We have used total and diffuse UV irradiance measurements from a multi-filter rotating shadow-band radiometer (UVMFR) in order to investigate aerosol absorption in the UV range for a 5-year period in Athens, Greece. This dataset was used as input to a radiative transfer model and the single scattering albedo (SSA) at 368 and 332 nm was calculated. Retrievals from a collocated CIMEL sun photometer were used to evaluate the products and study the absorption spectral behavior of retrieved SSA values. The UVMFR SSA, together with synchronous, CIMEL-derived retrievals of SSA at 440 nm, had a mean of 0.90, 0.87 and 0.83, with lowest values (higher absorption) encountered at the shorter wavelengths. In addition, noticeable diurnal variation of the SSA in all wavelengths is shown, with amplitudes up to 0.05. Strong SSA wavelength dependence is revealed for cases of low Ångström exponents, accompanied by a SSA decrease with decreasing extinction optical depth, suggesting varying influence under different aerosol composition. However, part of this dependence for low aerosol optical depths is masked by the enhanced SSA retrieval uncertainty. Dust and brown carbon UV absorbing properties were also investigated to explain seasonal patterns.
The role of aerosols, both natural and anthropogenic, is of high importance for regional and global climate change studies, as well as for pollution mitigation strategies (e.g., IPCC, 2013). However, a considerable amount of work still needs to be carried out in this field, as aerosols may have highly complex impact at local, regional and global climate scales. Furthermore, the components controlling aerosol forcing account for the largest uncertainties in relation to anthropogenic climate change (IPCC, 2013). A comprehensive review of the assessment of the aerosol direct effect, its state of play as well as current outstanding issues is provided by IPCC (2013) and Yu et al. (2006). Both studies emphasize that significant uncertainties in modeled single scattering albedo (SSA) retrievals constitute one of the largest single sources of uncertainty in current modeling estimates of aerosol climate forcing. SSA is the ratio of scattering to total extinction (scattering plus absorption), and it depends strongly on the chemical composition, size and mixing state of particles, as well as on relative humidity and wavelength. Comprehensive measurements are crucial to understand the aforementioned effects and to reduce SSA uncertainties, which in turn propagate into aerosol radiative forcing estimates. For example, for the same aerosol load (aerosol optical depth – AOD), the absorbing nature of aerosols can result to up to 50 % decrease in the erythemal irradiance compared to only scattering aerosols (Bais et al., 2014). It should be noted that SSA calculated in this study differs from in situ SSA values retrieved from absorption and scattering measurements at a single altitude level (e.g., at the ground). Thus, the SSA measured by sun-photometric measurements links with the radiation attenuation from aerosols in the whole atmospheric column.
In the visible (VIS) and in the near-infrared (NIR) parts of the spectrum, advanced retrieval algorithms for microphysical aerosol properties have been developed in the framework of the Aerosol Robotic Network (AERONET) and the Skyradiometer Network (SKYNET; e.g., Dubovik and King, 2000; Nakajima et al., 1996). AERONET stations currently provide inversion-based column average SSA retrievals at the VIS and NIR wavelengths (i.e., 440, 670, 870, 1020 nm). In addition, surface direct and diffuse irradiances have been previously used to derive spectral AOD and SSA at visible and ultraviolet (UV) wavelengths (King and Herman, 1979; King, 1979; Petters et al., 2003; Eck et al., 1998; Krotkov et al., 2005b; Bais et al., 2005; Goering et al., 2005; Taylor et al., 2008; Kudo et al., 2008; Corr et al., 2009). As AERONET does not provide any information about SSA at UV, only a few publications dealing with aerosol absorption at UV wavelengths can be found (e.g., Eck et al., 1998; Krotkov et al., 2005a; Bais et al., 2005; Corr et al., 2009). Unlike AERONET, the SKYNET sun photometers (manufactured by Prede Co. Ltd., Japan) are able to retrieve SSA at the UV wavelengths (Khatri et al., 2016, and references therein).
