Institute for Environmental Research and Sustainable Development IERSD

Athens, Greece

Institute for Environmental Research and Sustainable Development IERSD

Athens, Greece
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Raptis P.I.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,World Radiation Center | Psiloglou B.,Institute for Environmental Research and Sustainable Development IERSD | And 3 more authors.
Energy | Year: 2017

The ideal inclination of tilted surfaces, used to maximize the capture of surface solar irradiance, is determined by latitude and time of the year. Although several algorithms are used for its estimation, the effect of clouds is difficult to be taken into account and causes large deviations from the “clear sky scenario”. Our aim is to investigate the solar irradiance at inclined surfaces on real atmospheric conditions. A set of four pyranometers, located at the National Observatory of Athens, is used to measure the solar radiation for one year and at 1-min frequency. We use the Global Horizontal (GHI) and the Global Irradiance (GIβ) reaching surfaces tilted at a β angle, with different orientations, in order to quantify the energy benefits of different installations. Furthermore, model calculations were used to simulate GIβ at different tilt angles. GHI measurements agree within the theoretical calculations on cloudless days, receiving more irradiance than the inclined surface during summer months. However, the GIβ reach higher values than GHI in wintertime. Model calculations for various tilt angles reveal that the optimum one is around 30° on year basis. © 2017 Elsevier Ltd

Athanasopoulou E.,Institute for Environmental Research and Sustainable Development IERSD | Rieger D.,Karlsruhe Institute of Technology | Walter C.,Karlsruhe Institute of Technology | Vogel H.,Karlsruhe Institute of Technology | And 7 more authors.
Atmospheric Environment | Year: 2014

The current research study aims at investigating the atmospheric implications of a major fire event in the Mediterranean area. For this purpose, a regional aerosol model coupled online with meteorology (COSMO-ART) is applied over Greece during late summer 2007. Fire risk model results proved to be adequate in reproducing the highly destructive event, which supports further applications for national meteorological forecasts and early warning systems for fire prevention. Columnar aerosol loading field predictions are consistent with satellite maps, which further allows for the correlation of this wildfire event to the atmospheric chemistry and the radiative forcing. Gaseous chemistry resembles that in urban environments and led to nitrogen dioxide and ozone exceedances in several cities in proximity to and downwind the fire spots, respectively. Influence in Athens is found significant from the Euboean plume (45% of total surface PM10) and small (5%) from the fires in Peloponnese. Fire events are indicated by sharp increases in organic to elemental carbon (6), together with sharp decreases in secondary to total organic components (0.1), in comparison to their values during the pre- and post-fire period over Athens (1 and 0.6, respectively). The change in the radiative budget induced by the fire plume is found negative (3-day-average value up to -10Wm-2). Direct heat input is found negligible, thus the net temperature effect is also negative over land (-0.5K). Nevertheless, positive temperature changes are found overseas (hourly value up to+2K), due to the amplified radiation absorption by aged soot, coupled to the intense stabilization of the atmosphere above the sea surface. © 2014 Elsevier Ltd.

Poulakis E.,University of Crete | Theodosi C.,University of Crete | Bressi M.,CEA Saclay Nuclear Research Center | Sciare J.,CEA Saclay Nuclear Research Center | And 3 more authors.
Environmental Science and Pollution Research | Year: 2015

A variety of mineral components (Al, Fe) and trace metals (V, Cr, Mn, Ni, Cu, Zn, Cd, Pb) were simultaneously measured in PM2.5 and PM10 fractions at three different locations (traffic, urban, and suburban) in the Greater Paris Area (GPA) on a daily basis throughout a year. Mineral species and trace metal levels measured in both fractions are in agreement with those reported in the literature and below the thresholds defined by the European guidelines for toxic metals (Cd, Ni, Pb). Size distribution between PM2.5 and PM10 fractions revealed that mineral components prevail in the coarse mode, while trace metals are mainly confined in the fine one. Enrichment factor analysis, statistical analysis, and seasonal variability suggest that elements such as Mn, Cr, Zn, Fe, and Cu are attributed to traffic, V and Ni to oil combustion while Cd and Pb to industrial activities with regional origin. Meteorological parameters such as rain, boundary layer height (BLH), and air mass origin were found to significantly influence element concentrations. Periods with high frequency of northern and eastern air masses (from high populated and industrialized areas) are characterized by high metal concentrations. Finally, inner city and traffic emissions were also evaluated in PM2.5 fraction. Significant contributions (>50 %) were measured in the traffic site for Mn, Fe, Cr, Zn, and Cu, confirming that vehicle emissions contribute significantly to their levels, while in the urban site, the lower contributions (18 to 33 %) for all measured metals highlight the influence of regional sources on their levels. © 2015, Springer-Verlag Berlin Heidelberg.

