A study of the total atmospheric sulfur dioxide load using ground-based measurements and the satellite derived Sulfur Dioxide Index

Atmospheric Environment 43 (2009) 1693–1701

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A study of the total atmospheric sulfur dioxide load using ground-based measurements and the satellite derived Sulfur Dioxide Index A.K. Georgoulias a, *,1, D. Balis a, M.E. Koukouli a, C. Meleti a, A. Bais a, C. Zerefos b a b

Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece Laboratory of Climatology, University of Athens, 15784 Athens, Greece

a r t i c l e i n f o

a b s t r a c t

Article history: Received 10 June 2008 Received in revised form 7 December 2008 Accepted 8 December 2008

We present characteristics of the sulfur dioxide (SO2) loading over Thessaloniki, Greece, and seven other selected sites around the world using SO2 total column measurements from Brewer spectrophotometers together with satellite estimates of the Version 8 TOMS Sulfur Dioxide Index (SOI) over the same locations, retrieved from Nimbus 7 TOMS (1979–1993), Earth Probe TOMS (1996–2003) and OMI/Aura (2004–2006). Traditionally, the SOI has been used to quantify the SO2 quantities emitted during great volcanic eruptions. Here, we investigate whether the SOI can give an indication of the total SO2 load for areas and periods away from eruptive volcanic activity by studying its relative changes as a correlative measure to the SO2 total column. We examined time series from Thessaloniki and another seven urban and non-urban stations, five in the European Union (Arosa, De Bilt, Hohenpeissenberg, Madrid, Rome) and two in India (Kodaikanal, New Delhi). Based on the Brewer data, Thessaloniki shows high SO2 total columns for a European Union city but values are still low if compared to highly affected regions like those in India. For the time period 1983–2006 the SO2 levels above Thessaloniki have generally decreased with a rate of 0.028 Dobson Units (DU) per annum, presumably due to the European Union’s strict sulfur control policies. The seasonal variability of the SO2 total column exhibits a double peak structure with two maxima, one during winter and the second during summer. The winter peak can be attributed to central heating while the summer peak is due to synoptic transport from sources west of the city and sources in the north of Greece. A moderate correlation was found between the seasonal levels of Brewer total SO2 and SOI for Thessaloniki, Greece (R ¼ 0.710–0.763) and Madrid, Spain (R ¼ 0.691) which shows that under specific conditions the SOI might act as an indicator of the SO2 total load. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Sulfur dioxide Total column Brewer spectrophotometer Sulfur Dioxide Index Satellite observations

1. Introduction The atmospheric loading of sulfur dioxide (SO2) along with aerosols, carbon monoxide and dioxide, nitrogen oxides and ozone, is mainly responsible for air quality. Sulfur dioxide is the main source of atmospheric sulfur. Significant amounts of SO2 near the ground have a direct effect on human health, leading to respiratory symptoms, difficulty in breathing, even premature deaths in extreme cases, and inhibit plant growth. SO2 oxidizes in the troposphere to form sulfuric acid (H2SO4) which is mostly deposited as acid rain, being responsible for the contamination of soil and for the degradation of marble monuments. Moreover, SO2 plays an

* Corresponding author. Present address: Laboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric Pollutants, Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece. Tel.: þ30 2541079383. E-mail address: [email protected] (A.K. Georgoulias). 1 Tel.: þ30 2310998192; fax: þ30 2310998090. 1352-2310/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2008.12.012

important role in cloud formation physics, leading to clouds of high reflectivity. In the stratosphere SO2 is also oxidized and combines with water to H2SO4/H2O aerosols (Bekki, 1995). These aerosols scatter solar radiation and absorb long-wave radiation, causing heating in the stratospheric region and net cooling at the Earth’s surface. Anthropogenic SO2 and by extension sulfur emissions, are estimated to be larger than emissions from natural sources. The estimated difference between anthropogenic and natural sulfur emissions varies, since major natural sources like volcanic eruptions are occasional emitters. Sulfuric compound emissions of natural origin have been estimated to be 70  40 TgS/year (Jorgensen and Hansen, 1985) and 65  25 TgS/year (without seasalt sulfate) by Andreae and Jaeschke (1992). Anthropogenic emissions reached a maximum during the 1980s and from 1990 till today they have decreased strongly in Europe and North America as a result of sulfur control policies and the Eastern Europe sociopolitical changes (Smith et al., 2004; Stern, 2006; Vestreng et al., 2007). The period between 1990 and 2000 was dominated by the

