Maria Mylonaki

Mrs. Maria Mylonaki


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 December 2020 in Atmospheric Chemistry and Physics
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OSOurania Soupiona
Ourania Soupiona
ALEXANDROS PapayannisALEXANDROS Papayannis
ALEXANDROS Papayannis
PKPanagiotis Kokkalis
Panagiotis Kokkalis
RFRomanos Foskinis
Romanos Foskinis
GHGuadalupe Sánchez Hernández
Guadalupe Sánchez Hernández
Basil E. PsiloglouBasil E. Psiloglou
Basil E. Psiloglou
Remote sensing measurements of aerosols using depolarization Raman lidar systems from four EARLINET (European Aerosol Research Lidar Network) stations are used for a comprehensive analysis of Saharan dust events over the Mediterranean basin in the period 2014–2017. In this period, 51 dust events regarding the geometrical, optical and microphysical properties of dust were selected, classified and assessed according to their radiative forcing effect on the atmosphere. From west to east, the stations of Granada, Potenza, Athens and Limassol were selected as representative Mediterranean cities regularly affected by Saharan dust intrusions. Emphasis was given on lidar measurements in the visible (532 nm) and specifically on the consistency of the particle linear depolarization ratio (δp532), the extinction-to-backscatter lidar ratio (LR532) and the aerosol optical thickness (AOT532) within the observed dust layers. We found mean δp532 values of 0.24±0.05, 0.26±0.06, 0.28±0.05 and 0.28±0.04, mean LR532 values of 52±8, 51±9, 52±9 and 49±6 sr and mean AOT532 values of 0.40±0.31, 0.11±0.07, 0.12±0.10 and 0.32±0.17, for Granada, Potenza, Athens and Limassol, respectively. The mean layer thickness values were found to range from ∼ 1700 to ∼ 3400 m a.s.l. Additionally, based also on a previous aerosol type classification scheme provided by airborne High Spectral Resolution Lidar (HSRL) observations and on air mass backward trajectory analysis, a clustering analysis was performed in order to identify the mixing state of the dusty layers over the studied area. Furthermore, a synergy of lidar measurements and modeling was used to analyze the solar and thermal radiative forcing of airborne dust in detail. In total, a cooling behavior in the solar range and a significantly lower heating behavior in the thermal range was estimated. Depending on the dust optical and geometrical properties, the load intensity and the solar zenith angle (SZA), the estimated solar radiative forcing values range from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the top of the atmosphere (TOA). Similarly, in the thermal spectral range these values range from +2 to +4 W m−2 for the surface and from +1 to +3 W m−2 for the TOA. Finally, the radiative forcing seems to be inversely proportional to the dust mixing ratio, since higher absolute values are estimated for less mixed dust layers.

23 September 2019 in Atmospheric Chemistry and Physics
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EPEmmanouil Proestakis
Emmanouil Proestakis
VAVassilis Amiridis
Vassilis Amiridis
EMEleni Marinou
Eleni Marinou
IBIoannis Binietoglou
Ioannis Binietoglou
AAAlbert Ansmann
Albert Ansmann
GPGelsomina Pappalardo
Gelsomina Pappalardo
We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.

15 February 2021 in Atmospheric Chemistry and Physics
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MMMaria Mylonaki
Maria Mylonaki
EGElina Giannakaki
Elina Giannakaki
ALEXANDROS PapayannisALEXANDROS Papayannis
ALEXANDROS Papayannis
CPChristina-Anna Papanikolaou
Christina-Anna Papanikolaou
MKMika Komppula
Mika Komppula
OSOurania Soupiona
Ourania Soupiona
We introduce an automated aerosol type classification method, called Source Classification Analysis (SCAN). SCAN is based on predefined and characterized aerosol source regions, the time that the air parcel spends above each geographical region, and a number of additional criteria. The output of SCAN is compared with two independent aerosol classification methods, which use the intensive optical parameters from lidar data: (1) the Mahalanobis distance automatic aerosol type classification (MD) and (2) a neural network aerosol typing algorithm (NATALI). In this paper, data from the European Aerosol Research Lidar Network (EARLINET) have been used. A total of 97 free tropospheric aerosol layers from four typical EARLINET stations (i.e., Bucharest, Kuopio, Leipzig, and Potenza) in the period 2014–2018 were classified based on a 3β+2α+1δ lidar configuration. We found that SCAN, as a method independent of optical properties, is not affected by overlapping optical values of different aerosol types. Furthermore, SCAN has no limitations concerning its ability to classify different aerosol mixtures. Additionally, it is a valuable tool to classify aerosol layers based on even single (elastic) lidar signals in the case of lidar stations that cannot provide a full data set (3β+2α+1δ ) of aerosol optical properties; therefore, it can work independently of the capabilities of a lidar system. Finally, our results show that NATALI has a lower percentage of unclassified layers (4 %), while MD has a higher percentage of unclassified layers (50 %) and a lower percentage of cases classified as aerosol mixtures (5 %).