It is envisaged that improvement in the measurement accuracy and in the general understanding of aerosol absorption at UV (and immediate derivatives like the SSA) in various scientific applications will contribute significantly to improving the accuracy of UV-related radiation forcing estimates. For example, desert dust particles (Alfaro et al., 2004) and soot produced by fossil fuel burning as well as urban transportation all strongly absorb UV radiation. However, the optical properties of other potential UV absorbers like organic, nitrate and aromatic aerosols are still poorly known (Jackobson, 1999). Torres et al. (2007), in an overview study of OMI aerosol products, summarized the algorithmic techniques of SSA satellite retrieval at 388 nm, which uses the spectral variability between 354 and 388 nm, the 388 nm reflectance and a selection of the aerosol type. These retrievals were compared to AERONET SSA at 440 nm and a root mean square error of 0.03 was found (Jethva et al., 2014). MFRSR UV SSA retrievals of carbonaceous aerosols have also been carried out in the Amazon basin (Mok et al., 2016). They reported that brown carbon shows negligible absorption at VIS wavelengths, but significant absorption and strong spectral dependence at UV wavelengths.
Bergstrom et al. (2003) showed that spectra of aerosol SSA obtained in different campaigns around the world differed significantly from region to region, but in ways that could be ascribed to regional aerosol composition. Moreover, results from air, ground and laboratory studies, using both radiometric and in situ techniques, show that the fractions of black carbon, organic matter and mineral dust in atmospheric aerosols play a role in the determination of the wavelength dependence of aerosol absorption (Russell et al., 2010). Jethva and Torres (2011) provided a satellite-based evidence of the spectral dependence of absorption of biomass-burning aerosols over South America, using near-UV measurements from the Ozone Monitoring Instrument OMI during 2005–2007. Barnard et al. (2008) and Corr et al. (2009), while investigating the variability of SSA in a field study in the Mexico City metropolitan area, found that SSA in the near-UV spectral range (300 to 400 nm) is much lower compared to SSA at 500 nm, indicative of enhanced absorption in the near-UV range. They suggested that absorption by elemental carbon, dust or gas alone could not account for this enhanced absorption, leaving the organic carbon component of the aerosol as the most likely absorber. Many other studies report that, in addition to dust, the absorbing organic carbon compounds can induce strong spectral absorption, increasing towards the shortest UV wavelengths. Sources of these light–absorbing organic carbon compounds (often called brown carbon) are various, e.g., biomass burning (e.g., Kirchstetter et al., 2004), urban smoke (e.g., Liu et al., 2015) and biogenic emissions (e.g., Flores et al., 2014).
Corr et al. (2009) presented a review of studies estimating SSA at different
wavelengths. For the visible part of the spectrum, two different approaches
have been introduced. The first (Dubovik et al., 2002) uses sky radiance
measurements in a matrix inversion technique to calculate various aerosol
microphysical properties. This methodology has been widely applied within
AERONET. The second (Eck et al., 2003; Kassianov et al., 2005)
proposes the use of radiative transfer model (RTM) calculations, using as
input measurements of AOD and the ratio of direct to diffuse irradiance at
specific wavelengths. However, in the case of SSA calculations at UV
wavelengths, enhanced measurement uncertainties, RTM input assumptions and
interference from absorption by other gases (O
Moosmuller et al. (2012) showed that iron concentration in mineral dust aerosols is linked to lower SSA at 405 nm compared to 870 nm, which could be a hint for the lowest SSA in the UV–VIS range during dust events. Medina et al. (2012) also found large variation in the UV range SSA in El Paso–Juarez, with lower values compared to the visible wavelengths, and showed that during heavily polluted days SSA can get as low as 0.53 at 368 nm. Another effort was made in Belgium to calculate SSA at lower UV wavelengths, using Brewer (direct and global spectral irradiance at UV range) measurements, revealing lowest values but high uncertainty (Nikitidou et al., 2013). Recently, Schuster et al. (2016) tried to distinguish aerosol types by their optical properties and assumed that dust particles have higher absorption at UV wavelengths. They used imaginary refractive index spectral dependence to separate from black carbon and infer hematite and goethite in the coarse mode. They found that dust particles containing hematite are highly absorbing in the UV region.