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significant drop in industrial production in Eastern and Central Europe and consequently in energy consumption and sulfur emissions. Anthropogenic sulfur emissions have been estimated to range between 65 and 90 TgS in 1990 (Houghton et al., 1995; Benkovitz et al., 1996; Olivier et al., 1996; WMO, 1997). Andreae and Jaeschke (1992) have estimated annual anthropogenic sulfur emissions to be 93  15 TgS/year. Reviews of most recent inventories indicate a most likely value of 72  8 TgS (Smith et al., 2001) or 76 TgS (Gru¨bler, 1998). According to the report of the Intergovernmental Panel on Climate Change (IPCC) for 2000 (IPCC, 2000) anthropogenic SO2 emissions are considered to be around 71 TgS/ year. The distribution of these emissions is not globally uniform as the vast majority is in the Northern Hemisphere (Andres and Kasgnoc, 1998). About 90% of the anthropogenic sulfur emissions occur in the Northern Hemisphere while natural sulfur emissions are more evenly distributed between the two hemispheres. Contrary to Europe and North America, sulfur emissions in China and central Asia in general, rose significantly in the last 20 years due to continuous development of economics in these areas. Just for the period 1985–1994, sulfur emissions in China rose from an estimated 6.6 TgS in 1985 to 9.1 TgS in 1994, or by 38% (Sinton, 1996; Dadi et al., 1998). This increase in emissions in combination with the two greatest volcanic eruptions of the past century, El Chicho´n in April 1982 and Pinatubo in June 1991, which injected great amounts of SO2 into the atmosphere, rejuvenated scientific interest in SO2 detection and monitoring. Several methods have been developed for measuring not only near surface concentrations but also the total atmospheric content using ground-based instruments. Brewer spectrophotometers are being widely used for the assessment of SO2 total column over selected areas in matm-cm (Dobson units (DU)). Moreover, different types of satellite instruments have been used for SO2 remote sensing. Total ozone mapping spectrophotometers (TOMS) are of specific interest here, since the corresponding time series goes back to 1978. The TOMS instruments were initially designed just to map the daily global total ozone field. Prior to the eruption of El Chicho´n, ozone was thought to be the only significant atmospheric absorber at near ultraviolet wavelengths. However, the El Chicho´n plume appeared in Nimbus 7 TOMS data as anomalously high ozone amounts. The excess absorption was found to be primarily from SO2 (Krueger, 1983). With two absorbing constituents, the initial TOMS algorithm could no longer be used to accurately measure total ozone under the presence of volcanic plumes. Despite the fact that TOMS wavelengths are far less than optimal for the detection of SO2, a proper algorithm to detect the presence of SO2 was developed so that contaminated ozone data could be identified using the Sulfur Dioxide Index (SOI). The widely known Krueger–Kerr algorithm is based on a simultaneous solution of the absorption optical depth equations at four of the TOMS wavelengths, coupled with an empirical correction developed in background areas where SO2 absorption is negligible (Krueger et al., 1995). The present algorithm in use, Version 8 TOMS (V8 TOMS-ATBD), like its predecessor, Version 7 TOMS (McPeters et al., 1996, 1998), also produces an SOI which is distributed as part of a publicly available level-2 data set. SOI theoretically expresses an estimate of the total column SO2 in the free troposphere and stratosphere in cases when large amounts of SO2 have been injected in the atmosphere, especially during strong volcanic eruptions. The background total SO2 column in the atmosphere is very small (less than 0.1% of that of ozone) and most of the SO2 resides in the boundary layer. Since the scattering height in the atmosphere lies above the boundary layer in the UV/ VIS spectral region, the satellite instruments do not receive enough information from the lower atmospheric layer, hence the detection of SO2 from space in this spectral range and altitudes is difficult.

Moreover, many SO2 point sources (cities, industrial areas, etc.) are much smaller in size than most instruments’ single pixel which makes the detection of their emissions even harder. Even localized enhancements of boundary layer SO2 due to industrial emissions, which can increase the total column by a factor of 10 or more, are not easily discernible. However, episodic injection of SO2 by volcanic eruptions can produce total SO2 columns whose values range from 10% of the total ozone column to more than twice the total ozone column (Krueger, 1983; McPeters et al., 1984). For this reason scientists have focused from the very beginning on large volcanic eruptions and have used SOI just to quantify SO2 amounts originating from eruptive volcanic activity. Hence, SOI is generally used to characterize the accuracy of the ozone total column measurements and for areas away from volcanic activity SOI values have no physical meaning. In this paper we present results from total SO2 column measurements from a Brewer spectrophotometer at the city of Thessaloniki, Greece (40.63 N, 22.96 E) for the 25 years time period from April 1982 to March 2007. Several time periods were studied in order to quantify the SO2 levels above the city, to find any possible epochal and other trends and examine whether the measurements were sensitive enough to capture the enhancement of SO2 total load in the months that followed the great El Chicho´n volcanic eruption and hence confirm previous studies which showed that the volcanic plume spread even to the mid-latitudes and affected the atmospheric SO2 content there. The SO2 levels above Thessaloniki are compared to SO2 levels above five regions of the European Union and two regions in India. The European sites include two cities with around 5.5 million inhabitants (Madrid, Rome), two non-urban mountainous regions (Arosa, Hohenpeisseberg) and a non-urban region of low altitude situated close to an urban environment (de Bilt). The Indian sites include a large metropolitan area with more than 14 million inhabitants in the northern region of the country (New Delhi) and a non-urban mountainous region in the southern part of the country (Koidankanal). Previous studies provided evidence for transboundary transport of SO2 to the atmosphere above Thessaloniki from regions to the north of Greece (Zerefos et al., 2000). Thus, we can assume that a great portion of the SO2 above the city is located above the boundary layer and can therefore be detected by satellite instruments. Adopting the SOI from the Nimbus 7 TOMS instrument aboard Nimbus 7 satellite, Earth Probe TOMS aboard Earth Probe, and Ozone Monitoring Instrument (OMI) aboard EOS Aura as a measure of the amount of SO2 in the free atmosphere, we analyzed whether SOI’s relative changes can give an indication of changes in the SO2 total column above the city by correlating ground-based measurements and satellite observations. Then, the application of the method to the other seven stations is further discussed. Recent, more sophisticated algorithms, like the Band Residual Difference algorithm (Krotkov et al., 2006) which takes advantage of OMI’s full spectral coverage using the optimal wavelengths for the detection of SO2, allow the direct retrieval of the SO2 total column. However, we argue that the investigation of SOI remains of particular interest because we can take advantage of the long TOMS time series. 2. Data sets and algorithms 2.1. SO2 total column from Brewer spectrophotometers The ground-based observations used in this study comprise daily mean values of the measured SO2 total column in matm-cm (Dobson units (DU)) from Brewer spectrophotometers. Measurements of the direct solar irradiance at four wavelengths (310.1, 313.5, 316.8 and 320.1 nm) are used to derive the ozone total

