
health.
SO2 has been measured from space since the 1982 eruption of El
Chichón . This was the first time when
SO2 from satellite measurements could be determined from UV-VIS
sensors. Those measurements were carried out by Total Ozone Mapping
Spectrometer (TOMS), which had a limited SO2 detection sensitivity,
since the discrete measurement wavelengths were designed for total ozone
retrieval . Since then, next-generation space-borne
spectrometers like GOME (Global Ozone Monitoring Experiment) and
GOME-2, SCIAMACHY (SCanning Imaging Absorption spectroMeter for
Atmospheric CHartographY) and OMI (Ozone Monitoring Instrument) have shown
greatly improved SO2 detection sensitivity.
Currently, SO2 from volcanic eruptions and degassing are routinely
monitored using satellite data. For example, satellite measurements of
volcanic SO2 emissions can provide critical information for aviation
hazard mitigation . SO2 has low background,
making the volcanic SO2 plumes clearly distinguishable even at long
distance from the source. For example, services like SACS (Support to
Aviation Control Service, http://sacs.aeronomie.be) use SO2 as
an indicator for volcanic activity and send email notifications when
instrument specific SO2 thresholds are exceeded . Quality
and timeliness of satellite data products are essential for these kinds of
services. Near real-time satellite products – typically available 3 h after
the satellite overpass – are generally used for this purpose. Faster
processing can be achieved if the so-called direct-broadcast (DB) data are
used. This is possible for example for NASA's Terra, Aqua and Aura satellites
as well as the recently launched Suomi National Polar Partnership spacecraft,
which hosts the Ozone Mapping Profiler Suite (OMPS). The direct-broadcast
concept is based on measuring and simultaneously sending the observations
down to Earth for processing. The time needed for SO2 processing is
less than 15 min. However, this option is only available for specific
locations on the Earth. Direct-broadcast data are received, for example, in
Sodankylä (Finland), and SO2 maps over central and northern Europe
are available from SAMPO (Satellite measurements from Polar orbit,
http://sampo.fmi.fi) service, which is built on the heritage of OMI
Very Fast Delivery . This location is especially
suitable for receiving DB data since several overpasses are available during
1 day.
The opportunities to validate volcanic SO2 satellite products are
rare, because only occasionally the volcanic plumes drift over a ground-based
station where SO2 measurements are performed. The first successful
attempt to validate volcanic OMI SO2 took place in 2008 after the
Okmok volcanic eruption . This was followed by an
“opportunistic” validation study of Sarychev Peak volcanic eruption cloud,
using a mobile ground-based instrument . The conclusion of
the latter study was that stationary ground-based measurements would provide
better and more easily interpretable validation data. However, both studies
show good agreement between ground-based and OMI SO2 data. In these
studies, about 3–5 OMI pixels were compared against ground-based
observations.
GOME-2 SO2 total columns have also been used for monitoring volcanic
eruption and validated, for example, during the eruption of
the Eyjafjallajökull volcano (Iceland) in April and May 2010 using Brewer
measurements . GOME-2 data agreed very well with the Brewer
observations at Hohenpeissenberg (Germany), whereas the Brewer instrument at
Valentia (Ireland) showed up to 50 % higher SO2 columns. Part of this
difference was due to the fact that the Brewer data were available as daily
averages while the GOME-2 measurements represent a snapshot at the time of
the overpass. Furthermore, differences can be caused by uncertainties in both
satellite and Brewer observations.
In this paper, both OMI and OMPS operational products are used to monitor the
spatiotemporal evolution of the volcanic SO2 cloud generated during
the Holuhraun (Iceland) fissure eruption in September 2014. Since the
SO2 plume reached northern Finland, this episode gives the
opportunity to compare SO2 satellite data to the Brewer SO2
total columns available at Sodankylä ground-based station. Because the
satellite retrieval strongly depends on the air mass factor (AMF, the ratio
between slant and vertical column density) and on the a priori SO2
profile, the effects of these parameters on the retrieval are also discussed.
Furthermore, the implications of such volcanic eruption on air quality in
northern Finland are investigated, combining the time evolution of satellite
observations and SO2 concentrations at surface level.