The implications of all aforementioned gaps in knowledge are multitude, as UV
solar radiation has a broad range of effects on life (UNEP, 2003; UNEP et al., 1998, 2007). It influences not only human beings (e.g., Diffey,
1991) but also plants and animals (e.g., Bornman and Teramura, 1993).
Furthermore, it causes degradation of materials and functions as a driver of
atmospheric chemistry. There are various studies linking changes of the UV
radiation field with changes in the scattering and absorption of aerosols in
the atmosphere (e.g., Zerefos et al., 2012; Balis et al., 2004; Reuder and
Schwander, 1999; Krzyścin and Puchalski, 1998). Such changes can be
comparable in magnitude to those caused by the decline in stratospheric ozone
(Elminir, 2007; Reuder and Schwander, 1999; Krotkov et al., 1998). As an
example, analysis of long-term UV time series at Thessaloniki, Greece, showed
a reduction of 7 % of AOD (305 nm) per decade, while at the same time the UV
irradiance increased by 9 % (after removing ozone column effect on it).
This could only be explained by change in the absorption characteristics of
aerosols in the area (Meleti et al., 2009). Moreover, UV variation induced by
changes in aerosol optical properties directly affect tropospheric
photochemistry, causing
increases in regional O decreases in regional O
There are several more scientific issues that may be clarified with accurate
knowledge of aerosol absorption properties.
Future scenarios for simulations of global UV levels are based on ozone recovery, having as their sole input the predicted future decline in columnar ozone. Furthermore, simulations of the observed reduction of anthropogenic aerosols in the atmosphere of the US and Europe, during the course of the last decade (den Outer et al., 2005), included only cloud and AOD changes in the characterization of potential UV trends. In this regard, changes in the absorbing properties of aerosols on a global scale would have a large effect on the uncertainty budget in any of the above simulations (WMO, 2003). For example, a decrease in aerosol absorption properties accompanied by an AOD decrease in Europe could lead to a significant acceleration of the calculated ozone decline related to UV upward trends (Kazadzis et al., 2009; Zerefos et al., 2012).
The discrepancies between ground-based UV measurements and satellite-derived (OMI, TOMS, GOME) data are directly related to aerosol absorption that is absent from current satellite retrieval algorithms (Tanskanen et al., 2007; Arola et al., 2005). It has been shown that enhanced aerosol UV absorption in urban areas can cause up to 30 % overestimation in the satellite-retrieved UV radiation (Kazadzis et al., 2009).
Radiative transfer algorithms, calculating surface UV irradiance, lack accuracy due to large uncertainties in the input parameters (e.g., ozone levels, aerosol composition and surface albedo) used in model calculations. It is well established that the major input source of uncertainty in radiative-transfer model is aerosol absorption (e.g., Van Weele et al., 2000). In particular, the direct radiative effect of aerosols is very sensitive to mid-visible SSA. For example, a change in SSA from 0.9 to 0.8 can often alter the sign of the direct effect (Yu et al., 2006). Furthermore, availability and quality of observational SSA data are not the same as for AOD (Krotkov et al., 2005a). This is compounded by the lack of information on the vertical profile of aerosol optical properties, such as the SSA on a global scale. Only a few case studies have dealt with such measurements and these are limited to local scales (Müller et al., 1999).
In this work, we adopt a methodology for the calculation of the UV SSA, which is based on the idea of Krotkov et al. (2005a, b) and Corr et al. (2009). The methodology, together with the retrieval tools used and the technical assumptions, is presented in Sect. 2. The results from UV SSA measurements and their comparison with synchronous AERONET retrievals in the visible range are presented in Sect. 3. Finally, discussion of the observed diurnal SSA patterns in Athens, SSA wavelength dependency as well as concluding remarks is presented in Sect. 4.
In this work we present calculations of the SSA at two independently
retrieved UV wavelengths, 332 and 368 nm, in Athens, Greece. The period of
measurements is from July 2009 to May 2014. The ground-based Atmospheric
Remote Sensing Station (ARSS) has been in continuous operation since February
2009 to monitor ground radiation levels and aerosol loadings over Athens
(Amiridis et al., 2009). ARSS is located on the roof of the Biomedical
Research Foundation of the Academy of Athens (37.9
UVMFR angular response function at the 368 nm channel, normalized to the ideal (cosine) angular response. Two sets of responses, one from the south to north scan and one from the west to east, are provided.