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column with the use of the Kerr algorithm (Kerr et al., 1980). Then, from the direct solar irradiances at 306.3, 316.8 and 320.1 nm and the initially derived ozone total column, the SO2 total column is deduced applying the same algorithm again. This procedure may lead to negative SO2 total column values when low amounts of SO2 are present in the atmosphere. Even though these negative values have no physical meaning they are typically included in the data sets, since such values indicate very low total SO2 levels. The daily data are available to the scientific community through http://www. woudc.org, the online data base of the World Ozone and Ultraviolet Data Center (WOUDC). We used direct sun measurements for eight stations in total. The data from Thessaloniki station were spectrally retrieved by the MKII 005 Brewer Spectrophotometer of the Laboratory of Atmospheric Physics that is situated in the center of the city at 40.63 N, 22.96 E (Zerefos et al., 1986; Bais et al., 1993). Data are available for the time period April 1982–March 2007. The SO2 levels measured with Brewer spectrophotometers above seven stations with different geolocation and population characteristics were compared to the SO2 record of Thessaloniki. We included two urban European stations in Rome, Italy and Madrid, Spain with a population of five times the population of Thessaloniki, two non-urban mountainous European stations in Arosa, Switzerland and Hohenpeissenberg, Germany, a non-urban but near urban environment station in De Bilt, the Netherlands, an urban station in New Delhi, India, situated in the greater Delhi area with a population of 14 million people and a non-urban mountainous station in Kodaikanal, India. In Table 1 we summarize the geolocation of all the stations, some of their special characteristics, the type of the Brewer spectrophotometers at each station and the time periods for which the ground-based observations were considered. Each time period was selected in order to have 12-month years for each station. 2.2. Sulfur Dioxide Index – SOI from Nimbus 7 TOMS, Earth Probe TOMS and OMI The Version 8 TOMS SOI of Nimbus 7 TOMS, Earth Probe TOMS and EOS Aura OMI are available to the scientific community through http://toms.gsfc.nasa.gov/ n7toms/nim7toms_v8.html (TOMS data base), http://toms.gsfc.nasa.gov/eptoms/ep_v8.html (TOMS data base) and http://toms.gsfc.nasa.gov/omi/omi_data_ access.html (Aura Validation Data Center-AVDC) respectively. We used overpass data for the city of Thessaloniki and the other seven stations mentioned previously. Nimbus 7 TOMS operated for the time period from November 1978 to May 1993 while the Earth Probe TOMS data span from July 1996 until December 2006 and the OMI data set from August 2004 onwards. The time periods for which the satellite observations were analyzed along with the months characterized by a systematic lack of data are given in Table 2. Those months that typically lack data are primarily in the middle latitudes during winter time, due to meteorological characteristics, such as heavy cloudiness, that affect the retrievals.

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The satellite instruments discussed in this work do not share exactly the same special characteristics such as measuring wavelengths, orbit, single pixel size and overpass frequency. We give in the following a short description of these special characteristics and the differences between the instruments. Nimbus 7 TOMS is a single fixed monochromator measuring backscattered radiance at six near-UV wavelengths (312.34, 317.35, 331.06, 339.66, 359.88, 379.95 nm). The instrument was placed in a sun synchronous orbit at an altitude of 955 km with an instantaneous field of view of 50  50 km2 at nadir. Global coverage was achieved within one day since consecutive orbits overlapped to create a contiguous mapping. Essentially, Nimbus 7 TOMS and Earth Probe TOMS are the same type of instrument, with four of the Earth Probe TOMS wavelengths being nearly the same as four of the Nimbus 7 TOMS wavelengths (312.6, 317.5, 331.2, 360.4 nm) while the other two wavelengths (308.60, 322.3 nm) are different. The Earth Probe TOMS is also in a sun synchronous orbit at an altitude of 740 km with an instantaneous field of view size of 39  39 km2 at nadir and a daily coverage of 85% in the tropics. Earth Probe TOMS measurement noise is significantly lower compared with Nimbus 7 TOMS measurement noise. OMI aboard the EOS AURA satellite is a UV/VIS nadir solar backscatter spectrometer which was set in a sun synchronous polar orbit at an altitude of 705 km. Unlike the two previous TOMS instruments described above, OMI can measure the complete spectrum in the 270–500 nm wavelength range with a spectral resolution of w0.5 nm (Levelt et al., 2006). OMI observes the Earth and its atmosphere with daily global coverage and a high spatial resolution of 13  24 km2 at nadir. In general, OMI is characterized by its higher accuracy due to its better spatial resolution and the lower measurement noise compared with the TOMS instruments. The SOI is derived from spectral measurements of the satellite instruments TOMS and OMI applying the Version 8 TOMS algorithm. As mentioned in Section 1, SOI is a by-product of the algorithm used for ozone total column estimate, constituting an index that qualifies the ozone measurements in respect to SO2. Initially, the total ozone column Uo is estimated using radiance measurements at 317.5 nm and 331 nm. Using these values and a radiative transfer model, the algorithm derives a theoretical value (No) for N (see Eq. (1)):

N ¼ 100 log10 ðI=FÞ

(1)

where I is the radiance of the backscattered radiation coming from the coupled earth–atmosphere system and surfaces (clouds, water and land surfaces, etc.) and F is the solar irradiance at the top of the atmosphere. The measured value for N is derived using the spectral measurements from the different instruments (Nm). Theoretically, Nm and No should be equal but are typically different since factors like strongly absorbing aerosols, sea glint, snow or ice cover and calibration errors of the instruments affect the measurements’ quality. Because of these effects on the backscattered radiation and because of the simplifications used in its derivation, including

Table 1 Geographical coordinates and altitude of the ground-based locations, population of the surrounding area, type of the Brewer spectrophotometers at each station and time period of the ground-based measurements. Station

Coordinates

Altitude (m)/population

Brewer type

Measurement period

Arosa, Switzerland De Bilt, the Netherlands Hohen/berg, Germany Kodaikanal, India Madrid, Spain New Delhi, India Rome, Italy Thessaloniki, Greece

40.77 N, 9.67 E 52.00 N, 5.18 E 47.80 N, 11.02 E 10.23 N, 77.47 E 40.40 N, 3.68 W 28.67 N, 77.22 E 41.88 N, 12.50 E 40.63 N, 22.96 E

1840/w2300 1/w14800 975/– 2343/w33000 548/w5600000 220/w13800000 0/w5500000 50/w1060000