Taylor M.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Gerasopoulos E.,Institute for Environmental Research and Sustainable Development IERSD
Atmospheric Measurement Techniques | Year: 2014

To date, size distributions obtained from the aerosol robotic network (AERONET) have been fit with bilognormals defined by six secondary microphysical parameters: the volume concentration, effective radius, and the variance of fine and coarse particle modes. However, since the total integrated volume concentration is easily calculated and can be used as an accurate constraint, the problem of fitting the size distribution can be reduced to that of deducing a single free parameter - the mode separation point. We present a method for determining the mode separation point for equivalent-volume bi-lognormal distributions based on optimization of the root mean squared error and the coefficient of determination. The extracted secondary parameters are compared with those provided by AERONETs Level 2.0 Version 2 inversion algorithm for a set of benchmark dominant aerosol types, including desert dust, biomass burning aerosol, urban sulphate and sea salt. The total volume concentration constraint is then also lifted by performing multimodal fits to the size distribution using nested Gaussian mixture models, and a method is presented for automating the selection of the optimal number of modes using a stopping condition based on Fisher statistics and via the application of statistical hypothesis testing. It is found that the method for optimizing the location of the mode separation point is independent of the shape of the aerosol volume size distribution (AVSD), does not require the existence of a local minimum in the size interval 0.439 μm≤ r ≤ 0.992 μm, and shows some potential for optimizing the bi-lognormal fitting procedure used by AERONET particularly in the case of desert dust aerosol. The AVSD of impure marine aerosol is found to require three modes. In this particular case, bi-lognormals fail to recover key features of the AVSD. Fitting the AVSD more generally with multi-modal models allows automatic detection of a statistically significant number of aerosol modes, is applicable to a very diverse range of aerosol types, and gives access to the secondary microphysical parameters of additional modes currently not available from bi-lognormal fitting methods. © 2014 Author(s).

Gkikas A.,University of Ioannina | Gkikas A.,Barcelona Supercomputing Center | Hatzianastassiou N.,University of Ioannina | Mihalopoulos N.,University of Crete | And 2 more authors.
Atmospheric Environment | Year: 2016

An algorithm able to identify and characterize episodes of different aerosol types above sea surfaces of the greater Mediterranean basin (GMB), including the Black Sea and the Atlantic Ocean off the coasts of Iberia and northwest Africa, is presented in this study. Based on this algorithm, five types of intense (strong and extreme) aerosol episodes in the GMB are identified and characterized using daily aerosol optical properties from satellite measurements, namely MODIS-Terra, Earth Probe (EP)-TOMS and OMI-Aura. These aerosol episodes are: (i) biomass-burning/urban-industrial (BU), (ii) desert dust (DD), (iii) dust/sea-salt (DSS), (iv) mixed (MX) and (v) undetermined (UN). The identification and characterization is made with our algorithm using a variety of aerosol properties, namely aerosol optical depth (AOD), Ångström exponent (α), fine fraction (FF), effective radius (reff) and Aerosol Index (AI).During the study period (2000-2007), the most frequent aerosol episodes are DD, observed primarily in the western and central Mediterranean Sea, and off the northern African coasts, 7 times/year for strong episodes and 4 times/year for extreme ones, on average. The DD episodes yield 40% of all types of strong aerosol episodes in the study region, while they account for 71.5% of all extreme episodes. The frequency of occurrence of strong episodes exhibits specific geographical patterns, for example the BU are mostly observed along the coasts of southern Europe and off the Atlantic coasts of Portugal, the MX episodes off the Spanish Mediterranean coast and over the Adriatic and northern Aegean Sea, while the DSS ones over the western and central Mediterranean Sea. On the other hand, the extreme episodes for all but DD aerosol display more patchy spatial patterns. The strong episodes exhibit AOD at 550 nm as high as 1.6 in the southernmost parts of central and eastern Mediterranean Sea, which rise up to 5 for the extreme, mainly DD and DSS, episodes. Although more than 90% of all aerosol episodes last 1 day, there are few cases, mainly extreme DD episodes, which last up to 4 days. Independently of their type, the Mediterranean aerosol episodes occur more frequently in spring (strong and extreme episodes) and summer (strong episodes) and most rarely during winter. A significant year by year variability of Mediterranean aerosol episodes has been identified, more in terms of their frequency than intensity. An analysis of 5-day back trajectories for the most extreme episodes provides confidence on the obtained results of the algorithm, based on the revealed origin and track of air masses causing the episodes. The 25 and 6% of all strong and extreme episodes, respectively, are MX, thus highlighting the co-existence of different aerosol types in the greater Mediterranean. The intensity of both MX and DSS episodes exhibits similar patterns to those of DD strong ones, indicating that desert dust is a determinant factor for the intensity of aerosol episodes in the Mediterranean, including DSS and MX episodes. © 2015 Elsevier Ltd.