SSA is a key aerosol optical property and describes the portion of solar
irradiance that is scattered from the main direct beam passing through the
atmosphere. Changes in SSA influence mostly the diffuse radiation reaching
the Earth's surface, while its effect on direct radiation can be considered
negligible. SSA at a wavelength
Model calculations can be used for retrieving SSA when global and/or diffuse spectral irradiance, solar zenith angle (SZA), total column ozone and AOD are known (Krotkov et al., 2005b; Kazadzis et al., 2010; Ialongo et al., 2010; Corr et al., 2009; Bais et al., 2005). In our retrieval methodology we have used partly the basic approach that is described in detail in Corr et al. (2009) and Krotkov et al. (2005a, b). This approach is based on measurements of the direct to global irradiance ratios (DGR) and AODs measured with the UVMFR instrument in our case, which are used as the basic input parameters to the RTM, for the calculation of the SSA at 332 nm and 368 nm. These wavelengths are selected among the seven available due to their lowest ozone absorption (Paur and Bass, 1985). The advantage of this method is that the same detector and filter measure global and direct irradiance, thus there is no need for absolute irradiance calibration and raw voltage measurements (corrected for nighttime voltages and angular response) could be used.
Global irradiance measurements from the UVMFR have been used in order to
distinguish cloud-free conditions for each of the 1 min measurements.
Clouds are detectable in the measured UVMFR global irradiance (GI, at 368 nm)
since they cause larger variability than aerosols. To distinguish between
cloudy and cloud-free conditions, we have applied an updated version of the
method of Gröbner et al. (2001). The method is based on the comparison
of the measured global irradiance with radiative transfer calculations for
cloud-free conditions and quality assurance is checked with the following
criteria:
The measured GI has to lie within the modeled (cloud-free) GI for a range
of aerosol loads (AOD at 500 nm of 0.1 and 0.8, respectively), corresponding
to the 5th and 95th percentile of the AERONET data, for the examined
location and period. The rate of change in the measured GI with SZA has to be within the
limits depicted by the modeled cloud-free GI, otherwise the measurements are
assumed cloud contaminated. All measured GI values within a time window (d
If at least 85 % of the points in the time window meet the criteria, then the central
point is flagged as cloud free. In this study, we have allowed a tolerance
level of
Determination of cloudless 1 min measurements (red), from all measurements (blue) for a day with variable cloudiness in the afternoon.
ETC values at 368 nm, calculated using Langley plots of UVMFR measurements and using Cimel extrapolated AODs as input, for selected (low AODs and clear sky) days for the whole period.
Measurements of the diffuse and global irradiance from the UVMFR were used
to retrieve the direct irradiance at 332 and 368 nm. We used the AERONET
database to select days with very low AOD (< 0.1). For the urban
environment of Athens, such cases are related to northerly winds. In the
next step, we selected cloudless-sky half-days for determining
extraterrestrial Langley calibration constant (ETC) by applying the
Beer–Lambert law UVMFR direct voltage measurements. The
AODs at 332 and 368 nm were calculated using the selected UVMFR derived
ETC. In contrast to the Krotkov et al. (2005a) approach, we have not
transferred the CIMEL ETCs to the UVMFR measurements; instead, we have
independently calculated UVMFR-based AODs. Validation of the results was
performed based on synchronous UVMFR and CIMEL measurements. The mean AOD
calculated from the 1 min UVMFR measurements within
Comparison between the CIMEL and UVMFR retrieved AODs for synchronous measurements, at 332 nm (left panel) and 368 nm (right panel).
AOD differences between CIMEL and UVMFR at 368 nm as a function of solar zenith angle.