MKII 040/072 MKIII 100 MKII 010 MKIV 094 MKIV 070 MKIV 089 MKIV 067 MKII 005

April 1989–March 2007 January 1994–December 2004 June 1984–May 2007 March 1994–February 2004 May 1992–April 2002 August 1994–July 2002 January 1992–December 2006 April 1982–March 2007

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Table 2 Nimbus 7 TOMS, Earth Probe TOMS and OMI SOI measurement time period for each station (months with a systematic lack of data are also presented). Station

SOI: Nimbus 7 TOMS

SOI: Earth Probe TOMS

Arosa, Switzerland Months with no data De Bilt, The Netherlands Months with no data Hohen/berg, Germany Months with no data Kodaikanal, India Madrid, Spain New Delhi, India Rome, Italy Months with no data Thessaloniki, Greece

June 1979–May 1993 December June 1979–May 1993 Jan./Nov./Dec. June 1979–May 1993 January/December June 1979–May 1993 June 1979–May 1993 June 1979–May 1993 June 1979–May 1993 – June 1979–May 1993

January 1997–December January/December January 1997–December Jan./Nov./Dec. January 1997–December January/December January 1997–December January 1997–December January 1997–December January 1997–December – January 1997–December

the parameterization of atmospheric properties used as input to the radiative transfer computations and limitations in the way the computations represent the physical processes in the atmosphere, the initial ozone estimate will not be equal to the true ozone value. From r values at three different wavelengths and a fourth wavelength lR to calculate the effective reflectivity of an assumed Lambertian surface accounting for all the surfaces such as clouds, land, oceans, snow and ice, a new corrected value U can be calculated for the ozone total column and also the SOI as a by-product (McPeters et al., 1996, 1998). We use 312.34, 317.35, 331.06, 359.88 nm wavelengths from Nimbus 7 TOMS and 317.5, 322.3, 331.2, 360.4 nm wavelengths from Earth Probe TOMS and OMI. Generally, lR equals 331.06 nm for Nimbus 7 TOMS and 331.2 nm for Earth Probe TOMS and OMI at low solar zenith angles but switches to 359.88 and 360.4 nm correspondingly when the ozone absorption at 331.06 and 331.2 nm becomes too large. Generally, SOI expresses an estimate of the SO2 total column which leads to a deviation between Nm and No in cases of strong volcanic SO2 injection and has been used to flag total ozone measurements. In case of low atmospheric SO2 content SOI values have no obvious physical meaning. The index, depending on the satellite instrument, may take both positive and negative values. It was previously mentioned that Nimbus 7 TOMS and Earth Probe TOMS are more or less the same type of instrument, however, the wavelengths used for the calculation of SOI are partly different. Despite the fact that OMI and Earth Probe TOMS share the same wavelengths for the calculation of SOI the special characteristics of the two instruments differ. As mentioned in the previous paragraph OMI measurements are characterized by higher accuracy and stability due to the instrument’s better spatial resolution and the lower measurement noise compared with the TOMS measurements. All these differences have an impact on the SOI values which should presumably be investigated separately for each instrument. The TOMS SOI values are both negative and positive but the negative ones generally out number. On the contrary, the OMI SOI values are primarily positive. SOI’s relative changes may include information about the SO2 variability. It is this variability that renders SOI interesting for this study and not the absolute SOI values per se. The scientific question we hence attempt to answer in the following is whether the SOI can be used as a proxy for the long-term and seasonal SO2 variability of areas away from eruptive volcanic activity. 3. Results and discussion 3.1. SO2 total load estimated from Brewer spectrophotometers From ground-based observations we have estimated that the daily mean SO2 total column values over Thessaloniki range between a minimum of 4 DU and a maximum of 13.9 DU with an

SOI: OMI 1999

September 2004–August January/December September 2004–August January/December September 2004–August January/December September 2004–August September 2004–August September 2004–August September 2004–August December September 2004–August

1999 1999 1999 1998 1999 1999 1999

2006 2006 2006 2006 2006 2006 2006 2006

overall mean of 1.717  1.100 DU for the time period April 1982– March 2007. For a typical non-urban alpine region in the center of Europe with zero background SO2 load like Arosa, the daily mean SO2 total column ranges between a minimum of 7.5 DU, i.e. no SO2 and a maximum of 13.1 DU, with an overall mean of 0.346  0.814 DU for the time period April 1989–March 2007. New Delhi has the highest overall mean value calculated from the monthly mean SO2 total column followed by Thessaloniki, Kodaikanal, Hohenpeissenberg, Madrid, De Bilt, Rome and Arosa. The mean SO2 levels above all the stations under investigation are given in Table 3. The Brewer spectrophotometers are designed to measure primarily the atmospheric ozone content while the retrieval of sulfur dioxide is a side product of these measurements. Hence, a significant uncertainty is expected for the SO2 values measured as discussed in detail by Fioletov et al. (1998). However, mean values calculated for extended periods of time are considered indicative of the SO2 loading and can be used for comparisons between different stations. 3.2. SO2 temporal variability over Thessaloniki The annual variability of the SO2 total column above Thessaloniki, shown in Fig. 1, is characterized by periods of higher and lower SO2 levels. The linear fit applied to the annual mean SO2 total column values, also shown in Fig. 1, confirmed that the total SO2 levels above Thessaloniki have decreased by 0.028 DU/year. For the time period from 1983 to 2006 the years with the lowest and highest annual mean SO2 total column are 2006 (1.002  0.955 DU) and 1990 (2.290  1.012 DU), respectively. Only years with a full 12-month data set were included in this analysis. A very high annual mean SO2 total column was seen in1982 (2.298  1.190 DU) Table 3 Overall mean SO2 total column (Brewer) and SOI (Nimbus 7 TOMS, Earth Probe TOMS, OMI) calculated from the corresponding monthly mean SO2 total column and SOI time series. Station

SO2 total column (DU): Brewer

Arosa, Switzerland De Bilt, The Netherlands Hohen/berg, Germany Kodaikanal, India Madrid, Spain New Delhi, India Rome, Italy Thessaloniki, Greece