Section describes the data set used in the comparison. The
comparison results are presented and discussed in Sect. . The
main findings of this work are summarised in Sect. .
Data set
Satellite SO2 products
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. .
Summary of the SO2 retrieval algorithms.
Producta
CMAb
Algorithm
Reference
(km)
PBL
0.9
BRDc
PCAd
TRL
2.5
TRM
7.5
LFe
STL
17
a Satellite SO2 total column optimised for different altitude regions: planetary boundary layer (PBL), lower troposphere (TRL), mid-troposphere (TRM) and lower stratosphere (STL).b Centre of mass altitude (CMA).c Band residual difference (BRD).d Principal component analysis (PCA), available for OMI standard product only. e Linear fit (LF).
Ground-based measurements
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.
Results and discussion
Timeline of Holuhraun eruption
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.
Comparison between satellite and ground-based SO2 total columns
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.
SO2 total columns as seen from OMI SP TRL product during the
Holuhraun fissure eruption for 6 days in September 2014. The dates
(day/month) are indicated in the title of each panel. The blue crosses
indicate the location of Sodankylä ground-based station.
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.
SO2 vertical columns in Sodankylä, Finland during
selected days of September 2014. Black dots refer to ground-based Brewer
measurements, circles to OMI SP and crosses to OMPS observations. Different
colours correspond to different satellite products sensitive to different
altitude regions: PBL (blue), TRL (green), TRM (red) and STL (light blue).
The pink stars refer to the PBL product processed using the BRD algorithm.
PBL, TRL, TRM and STL satellite products for cloudy scenes (cloud fraction
larger than 0.3) are shown in grey (from light to dark grey, respectively)
and should be considered with caution.
Summary of the satellite overpasses at Sodankylä.
Date
Time
Data producta
CTPb
Distancec
CFd
SZAe
SO2 total column (DU)f
Brewer DSg
(09/14)
(UTC)
(km)
PBLh
TRL
TRM
STL
SO2 (DU)
Time (UTC)
5
08:04
OMPS DB
3
58.2
0.29
64.2
-1.05
-1.04
-0.44
-0.30
6.2±0.3
07:59
5
08:20
OMI SP
2
56.1
0.41
63.3
-0.84 / 1.30
-0.42
-0.11
-0.06
3.2±0.4
08:18
5
08:20
OMI DB
2
56.1
0.41
63.3
-0.75
0.25
0.06
0.03
3.2±0.4
08:18
5
09:43
OMPS DB
12
23.2
0.21
60.6
-0.08
0.59
0.31
0.25
2.9 ± 0.5
09:39
5
09:57
OMI SP
16
7.7
0.22
60.6
2.49/-0.3
0.72
0.33
0.26
3.7 ± 0.3
09:56
5
09:57
OMI DB
16
7.7
0.21
60.6
2.85
1.20
0.51
0.38
3.7 ± 0.3
09:56
5
11:23
OMPS DB
31
33.2
0.25
61.9
0.88
0.91
0.41
0.31
3.9 ± 0.4
11:19
6
09:03
OMI SP
6
8.0
0.24
62.1
2.59 / 2.79
0.93
0.42
0.30
4.4 ± 0.3
09:02
6
09:03
OMI DB
6
8.0
0.24
62.1
3.86
1.66
0.68
0.47
4.4 ± 0.3
09:02
6
12:19
OMI SP
58
13.3
0.44
64.6
1.53 / 0.25
0.86
0.30
0.18
6.2±0.4
12:28
6
12:19
OMI DB
58
13.3
0.45
64.6
-0.09
0.89
0.27
0.17
6.2±0.4
12:28
10
08:10
OMPS DB
3
19.7
0.25
65.4
0.93
0.45
0.19
0.13
0.7±0.4
08:13
10
08:38
OMI SP
4
32.0
0.38
64.6
0.77 / 0.06
0.21
0.07
0.05
0.8±0.2
08:27
10
08:38
OMI DB
4
32.0
0.39
64.6
0.94
0.70
0.23
0.15
0.8±0.2
08:27
10
09:49
OMPS DB
14
30.1
0.29
62.8
1.21
1.08
0.54
0.44
2.5 ± 0.5
09:48
10
10:16
OMI SP
22
8.1
0.15
62.4
3.31 / 4.44
0.65
0.36
0.27
2.6 ± 0.3
10:28