This comparison turns out to have Pearson product moment correlation
coefficient equal to 0.96 and 0.98, respectively, for the 332 and 368 nm
AODs. Mean differences were 0, with standard deviations 0.031 and 0.025
for the respective wavelengths, comparable with the CIMEL AOD retrieval
uncertainty (
In Fig. 5, AOD values were grouped into bins of 5
Applying the RTM, we calculated look-up tables (LUT) of the DGR values at
368 and 332 nm as a function of SZA, AOD, SSA, asymmetry factor (
LUT of direct to global ratio at 368 nm, as calculated for AOD 0.1
(left) and 0.8 (right) with respect to SZA (
Uncertainty estimate (color) for the SSA retrieval from UVMFR as a
function of AOD and SZA at 368 nm (left panel) and 332 nm (right panel). This
is based on DGR and AOD uncertainties. Superimposed, mean AODs for 2.5
The CIMEL sun photometer provides SSA inversion retrievals labeled as Level
1.5 and Level 2.0 data. Level 2.0 (L2) data are recommended by AERONET as
they have less uncertainty but they are restricted to measurement with
SZA > 50 Climatological studies at areas without large average annual AODs
or
cases of moderate to high aerosol episodes: as an example, for the urban
site of Athens the number of measurements is limited to an average of 11
cases per month, for the whole analysis period. Diurnal variation studies due to the SZA restriction. For mid- and low-latitude sites, this limitation leads to a crucial lack of information on
diurnal SSA patterns, as there are only few wintertime measurements and
close to zero measurements at local noon.
Daily mean SSAs in the UV (UVMFR) at two wavelengths and at 440 nm (CIMEL) for Athens area.
AERONET Level 1.5 (L1.5) SSA data are provided by AERONET for all AODs and at all SZA that almucantar scans are performed. In this work L1.5 data were used with an extra quality control. We have ignored SSA L1.5 data when L2 size distribution is not available. Thus, we have an enhanced L1.5 SSA dataset with AOD < 0.4, but with L2 cloud screening, calibrations and quality controls. Data have been compared with UVMFR retrieved SSAs taking into account limitations related to the retrieval uncertainties. Khatri et al. (2016) studied AERONET SSA retrieval uncertainties in order to compare with SKYNET and found that AOD errors introduce the largest variations. They also found that the sky irradiance calibration has a primary role in the uncertainty of the retrieval, and they investigated the influence of surface albedo and sphericity of aerosols, which was found negligible.
Regarding the UVMFR data, the uncertainty of the UVMFR SSA retrieval is
mainly related to
direct to global irradiance measurement uncertainties RTM input data accuracy.
Direct to global irradiance measurement uncertainties can result to a range
of SSA values rather than a single value, which would produce a close match
between the measurement and the RTM DGR outputs. This range broadens at low
SZA and high aerosol level cases, as shown in Fig. 6, when the impact of
the scattering and absorbing nature of aerosols on solar radiation is higher. The
RTM inputs that were used for the SSA LUT construction include also an
uncertainty budget (AOD, surface albedo, constant aerosol vertical profile,
asymmetry factor). Following the uncertainty analysis of Krotkov et al. (2005b), the total relative uncertainty of the DGR measurement was calculated
to be
We calculated the SSA at 332 and 368 nm using 1 min data from the UVMFR. For the period under investigation, we also calculated the daily mean SSAs at these two wavelengths in the UV band and also the mean daily SSAs in the visible band, derived from data provided by the CIMEL (L1.5 data) operating in Athens' AERONET station (Fig. 8).
The 2
Mean monthly SSAs (left axis) in the UV (UVMFR) at two wavelengths and AOD at 368 nm from the UVMFR (right axis) for the whole 5-year period in Athens. Error bars represent 1 standard deviation of the mean.