0.354  0.619 1.152  2.724 1.248  1.008

3.105  0.933

0.304  0.763 0.881  2.663 0.824  0.882

2.730  0.824

0.551  0.556 2.116  2.322 0.652  1.509

2.785  0.844

1.745  0.880 1.338  1.533 2.260  1.815

1.479  1.121

SOI: Nimbus 7 TOMS

SOI: Earth Probe TOMS

SOI: OMI

0.454  0.941 2.133  1.989 1.879  1.621 1.665  1.121 3.593  3.158 0.864  2.847 4.388  1.656 0.830  1.631 0.182  1.802 1.479  2.136 1.992  1.523 1.753  0.633 1.665  2.037 1.720  1.588

2.306  1.050 2.926  1.155

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Fig. 1. Annual variability of the Brewer SO2 total column above Thessaloniki, Greece for the time period 1983–2006. The linear fit shows the general decrease of the columnar SO2 above the city with a rate of 0.028 DU/year.

but this year was not included in the investigation of the annual variability since the ground-based data set starts from April 1982. For the same reason we excluded data from the year 2007 as ground-based data are only available until March 2007. The seasonal variability of the SO2 total column over Thessaloniki, shown in Fig. 2, exhibits a double peak structure. There are two discrete periods, henceforth called a cold and a hot period. Generally, the highest values appear during the January–February– March cold period while a second lower peak appears during the July–August hot period. The cold peak can be attributed to oil burning central heating systems widely used during the winter in Greece. February is the month with the highest overall monthly mean SO2 total column for the whole time record (2.097  1.393 DU) followed by January (1.929  1.212 DU) and March (1.911  1.271 DU). Low monthly mean values are to be expected for August and July due to high temperatures and less traffic in the center of the city during the summer holiday period. June is the month with the minimum overall monthly mean SO2 total column (1.448  0.964 DU) while contrary to what would be

Fig. 2. Seasonal variability of the Brewer SO2 total column for the time period April 1982–March 2007 for the city of Thessaloniki, Greece. Upper panel, including the standard deviation; lower panel, without the standard deviation and zoomed view.

expected July (1.730  1.061 DU) and August (1.670  1.103 DU) show high overall monthly mean values. According to previous studies the July–August peak can be attributed to the synoptic transport of SO2 from areas inside but mainly outside Greece (Zerefos et al., 2000). SO2 has a lifetime of 1–2 days inside the boundary layer of urban areas and about 4 days for non-urban areas, and can be transported even for hundreds of kilometers before its total depletion. Zerefos et al. (2000) examined the appearance of high values of SO2 total column during July and August and showed that local sources contribute primarily to the surface concentrations. According to them, about 40% of the mean summer columnar SO2 over Thessaloniki originates from national sources, including lignite-burning power stations west of the city, while 60% originates from trans-boundary transport from ligniteburning sources in Bulgaria, Romania and the former Yugoslavia. The latter contribution may rise to about 80% during north-east flow conditions. These results confirmed independent satellite observations from the Global Ozone Monitoring Instrument (GOME) (Eisinger and Burrows, 1998). As discussed above, 1982 was a year with a comparably high annual mean SO2 total column. Also, 1983 was exceptional, being the year with the third highest value from 1983 to 2007. These high levels could possibly be attributed to the 1982 El Chicho´n great volcanic eruption. Previous studies showed that the volcanic plume spread even to the mid-latitudes and affected SO2 measurements there. Here, we investigate whether Brewer measurements were sensitive enough to capture this already recorded enhancement of the SO2 total load during the months that followed the eruption. El Chicho´n, located in southern Mexico (17.3 N, 95.2 W), is responsible for the second largest volcanic eruption of the 20th century on the 4th of April 1982, after 8 days of intense volcanic activity. Satellite observations showed that El Chicho´n’s cloud had spread mainly over the Northern Hemisphere up to about 30 N until June 1982 (Barth et al., 1983). Hofmann and Rosen (1983) used balloon measurements to detect traces of the volcanic eruption over Laramie, US (41 N, 105.5 W) during the summer of 1982. Their results were confirmed by ground-based observations in northern Greece (Zerefos, 1984). Lidar measurements indicating the presence of the volcanic cloud in Frascati (near Rome), Italy, were made in May 1982 (Adriani et al., 1983). Our analysis showed that monthly mean SO2 total columns from May to November 1982 were higher than the corresponding overall monthly means for the period from April 1982 to March 2007. The same period in 1983 showed mostly lower

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values than in 1982, except for July and August. The highest monthly mean SO2 total column of 4.065  1.052 DU was measured in September 1982. The high total SO2 values which are in agreement with previous studies and the decrease during the months of 1983, may be indicative of the presence of volcanic SO2 above Thessaloniki. However, an inconclusive volcanic SO2 effect cannot be claimed. Since the annual cycle of the SO2 total column is dominated by central heating during the cold period and synoptic transport during the hot period of the year, meteorological conditions (temperature, wind speed and directions, etc.) could also be responsible for the aforementioned high values and the differences between 1982 and 1983. 3.3. SOI levels at selected sites In this section we examine the SOI levels retrieved from different satellite instruments over areas without permanent volcanic activity. SOI values of Nimbus 7 TOMS and Earth Probe TOMS over Thessaloniki are generally negative while OMI on the other hand gives positive SOI values. Furthermore, the measurements’ noise decreases considerably from Nimbus 7 TOMS to Earth Probe TOMS and from Earth Probe TOMS to OMI. SOI values retrieved from Nimbus 7 TOMS for Thessaloniki range between a minimum of 25 and a maximum of 23 with an overall mean of 1.66  6.30 for the time period June 1979–May 1993. Earth Probe TOMS SOI values range between a minimum of 14 and a maximum of 11 with an overall mean of 2.19  3.58 for the time period January 1997– December 1999 while OMI SOI values range from 10 to 10 with an overall mean of 2.70  2.40 for the time period September 2004– August 2006. We used measurements from Earth Probe TOMS just for the period 1997–1999 since measurements after 2000 are not considered reliable due to serious calibration issues. In the three right-most columns of Table 3 we have summarized the SOI levels for all the 8 stations following the method explained in Section 3.1. The classification of the stations with respect to SOI levels differs from instrument to instrument and from the classification using WOUDC’s ground-based observations. 3.4. SOI temporal variability over Thessaloniki In this section the temporal variability of the SOI over Thessaloniki is presented for the three satellite instruments. The annual variability of Nimbus 7 TOMS SOI for the full year time period