Balaras C.A.,Institute for Environmental Research and Sustainable Development IERSD | Dascalaki E.G.,Institute for Environmental Research and Sustainable Development IERSD
ASHRAE Transactions | Year: 2011

The European Union has set an ambitious target for improving energy efficiency in the building sector so that all new buildings as of 2021 should be near zero energy. A major effort is under way for the implementation of the European Directive on the energy performance of buildings (EPBD). This paper presents an overview of the relevant European legislative efforts and focuses on an example for Greece, its national efforts to meet these objectives and an assessment of potential energy conservation in the Hellenic building stock. The untapped energy savings from the Hellenic building sector could play a major role in the efforts to reach the national indicative energy savings target of 3.8 Mtoe by 2016. © 2011 ASHRAE.

Taylor M.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,World Radiation Center | Amiridis V.,National institute for astrophysics | Kahn R.A.,NASA
Atmospheric Environment | Year: 2015

The optical and microphysical characteristics of distinct aerosol types in the atmosphere are not yet specified at the level of detail required for climate forcing studies. What is even less well known are the characteristics of mixtures of aerosol and, in particular, their precise global spatial distribution. Here, cluster analysis is applied to seven years of 3-hourly, gridded 2.5°×2° aerosol optical depth data from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, one of the most-studied global simulations of aerosol type currently available, to construct a spatial partition of the globe into a finite number of aerosol mixtures. The optimal number of aerosol mixtures is obtained with a k-means algorithm with smart seeding in conjunction with a stopping condition based on applying the 'law of diminishing returns' to the norm of the Euclidean distance to provide upper and lower bounds on the number of clusters. Each cluster has a distinct composition in terms of the proportion of biomass burning, sulfate, dust and marine (sea salt) aerosol and this leads rather naturally to a taxonomy for labeling aerosol mixtures. In addition, the assignment of primary colors to constituent aerosol types enables true color-mixing and the production of easy-to-interpret maps of their distribution. The mean multiyear global partition as well as partitions deduced on the seasonal timescale are used to extract aerosol robotic network (AERONET) Level 2.0 Version 2 inversion products in each cluster for estimating the values of key optical and microphysical parameters to help characterize aerosol mixtures. On the multiyear timescale, the globe can be spatially partitioned into 10 distinct aerosol mixtures, with only marginally more variability on the seasonal timescale. In the context of the observational constraints and uncertainties associated with AERONET retrievals, bivariate analysis suggests that mixtures dominated by dust and marine aerosol can be detected with reference to their single scattering albedo and Angstrom exponent at visible wavelengths in conjunction with their fine mode fraction and sphericity. Existing multivariate approaches at classification appear to be more ambiguous. The approach presented here provides gridded (1°×1°) mean compositions of aeorosol mixtures as well as tentative estimates of mean aerosol optical and microphysical parameters in planetary regions where AERONET sites do not yet exist. Spreadsheets of gridded cluster indices for multiyear and seasonal partitions are provided to facililate further study of the global distribution of aerosol mixtures and possibly for the selection of new AERONET site locations. © 2015 Elsevier Ltd.

Taylor M.,Institute for Environmental Research and Sustainable Development IERSD | Kosmopoulos P.G.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,World Radiation Center | And 3 more authors.
Journal of Quantitative Spectroscopy and Radiative Transfer | Year: 2016

This paper reports on the development of a neural network (NN) model for instantaneous and accurate estimation of solar radiation spectra and budgets geared toward satellite cloud data using a 2.4. M record, high-spectral resolution look up table (LUT) generated with the radiative transfer model libRadtran. Two NN solvers, one for clear sky conditions dominated by aerosol and one for cloudy skies, were trained on a normally-distributed and multiparametric subset of the LUT that spans a very broad class of atmospheric and meteorological conditions as inputs with corresponding high resolution solar irradiance target spectra as outputs. The NN solvers were tested by feeding them with a large (10. K record) "off-grid" random subset of the LUT spanning the training data space, and then comparing simulated outputs with target values provided by the LUT. The NN solvers demonstrated a capability to interpolate accurately over the entire multiparametric space. Once trained, the NN solvers allow for high-speed estimation of solar radiation spectra with high spectral resolution (1. nm) and for a quantification of the effect of aerosol and cloud optical parameters on the solar radiation budget without the need for a massive database. The cloudy sky NN solver was applied to high spatial resolution (54. K pixel) cloud data extracted from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat Second Generation 3 (MSG3) satellite and demonstrated that coherent maps of spectrally-integrated global horizontal irradiance at this resolution can be produced on the order of 1 min. © 2015 Elsevier Ltd.

Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Veselovskii I.,Physics Instrumentation Center | Amiridis V.,National institute for astrophysics | Grobner J.,World Radiation Center | And 6 more authors.
Atmospheric Measurement Techniques | Year: 2014

Synchronized sun-photometric measurements from the AERONET-CIMEL (AErosol RObotic NETwork) and GAW-PFR (Global Atmospheric Watch-Precision Filter Radiometer) aerosol networks are used to compare retrievals of the aerosol optical depth (AOD), effective radius, and volume concentration during a high-temporal-resolution measurement campaign at the Athens site in the Mediterranean Basin from 14 to 22 July 2009. During this period, direct-sun AOD retrievals from both instruments exhibited small differences in the range 0.01-0.02. The AODs measured with CIMEL and PFR instruments were inverted to retrieve particle microphysical properties using the linear estimation (LE) technique. For low aerosol loads (AOD < 0.2), measurements of the effective radius by the PFR were found to be -20% to +30% different from CIMEL values for both direct-sun data and inversion data. At higher loads (AOD > 0.4), measurements of the effective radius by the PFR are consistently 20 % lower than CIMEL for both direct-sun and inversion data. Volume concentrations at low aerosol loads from the PFR are up to 80% higher than the CIMEL for direct-sun data but are up to 20% lower when derived from inversion data under these same conditions. At higher loads, the percentage difference in volume concentrations from the PFR and CIMEL is systematically negative, with inversion data predicting differences 30% lower than those obtained from direct-sun data. An assessment of the effect of errors in the AOD retrieval on the estimation of PFR bulk parameters was performed and demonstrates that it is possible to estimate the particle volume concentration and effective radius with an uncertainty < 65% when AOD < 0.2 and when input errors are as high as 10%. © Author(s) 2014. CC Attribution 3.0 License.

Taylor M.,Institute for Environmental Research and Sustainable Development IERSD | Kazadzis S.,Institute for Environmental Research and Sustainable Development IERSD | Tsekeri A.,National institute for astrophysics | Gkikas A.,University of Ioannina | Amiridis V.,National institute for astrophysics
Atmospheric Measurement Techniques | Year: 2014

In order to exploit the full-earth viewing potential of satellite instruments to globally characterise aerosols, new algorithms are required to deduce key microphysical parameters like the particle size distribution and optical parameters associated with scattering and absorption from space remote sensing data. Here, a methodology based on neural networks is developed to retrieve such parameters from satellite inputs and to validate them with ground-based remote sensing data. For key combinations of input variables available from the MODerate resolution Imaging Spectro-radiometer (MODIS) and the Ozone Measuring Instrument (OMI) Level 3 data sets, a grid of 100 feed-forward neural network architectures is produced, each having a different number of neurons and training proportion. The networks are trained with principal components accounting for 98% of the variance of the inputs together with principal components formed from 38 AErosol RObotic NETwork (AERONET) Level 2.0 (Version 2) retrieved parameters as outputs. Daily averaged, co-located and synchronous data drawn from a cluster of AERONET sites centred on the peak of dust extinction in Northern Africa is used for network training and validation, and the optimal network architecture for each input parameter combination is identified with reference to the lowest mean squared error. The trained networks are then fed with unseen data at the coastal dust site Dakar to test their simulation performance. A neural network (NN), trained with co-located and synchronous satellite inputs comprising three aerosol optical depth measurements at 470, 550 and 660 nm, plus the columnar water vapour (from MODIS) and the modelled absorption aerosol optical depth at 500 nm (from OMI), was able to simultaneously retrieve the daily averaged size distribution, the coarse mode volume, the imaginary part of the complex refractive index, and the spectral single scattering albedo - with moderate precision: correlation coefficients in the range 0.368 ≤ R ≤ 0.514. The network failed to recover the spectral behaviour of the real part of the complex refractive index. This new methodological approach appears to offer some potential for moderately accurate daily retrieval of the total volume concentration of the coarse mode of aerosol at the Saharan dust peak in the area of Northern Africa. © 2014 Author(s).

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