10
10:16
OMI DB
22
8.1
0.15
62.4
2.73
0.84
0.46
0.35
2.6 ± 0.3
10:28
27
07:44
OMI SP
1
7.9
0.59
73.3
9.17 / –
9.07
3.06
1.50
8±0.4
07:35
27
09:21
OMI SP
8
17.2
0
69.4
9.99 / 2.66
3.42
1.37
0.81
6.6 ± 0.4
09:30
27
09:21
OMI DB
8
17.2
0
69.4
9.50
3.55
1.42
0.84
6.6 ± 0.4
09:30
27
12:37
OMI SP
60
26.2
0.86
74.2
4.64 / –
3.41
1.39
0.70
–
–
28
08:26
OMI SP
3
19.1
0
71.6
1.36 / –
-1.40
-0.47
-0.23
0.2±0.2
08:37
28
09:12
OMPS DB
8
12.5
0.06
70.0
-2.94
-1.61
-0.66
-0.40
1.0 ± 0.3
09:14
28
10:03
OMI SP
18
4.0
0
69.4
-1.27 / 0.95
0.27
0.11
0.06
1.4 ± 0.2
10:02
28
10:52
OMPS DB
27
25.3
0.11
70.1
1.51
0.99
0.43
0.27
1.9 ± 0.2
10:40
29
07:15
OMPS DB
1
8.5
0.04
75.3
-1.94
–
-1.00
-0.40
9.4±1.3
07:17
29
08:54
OMPS DB
6
11.9
0.41
70.7
5.76
1.81
0.77
0.55
12 ± 0.9
08:52
29
09:09
OMI SP
7
24.9
0.73
70.5
7.44 / –
2.81
1.06
0.73
11.8 ± 0.8
09:08
29
10:34
OMPS DB
23
6.4
0.31
70.1
3.66
1.75
-0.81
0.58
3.9 ± 0.8
10:31
29
12:15
OMPS DB
36
40.8
0.55
74.2
2.91
1.84
0.61
0.32
–
–
29
12:25
OMI SP
59
28.3
0.71
74.2
4.20 / –
2.14
0.76
0.39
–
–
a Satellite data products. The options are the following: OMI SP (standard product); OMI DB (Direct Broadcast) and OMPS DB.b Cross track position (CTP). Ranging from 1 to 60 for OMI and from 1 to 36 for OMPS. The central pixels (nadir) are smaller than those at the edges of the swath and they are highlighted in bold.c Distance between the centre of the satellite pixel and Sodankyä.d Satellite-derived cloud fraction (CF).e Satellite-derived solar zenith angle (SZA).f Satellite SO2 total column optimised for different altitude regions: planetary boundary layer (PBL), lower troposphere (TRL), mid-troposphere (TRM) and lower stratosphere (STL).g SO2 total column from Brewer spectrophotometer direct sun (DS) measurements. The closest observations (within 30 min) to the satellite overpass time are taken into account.h OMI SP PBL product is processed using both band residual
difference and principal component analysis algorithms (BRD / PCA).
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.
Analysis of the uncertainties
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.
Effect of volcanic SO2 emission on the surface-level concentration
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.
Left panel: OMI SP PBL (PCA algorithm) during 10 September 2014. The
black cross indicates the location of Sodankylä. The triangles indicate
the location of the air quality stations: Sammaltunturi (blue), Kevo (green),
Raja-Jooseppi (red), Oulanka (light blue). Right panel: Time series of the
SO2 concentration in the northern Finland air quality stations in
September 2014.
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.
Summary and remarks
The comparison of satellite
SO2 retrievals derived from the OMI and OMPS instruments with
ground-based observations during the Icelandic Holuhraun fissure eruption in
September 2014 is presented in this paper. The satellite observations were
compared against ground-based Brewer measurements made in Sodankylä,
Finland, which is located more than 2000 km from the emission source. On 29 September 2014, the Brewer measured the SO2 total column record value
(13.9 DU) for 2014. This is the second largest value measured in
Sodankylä, after the Kasatochi volcanic eruption in 2008 (17.2 DU).