1980–1992 along with the SOI monthly means for the whole time record (June 1979–May 1993) are shown in Fig. 3. For the same period SOI levels above Thessaloniki strongly increased from 1980 to 1985 and decreased thereafter. The relative changes of the annual mean SOI values do not follow the corresponding mean SO2 total column values. Especially in 1982, the year of the powerful volcanic eruption of El Chicho´n, there are no particularly high annual and monthly mean values. It is therefore likely that there was almost no effect of the eruption of El Chicho´n on the SOI values derived from Nimbus 7 TOMS. The annual and monthly SOI means from Earth Probe TOMS and OMI, also shown in Fig. 3, primarily take negative values for Nimbus 7 TOMS and Earth Probe TOMS and positive for OMI. The annual mean standard deviation bars are indicative of the significant decrease of the measurement noise from sensor to sensor. The seasonal variability of SOI from Nimbus 7 TOMS, shown in Fig. 4a, is characterized by three distinct periods, two cold ones and one hot, for the 14 years between June 1979 and May 1993. The highest values appear during the February–March period with lower values during the May–June–July–August and October– November–December periods. The basic difference with groundbased observations is the fact that Nimbus 7 TOMS gives very low SOI values during January. The seasonal variability of the Earth Probe TOMS SOI for the time period January 1997–December 1999 is characterized by high winter values and low summer values, August being the month with the lowest SOI values (Fig. 4b). The seasonal variability of SOI from OMI for the period September 2004–August 2006 (Fig. 4c) exhibits a double structure with two distinct periods. The highest values appear during the December– March period while a second lower peak appears during the May– June–July period. Comparison of Fig. 4a, b and c reveals that the variability of SOI is much stronger for the Earth Probe TOMS observations than the Nimbus 7 TOMS and OMI observations. 3.5. Correlation of ground-based and satellite observations The study of the seasonal variability of SOI and the time series of the daily and the monthly mean SOI values for the station of Thessaloniki showed that the relative changes of SOI partly follow the corresponding changes of the SO2 total column. We therefore analyzed whether SOI may indicate the SO2 total load for the city of Thessaloniki through its relative changes. Our efforts to correlate daily measurements of the SO2 total column with daily

Fig. 3. Annual means of the Nimbus 7 TOMS, Earth Probe TOMS and OMI SOI for Thessaloniki, Greece. The grey squares represent the monthly mean values.

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Fig. 4. Seasonal variability of (a) Nimbus 7 TOMS SOI for the time period June 1979– May 1993, (b) Earth Probe TOMS SOI for the time period January 1997–December 1999 and (c) OMI SOI for the time period September 2004–August 2006. Upper panel, standard deviation included; lower panel, without the standard deviation and zoomed view.

measurements of SOI failed for all the three instruments, which indicate that SOI is not suitable to detect day-to-day variability of SO2. This was partly expected since the sensitivity of the TOMS and OMI instruments with respect to SO2 in the boundary layer is generally limited. For example, a set of SO2 retrievals from Nimbus 7 TOMS for an area without volcanic SO2 contamination has a standard deviation (s) of 6. The measurement noise for Earth Probe TOMS and OMI is much lower but still considerable, since, as it is shown here, none of the instruments can capture the daily variability of the SO2 load. In order to reduce the measurement noise we tried to correlate monthly mean SO2 total column values with monthly mean SOI values. Observations from the Brewer spectrophotometer correlate linearly only with the observations from OMI with a low correlation coefficient (R) of 0.467 (Fig. 5a). There were 24 common months of measurements in our data sets for the time period September 2004– August 2006 which is interpreted to 24 data points. We also calculated an overall SO2 total column mean and an overall SOI mean for each month of the year which is interpreted to 12 values for each instrument. We refer to these mean values as overall monthly mean values. Overall monthly mean total SO2 values are correlated with overall monthly mean SOI values from Nimbus 7 TOMS (Fig. 5b) and OMI (Fig. 5c) with correlation coefficients of 0.710 and 0.736

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Fig. 5. (a) Correlation of ground-based monthly mean SO2 total columns (Brewer) and the monthly mean OMI SOI for the station of Thessaloniki, Greece. The solid line represents the linear regression fit applied (24 common months). The regression line is expressed by SO2 ¼ 0.2909( 0.1174)SOI þ 0.7332( 0.3682) and the correlation coefficient is R ¼ 0.467. (b) Correlation of ground-based overall monthly mean SO2 total columns (Brewer) and the overall monthly mean Nimbus 7 TOMS SOI for the station of Thessaloniki, Greece. The solid line represents the linear regression fit applied (data of 12 months). The regression line is expressed by SO2 ¼ 0.3737( 0.1172)SOI þ 2.4687( 0.1476) and the correlation coefficient is R ¼ 0.710. (c) Correlation of ground-based overall monthly mean SO2 total columns (Brewer) and the overall monthly mean OMI SOI for the station of Thessaloniki, Greece. The solid line represents the linear regression fit applied (data of 12 months). The regression line is expressed by SO2 ¼ 0.3006( 0.0873)SOI þ 0.6992( 0.2722) and the correlation coefficient is R ¼ 0.736.