28 February 2023 in Atmospheric Measurement Techniques
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AGAntonis Gkikas
Antonis Gkikas
AGAnna Gialitaki
Anna Gialitaki
IBIoannis Binietoglou
Ioannis Binietoglou
EMEleni Marinou
Eleni Marinou
MTMaria Tsichla
Maria Tsichla
VAVassilis Amiridis
Vassilis Amiridis
Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). Aeolus, carrying ALADIN (Atmospheric LAser Doppler INstrument), the first UV HSRL (High Spectral Resolution Lidar) Doppler lidar ever placed in space, provides also vertically resolved optical properties of particulates (aerosols and clouds). The present study focuses on the assessment of Aeolus L2A particulate backscatter coefficient (baseline 2A11), retrieved by the Standard Correct Algorithm (SCA), in the eastern Mediterranean, a region hosting a variety of aerosol species. Ground-based retrievals acquired by lidar instruments operating in Athens (central Greece), Thessaloniki (northern Greece) and Antikythera (southwestern Greece) serve as reference. All lidar stations provide routine measurements to the PANACEA (PANhellenic infrastructure for Atmospheric Composition and climatE chAnge) network. A set of ancillary data, including sun-photometric observations (AERONET), reanalysis products (CAMS and MERRA-2), satellite observations (MSG-SEVIRI and MODIS Aqua) and backward-trajectories modelling (FLEXPART), is utilized towards an optimum characterization of the probed atmospheric conditions under the absence of a classification scheme in Aeolus SCA profiles. First, emphasis is given on the assessment of Aeolus SCA backscatter coefficient under specific aerosol scenarios over Antikythera island. Due to the misdetection of the cross-polar component of the backscattered lidar signal, Aeolus underestimates the aerosol backscatter coefficient by up to 33 % when non-spherical mineral particles are recorded (10 July 2019). A good performance is revealed on 3 July 2019, when horizontally homogeneous loads of fine spherical particles are confined below 4 km. For other two cases (8 July 2020 and 5 August 2020), due to noise issues, the SCA performance degrades in terms of depicting the stratification of aerosol layers composed of particles of different origin. According to the statistical assessment analysis of 43 identified cases, a poor-to-moderate performance is revealed for the unfiltered (aerosols plus clouds) SCA profiles, which improves substantially when cloud-contaminated profiles are excluded from the collocated sample. This improvement is evident at both Aeolus vertical scales (regular scales have 24 bins and mid-bin scales have 23 bins), and it is justified by the drastic reduction in the bias (from 0.45 to 0.27 Mm−1 sr−1 for SCA and from 0.69 to 0.37 Mm−1 sr−1 for SCA mid-bin) and root mean square error (from 2.00 to 1.65 Mm−1 sr−1 for SCA and from 1.88 to 1.00 Mm−1 sr−1 for SCA mid-bin) scores. In the vertical, the SCA performance degrades at the lowermost bins due to either the contamination from surface signals or the increased noise levels for the aerosol retrievals. Among the three PANACEA stations, the best agreement is found at the remote site of Antikythera with respect to the urban sites of Athens and Thessaloniki. Finally, all key Cal/Val (calibration and validation) aspects necessary for future relevant studies, the recommendations for a possible Aeolus follow-on mission and an overview of the ongoing related activities are thoroughly discussed.