The mean diurnal course shows variability of the order of 0.02 to 0.04, with
highest absorption (lowest SSAs) encountered
Diurnal patterns of SSA derived from the UVMFR and CIMEL
measurements. Mean values per hour are plotted with error bars corresponding
to 1 standard deviation. Local time in Athens is UTC
In order to investigate the possible dependence of SSA on AOD, the
synchronous UVMFR and CIMEL SSA retrievals plotted against AOD at 440 nm are
shown in Fig. 11. SSA decreases with decreasing optical extinction,
although lower AODs are also linked to higher uncertainties of the retrieved
SSA. This behavior probably reflects seasonal changes in the average aerosol
composition in Athens. Indeed, the annual cycle of SSA is the same as the AOD
annual cycle, having a maximum in summer and a minimum in winter. Studies of
the SSA annual variability for other cities such as Ispra, Italy, and
Thessaloniki, Greece (Arola et al., 2005; Bais et al., 2005), revealed the
same trend, with low SSA values (high absorption) associated with low AOD. It
has to be noted that due to low AOD, the uncertainties associated with data
obtained from both retrieval techniques (AERONET and UVMFR) are quite high.
For higher AOD (> 0.6), CIMEL retrievals show an almost constant
value of the SSA
Dependence of the calculated SSA from AOD measurements.
We have performed an analysis of the differences of SSAs between the visible
and the UV parts of the spectrum based on aerosol characteristics, using
synchronous CIMEL and UVMFR SSA retrievals and an aerosol classification
scheme described in detail in Mielonen et al. (2009). In that work, a
classification of AERONET data was used in order to derive six aerosol types
based on SSA at 440 nm and the Ångström exponent (AE) that was derived in the 440–870 nm
wavelength range. Mielonen et al. (2009) used a visualization of this
characterization, by plotting AE versus SSA for individual sites, and
compared their results with the CALIPSO (Omar et al., 2005) aerosol
classification scheme obtaining good agreement. In addition, the difference
between SSA at 440 and 1020 nm (similar to the approach applied by
Derimian et al., 2008) was implemented to better distinguish fine absorbing
aerosols from coarse. The main idea was to fill this SSA versus AE aerosol-type-related “space” with the differences of SSA
Daily average SSA
The results in Fig. 12 show that a mixture of aerosol types is typical for
ARSS site in Athens, with SSA
In order to better understand the potential relative contributions of dust and brown carbon, we applied the method of Schuster et al. (2016) to the AERONET measurements in Athens. This method separates contributions from black carbon, organic carbon, hematite and goethite to the retrieved refractive index at all available wavelengths, even in complex mixtures. Figure 13 shows the fractions of total aerosol volume attributed to these components, as well as the volume fractions, accordingly. It is evident that both brown carbon and mineral dust are likely absorbing components involved in the aerosol mixture in Athens, with brown carbon probably playing the more dominant role. Brown carbon highly absorbs in UV wavelengths and hardly any above 0.7 nm (Kirchstetter et al., 2004). Brown carbon fraction is higher in October, but it has very large concentrations during the period March–June, which partly explains low SSA values in Fig. 9.
Total volume (in the upper plot) and volume fraction (in the lower plot) of absorbing aerosol components, as inferred from the method of Schuster et al. (2016). The retrieval gives the fractions for fine and coarse mode separately and here the contributions are shown as mode-weighted median value.
The usefulness of the AE for aerosol extinction is that its value depends
primarily on the size of the particles, ranging from a value of 4 for very
small particles (Rayleigh scattering) to around 0 for very large particles
(such as cloud drops). Various studies (e.g., Bergstrom et al., 2007) have
used the Ångström absorption exponent (AAE) to study the aerosol
absorption wavelength dependence for different aerosol types and mixtures.
AAE is calculated similarly with AE, only using AOD*(1-SSA) instead of AOD.
As the absorption AOD is a relatively smooth decreasing function with
wavelength, it can be approximated by a power law wavelength dependence via
the AAE, which is defined as the negative of the slope of the absorption on
a log–log plot. The measurements of AAE
Finally, we have calculated mean CIMEL SSA values for all four retrieved
wavelengths (440, 673, 870 and 1020 nm) and for the whole period
under study, and synchronous (5 min SSA averaged around the CIMEL
measurement time) UVMFR SSAs at the UV (332 and 368 nm). The results are
shown in Fig. 14 with error bars at 1
Wavelength dependence of SSA from synchronous CIMEL and UVMFR measurements. Blue points represent all data points, red points are data retrievals with AOD > 0.2, green points are data with AE > 1.2 and black points are data only dust aerosol cases. Vertical bars represent 1 standard deviation of the calculated mean.