respectively. From these figures we see that in particular cases the SO2 total column levels above Thessaloniki can be estimated using corresponding SOI levels. On the contrary, overall monthly mean ground-based observations do not correlate significantly with overall monthly mean Earth Probe TOMS observations. In order to connect those cases where ground-based observations correlate satisfactorily with satellite observations with the existence of high SO2 levels, we calculated overall mean SO2 total columns from the monthly mean time series referring to BrewerNimbus 7 TOMS (2.0180.592), Brewer-Earth Probe TOMS (1.529  0.497) and Brewer-OMI (1.584  0.719) measurement coincidence time period. The relatively high SO2 total load over Thessaloniki during the Brewer-Nimbus 7 TOMS measurement period could be partly responsible for the satisfactory correlation of the Brewer and Nimbus 7 TOMS overall monthly mean observations. The SO2 total load drops down by almost half a DU during the

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Brewer-Earth Probe TOMS and Brewer-OMI measurement periods, as was expected from the annual reduction already seen in the trend analysis presented before. Brewer and Earth Probe observations do not correlate significantly which may be attributed to the decrease of the SO2 total content. The significant correlation of the Brewer and OMI overall monthly mean observations, despite lower SO2 levels, could be attributed to the instrument’s comparably high sensitivity. One should however take into account that all satellite instruments primarily detect SO2 amounts situated above the boundary layer. The presence of SO2 transport in upper tropospheric levels could therefore be partly responsible for the satisfying correlation between ground-based and satellite observations. We tried to apply the same methodology in order to examine the data from the other seven stations. Unfortunately, for several stations there were months that systematically lacked corresponding ground-based and satellite measurements. It has to be emphasized that only correlation coefficients based on 12 common months could be regarded as being representative of the yearly distribution. We therefore focused only on observations for stations with 12 common months of ground-based and satellite measurements. From these stations, only for Madrid and despite the low SO2 content (0.351  0.912 DU) during the Brewer-Earth Probe TOMS period the overall monthly mean SO2 total column values from the Brewer instrument correlate satisfactorily with corresponding SOI values from Earth Probe TOMS with a correlation coefficient (R) of 0.691. The special characteristics of the SO2 total column levels and seasonal variability over Madrid have not been previously studied. Studies have only focused on the analysis of near surface concentration measurements showing a very strong seasonal variation with higher values during the cold period (November–February) and much lower values during the hot period (May–August) ˜ ano (Herna´ndez et al., 1983; Ferna´ndez-Jimene´z et al., 2003; Artı´n et al., 2003). According to Ferna´ndez-Jimene´z et al. (2003) the SO2 near surface concentrations are comparably low due to the application of a strict emission policy from the local administration. For the time period we study, the principal emission sources for the area of Madrid were combustion in manufacturing industry (52%), non-industrial combustion plants (28%) and road traffic (18%) according to Lumbreras et al. (2002). Trans-boundary transport of SO2 has not been recorded from previous studies, therefore the SO2 levels above the city are considered to be primarily of local origin. The higher winter concentrations are mostly attributed to central domestic and administrative installations, usually coal or fuel-oil ˜ ano et al., 2003). The seasonal variability of the surface fed (Artı´n concentrations in Madrid is partly determined by the special climatological, synoptic and topographic characteristics of the area. Madrid is located in the center of the Iberian Peninsula within an airshed bordered to the north-northwest by a high mountain range and to the northeast and east by lower mountainous terrain. The climate of the area is continental with dry and hot summers and cold winters with cloudless skies. During summer, the development of strong thermal convective activity and the influence of the mountains favor the dispersion of atmospheric pollutants (Crespı´ et al., 1995). During winter and autumn, atmospheric pollution episodes are rather common, linked to stagnant anticyclone conditions. Anticyclonic stagnation can lead to surface thermal inversions impeding the dispersion of atmospheric pollutants and preventing polluted air masses from being transported to the free ˜ ano et al., 1994). However, under normal troposphere (Artı´n conditions in the presence of solar insolation, heating of the ground by the sun leads to the development of a convective boundary layer. The turbulent eddies formed by the convection mix the pollutants throughout the layer. Under such conditions a fraction of the atmospheric SO2 can be transported above the boundary layer. The

overpass time of Earth Probe TOMS over the area of Madrid is around local noon (w11UTC) when the dispersion is expected to be vigorous. This situation favors the detection of SO2. The seasonal variability of the SO2 total column from the Brewer observations and the SOI values from the Earth Probe TOMS observations follows the variability of the near surface SO2 concentrations recorded from previous works. This shows that Earth Probe TOMS is able to record the SO2 total column enhancements coming from central heating systems operated during the cold period. The case of Madrid differs from that of Thessaloniki because of the low SO2 levels and the local character of the SO2 emissions. Significant trans-boundary SO2 transport has not been recorded and despite the fact that a fraction of the SO2 can be transported above the boundary layer, the winter conditions are not the most favorable for such a transport. However, in both cases there is a very strong seasonal variability with a winter peak due to the use of heating systems and lower values during the summer. It can be inferred that a strong seasonal variability could be partly responsible for the satisfying correlation between ground-based and satellite observations. In addition, Madrid’s cloudless conditions favor the detection of SO2 from space. Hence, summarizing we could say that SOI may act as an indicator of the atmospheric SO2 content and its seasonal variability, depending on the satellite instrument sensitivity, favorable observation conditions, the presence of SO2 above the boundary layer and the strength of the seasonal variability. 4. Summary and conclusions Ground-based measurements from the MKII 005 Brewer Spectrophotometer at Thessaloniki, Greece, were studied for the time period from April 1982 to March 2007. An overall mean value of 1.717  1.100 DU was calculated for the SO2 total column while it was also shown that the total SO2 levels above Thessaloniki have generally decreased with a rate of 0.028 DU per annum. We found a seasonal variability of the SO2 total content above the city with two distinct periods during the winter and summer months. The cold period from January to March can be attributed to the wide use of oil burning heating systems during the Greek winters. The peak of July–August, in agreement with previous studies, can be attributed to lignite-burning power stations to the WSW of the city and trans-boundary transport from SO2 sources in Bulgaria, Romania and the former Yugoslavia. Our analysis of the Thessaloniki data and seven other stations in Europe and India revealed that mean SO2 levels over the city of New Delhi, India, are the highest, followed by Thessaloniki, Kodaikanal (India), Hohenpeissenberg (Germany), Madrid (Spain), De Bilt (The Netherlands), Rome (Italy) and Arosa (Switzerland). In this work SOI measurements from Nimbus 7 TOMS, Earth Probe TOMS and OMI satellite instruments for areas away from volcanic activity are presented for the first time. For the area of Thessaloniki, SOI values retrieved from Nimbus 7 TOMS (1.66  6.30) and Earth Probe TOMS (2.19  3.58) observations are generally negative while SOI values retrieved from OMI (2.70  2.40) observations are generally positive. The seasonal variability of SOI from Nimbus 7 TOMS is characterized by three distinct periods, two cold and one hot, for the 14 years time period June 1979–May 1993. The seasonal variability of Earth Probe TOMS SOI for the time period January 1997–December 1999 is characterized by high winter values and low summer values while SOI from OMI for the period September 2004–August 2006 shows a double peak structure with two discrete periods, a cold and a hot one. The comparison of SOI levels from Thessaloniki with SOI levels from the other seven stations reveals that the classification of the stations with respect to SOI measurements differs from instrument to