The best agreement with the Brewer data was usually achieved with the
satellite data products that assume a priori profile with SO2
predominantly in the planetary boundary layer, i.e. the lowest levels of the
atmosphere. This is reasonable since the SO2 emissions in Iceland
were emitted at tropospheric altitudes. In addition, exceptionally high
SO2 surface concentrations (up to about 180 µgm-3)
were observed in northern Finland, where the typical background SO2
concentrations are close to zero. The air quality monitoring site located at
the highest altitude, Sammaltunturi, was the most affected; hourly
SO2 concentration exceeded 100 µgm-3 15 times.
Record high concentrations were also detected at Oulanka, where the highest
hourly, daily and monthly averages in the past 10 years were recorded. The
SO2 concentration peaks in the time series correspond to enhanced
SO2 signals in the satellite data observed on the same days. This
supports the hypothesis that the volcanic plume was located very close to the
surface. These results show also that the satellite retrieval algorithms can
detect, qualitatively, the geographical location of the SO2 plume, as
compared to the ground-based stations.
The comparison between satellite and Brewer SO2 total columns showed
the best agreement during the first half of September. During this first
period, the BRD and the new PCA algorithms give very similar results for the
OMI PBL product. Also the OMI DB products were available until 27 September.
The direct-broadcast and standard products showed very similar results. The
discrepancy between these products (both derived using the BRD algorithm) is
related to the different residual correction methods.
In the latter comparison period, the agreement with satellite products was
weaker and the best agreement was found with PBL and TRL data products. The
weaker agreement can be related to the less favourable satellite retrieval
conditions, e.g. the large solar zenith angles (close or above 70∘)
and the frequent cloudy conditions. Less OMI PBL data from PCA algorithm were
available, because the retrievals with slant column O3 over 1500 DU
(corresponding to high O3 and large solar and viewing angles) are not
included in the data set. Also, the different OMI PBL products (PCA and BRD)
gave less similar results than at the beginning of September. Despite these
limitations, the satellite observations were still able to follow the daily
evolution of the Brewer SO2 total column values.
There are not many validation studies including satellite SO2 data
and even less at high latitudes. This is the first work in which PBL products
are used to analyse volcanic emissions, because the SO2 plume was
located at very low altitudes. Because the solar and viewing zenith angles
assumed in the satellite retrieval refer to lower-latitude regions, the
satellite data for PBL are expected to underestimate SO2 at high
latitudes. Furthermore, the knowledge of the SO2 vertical profile is
critical to evaluate how the satellite retrievals compare to the actual
SO2 column. This study highlights the need for improved retrievals at
high latitudes and provides useful information about satellite SO2
data quality during a volcanic eruption episode with several peculiarities:
the SO2 plume was found close to the surface and strongly affected
the air quality levels in northern Finland; the ground-based station
Sodankylä is located at high latitudes (above 67∘ N), where the
satellite retrievals are particularly challenging because of high solar
zenith angles and frequent cloudy scenes; the absolute SO2 values are
much higher than the background, reaching up to 9 DU in this study. Also,
this is the first time when direct-broadcast SO2 satellite data (from
both OMI and OMPS instruments) are compared against ground-based
observations.
The end of Holuhraun fissure eruption was declared at the end of February 2015, meaning that the eruption continued during the northern hemispheric
winter. Monitoring SO2 during winter using UV-VIS instruments like
OMI and OMPS becomes more difficult because of the reduced length of the day
and increasing solar zenith angles. This can be already seen, e.g. in
Fig. : the observable area is quickly reduced moving from the
beginning to the end of September. For this reason, this study was limited to
the month of September only. In addition to instruments like OMI and OMPS,
SO2 can be measured using satellite instruments like IASI
Infrared Atmospheric Sounding Interferometer, e.g. and
AIRS Atmospheric Infrared Sounder, e.g., which use the IR
channels. However, they are less sensitive than the UV-VIS instruments to the
tropospheric SO2 signal.