The spectral dependence of the SSA from the visible to the UV wavelengths is in agreement with findings presented by Corr et al. (2009) and Krotkov et al. (2009). The same approach was also applied to Mexico City, where measurements are also influenced by city emissions and blowing dust. Corr et al. (2009) studied the SSA behavior at UV wavelengths and showed that for AOD > 0.1, SSA varied from 0.78 to 0.80 at 332 and 368 nm, respectively, with enhanced absorption at UV wavelengths relative to VIS, a finding in accordance with these types of aerosols. Krotkov et al. (2009), modifying a UVMFR in order to measure also at 440 nm, found strong SSA wavelength dependence across the blue and near-UV spectral region.
The advantages of measuring the aerosol absorption (SSA) in the UV with a
UVMFR instrument can be summarized as follows:
AOD, in the UV wavelength range, is higher (for the same aerosol mass) than
in the visible spectral range. SSA retrievals with an uncertainty of SSA retrievals are stable and repeatable over the 5-year period.
We have analyzed a 5-year period of UVMFR and CIMEL measurements performed in
Athens, retrieving SSA at visible and UV wavelengths based on the effect of
aerosol SSA on the DGR for a given AOD and air mass.
Since the CIMEL retrieval algorithm is more accurate for high SZA, the
combination of the two instruments allows for higher measurement frequency of
SSA and the ability to derive a complete diurnal cycle of aerosol absorption.
As a follow-up, the spectral differences of the aerosol absorption properties
in the visible and UV wavelength ranges have been investigated, using
synchronous CIMEL and UVMFR retrievals. Results of this work confirmed
similar results found for Mexico City, Mexico (Corr et al., 2009), Greenbelt,
Maryland, USA (Krotkov et al., 2005b), and Rome, Italy (Ialongo et al., 2010),
which presented enhanced absorption of aerosols for UV wavelengths.
We have also used the produced dataset to investigate possible effects of
aerosol type on the observed SSA wavelength differences. The enhanced UV
absorption can be mainly due to either dust or organic aerosol. Our analysis
of Athens AERONET measurements suggests that the relative role of absorbing
organic aerosol is somewhat more significant than dust. The enhanced aerosol
absorption found when comparing UV and visible spectrum results, shows the following:
We expect a systematic overestimation of modeled solar UV irradiance using
SSA from extrapolation from the visible range as an input to RTMs. There is a possibility of a decrease in specific days/cases of regional
ozone due to enhanced aerosol absorption (Li et al., 2005). For Athens, such
a case could be verified only with chemical model results. Satellite post-correction results (e.g., Arola et al., 2009), including
aerosol absorption effects, have to take into account absorption enhancement
in the UV range. We expect an overestimation of the UV irradiance (UV index) calculations on
cloudless cases under dust and/or brown carbon presence when using SSA
values from the visible range. This comes as a combination of the
overestimated SSA and the high AODs during such events.
However, the spectral SSA differences that we found are well within the
uncertainty of both retrievals, as instrumental effects or absolute
calibration uncertainties of sky radiances (
The extended SSA dataset significantly improves comparative statistics and provides additional information on the effects of varying background aerosol conditions and higher aerosol absorption compared to that in Washington, DC, where dust aerosol cases are very rare. In conclusion, the combined use of CIMEL sun and sky radiance measurements in the visible with UVMFR total and diffuse irradiance measurements in the UV provides an important advantage for remote measurements of column aerosol absorption over the UV–VIS spectral range.
Data can be accessed through personal communication with S. Kazadzis.
Panagiotis Raptis would like to acknowledge the project Aristotelis SOLAR (50561), “Investigation on the factors affecting the solar radiation field in Greece”. Vassilis Amiridis, Stelios Kazadzis and Evangelos Gerasopoulos would like to acknowledge the project “European Union's Horizon 2020 Research and Innovation Programme ACTRIS-2” (grant agreement no. 654109). Edited by: O. Torres Reviewed by: N. A. Krotkov and one anonymous referee