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instrument and from the classification using ground-based measurements. Our study showed that for Thessaloniki, Greece, seasonal relative changes of Nimbus 7 TOMS and OMI SOI partly follow the corresponding changes of the Brewer spectrophotometer’s SO2 total column results. Similar results were obtained for Earth Probe TOMS SOI and Brewer SO2 total column measurements for Madrid, Spain. We have demonstrated by correlating ground-based and satellite observations that in some cases the mean SO2 total column can be estimated using corresponding SOI levels. This work suggests that the relative changes of SOI could be used as an indicator of the SO2 total content under specific conditions. It depends on the sensitivity of the instruments with respect to SO2 in the boundary layer but also on favorable observation conditions, the presence of SO2 in higher atmospheric levels and the strength of the seasonal variability. The results presented here may act as a benchmark as the use of SOI could be applied rigorously in the future to detect tropospheric SO2 amounts over areas where ground-based data are not available. Acknowledgements The authors acknowledge the use of Nimbus 7 TOMS and Earth Probe TOMS Sulfur Dioxide Index data from TOMS NASA/GSFC database (http://toms.gsfc.nasa.gov/), OMI Sulfur Dioxide Index data from AVDC (http://avdc.gsfc.nasa.gov) and Brewer SO2 total column data from the WOUDC database (http://www.woudc.org). Special thanks are expressed to the anonymous reviewers whose comments and suggestions helped to substantially improve this manuscript. References Adriani, A., Congeduti, F., Fiocco, G., Gobbi, G.P., 1983. One-year lidar observations of the stratospheric aerosol at Frascati, March 1982–March 1983. Geophysical Research Letters 10, 1005–1008, ISSN 0094-8276. ˜ ano, B., Pujadas, M., Plaza, J., Crespı´, S.N., Cabal, H., Acen ˜ a, B., Tere´s, J., 1994. Air Artı´n pollution episodes in the Madrid airshed. In: Borrell, P.M., Borrell, P., Cvitas, T., Seiler, W. (Eds.), Transport and Transformation of Pollutants in the Troposphere SPB. Academic Publishing, pp. 294–297. ˜ ano, B., Salvador, P., Alonso, D.G., Querol, X., Alastuey, A., 2003. Anthropogenic Artı´n and natural influence on the PM10 and PM2.5 aerosol in Madrid (Spain). Analysis of high concentration episodes. Environmental Pollution 25, 453–465. Andreae, M.O., Jaeschke, W.A., 1992. Exchange of sulfur between biosphere and atmosphere over temperate and tropical regions. In: Howarth, R.W., Stewart, J.W.B., Ivanov, M.V. (Eds.), Sulfur Cycling on the Continents Systems and Wetlands. Wiley, Chichester, UK, pp. 27–61. Andres, R.J., Kasgnoc, A.D., 1998. A time-averaged inventory of subaerial volcanic sulfur emissions. Journal of Geophysical Research 103, 25251–25261. Bais, A.F., Zerefos, C.S., Meleti, C., Ziomas, I.C., Tourpali, K., 1993. Spectral measurements of solar UVB radiation and its relations to total ozone, SO2, and clouds. Journal of Geophysical Research 98, 5199–5204. Barth, C.A., Sanders, R.W., Thomas, R.J., Thomas, G.E., Jakosky, B.M., West, R.A., 1983. Formation of the El Chichon aerosol cloud. Geophysical Research Letters 10, 993. Bekki, S., 1995. Oxidation of volcanic SO2: a sink for stratospheric OH and H2O. Geophysical Research Letters 22, 913–916. Benkovitz, C.M., Scholtz, M.T., Pacyna, J., Tarrason, L., Dignon, J., Voldner, E.C., Spiro, P.A., Logan, J.A., Graedel, T.E., 1996. Global gridded inventories of anthropogenic emissions of sulfur and nitrogen. Journal of Geophysical Research 101 (D22), 29239–29253. ˜ ano, B., Cabal, H., 1995. Synoptic classification of the mixed-layer Crespı´, S.N., Artı´n height evolution. Journal of Applied Meteorology 34, 1666–1677. Dadi, Z., Xueyi, L., Huaqing, X., 1998. Estimate of Sulfur Dioxide Emissions in China in 1990 and 1995. Energy Research Institute, Beijing, China. Eisinger, M., Burrows, J.P., 1998. Tropospheric sulfur dioxide observed by the ERS-2 GOME instrument. Geophysical Research Letters 25, 4177–4180. Ferna´ndez-Jimene´z, M.T., Climent-Font, A., Sa´nchez Anto´n, J.L., 2003. Long term atmospheric pollution study at Madrid City (Spain). Water, Air and Soil Pollution 142, 243–260.

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