6 February 2023 in Atmospheric Chemistry and Physics
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KMKonstantinos Michailidis
Konstantinos Michailidis
MKMaria-Elissavet Koukouli
Maria-Elissavet Koukouli
DBDimitris Balis
Dimitris Balis
JVJ. Pepijn Veefkind
J. Pepijn Veefkind
MGMartin De Graaf
Martin De Graaf
HBHolger Baars
Holger Baars
The purpose of this study is to investigate the ability of the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) to derive accurate geometrical features of lofted aerosol layers, selecting the Mediterranean Basin as the study area. Comparisons with ground-based correlative measurements constitute a key component in the validation of passive and active satellite aerosol products. For this purpose, we use ground-based observations from quality-controlled lidar stations reporting to the European Aerosol Research Lidar Network (EARLINET). An optimal methodology for validation purposes has been developed and applied using the EARLINET optical profiles and TROPOMI aerosol products, aiming at the in-depth evaluation of the TROPOMI aerosol layer height (ALH) product for the period 2018 to 2022 over the Mediterranean Basin. Seven EARLINET stations were chosen, taking into consideration their proximity to the sea, which provided 63 coincident aerosol cases for the satellite retrievals. In the following, we present the first validation results for the TROPOMI/S5P ALH using the optimized EARLINET lidar products employing the automated validation chain designed for this purpose. The quantitative validation at pixels over the selected EARLINET stations illustrates that the TROPOMI ALH product is consistent with the EARLINET lidar products, with a high correlation coefficient R=0.82 (R=0.51) and a mean bias of -0.51±0.77 km and -2.27±1.17 km over ocean and land, respectively. Overall, it appears that aerosol layer altitudes retrieved from TROPOMI are systematically lower than altitudes from the lidar retrievals. High-albedo scenes, as well as low-aerosol-load scenes, are the most challenging for the TROPOMI retrieval algorithm, and these results testify to the need to further investigate the underlying cause. This work provides a clear indication that the TROPOMI ALH product can under certain conditions achieve the required threshold accuracy and precision requirements of 1 km, especially when only ocean pixels are included in the comparison analysis. Furthermore, we describe and analyse three case studies in detail, one dust and two smoke episodes, in order to illustrate the strengths and limitations of the TROPOMI ALH product and demonstrate the presented validation methodology. The present analysis provides important additions to the existing validation studies that have been performed so far for the TROPOMI S5P ALH product, which were based only on satellite-to-satellite comparisons.

7 January 2022 in Atmosphere
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CPChristina-Anna Papanikolaou
Christina-Anna Papanikolaou
ALEXANDROS PapayannisALEXANDROS Papayannis
ALEXANDROS Papayannis
MMMaria Mylonaki
Maria Mylonaki
RFRomanos Foskinis
Romanos Foskinis
PKPanagiotis Kokkalis
Panagiotis Kokkalis
DADIMITRA ANAGNOU
DIMITRA ANAGNOU
Vertical profiling of aerosol particles was performed during the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) winter campaign (10 January 2020–7 February 2020) over the city of Ioannina, Greece (39.65° N, 20.85° E, 500 m a.s.l.). The middle-sized city of Ioannina suffers from wintertime air pollution episodes due to biomass burning (BB) domestic heating activities. The lidar technique was applied during the PANACEA winter campaign on Ioannina city, to fill the gap of knowledge of the spatio-temporal evolution of the vertical mixing of the particles occurring during these winter-time air pollution episodes. During this campaign the mobile single-wavelength (532 nm) depolarization Aerosol lIdAr System (AIAS) was used to measure the spatio-temporal evolution of the aerosols’ vertical profiles within the Planetary Boundary Layer (PBL) and the lower free troposphere (LFT; up to 4 km height a.s.l.). AIAS performed almost continuous lidar measurements from morning to late evening hours (typically from 07:00 to 19:00 UTC), under cloud-free conditions, to provide the vertical profiles of the aerosol backscatter coefficient (baer) and the particle linear depolarization ratio (PLDR), both at 532 nm. In this study we emphasized on the vertical profiling of very fresh (~hours) biomass burning (BB) particles originating from local domestic heating activities in the area. In total, 33 out of 34 aerosol layers in the lower free troposphere were characterized as fresh biomass burning ones of local origin, showing a mean particle linear depolarization value of 0.04 ± 0.02 with a range of 0.01 to 0.09 (532 nm) in a height region 1.21–2.23 km a.s.l. To corroborate our findings, we used in situ data, particulate matter (PM) concentrations (PM2.5) from a particulate sensor located close to our station, and the total black carbon (BC) concentrations along with the respective contribution of the fossil fuel (BCff) and biomass/wood burning (BCwb) from the Aethalometer. The PM2.5 mass concentrations ranged from 5.6 to 175.7 μg/m3, while the wood burning emissions from residential heating were increasing during the evening hours, with decreasing temperatures. The BCwb concentrations ranged from 0.5 to 17.5 μg/m3, with an extremely high mean contribution of BCwb equal to 85.4%, which in some cases during night-time reached up to 100% during the studied period.