The occurrence of non-fatal acute coronary syndromes (ACS) is examined in relation with the local bioclimatic conditions in the Ierapetra area, in the southernmost part of Crete Island, Greece, during the period 2004-2007. Daily ACS counts and corresponding meteorological parameters, such as maximum and minimum air temperature, relative humidity, wind speed and cloudiness, were analyzed. Besides, the daily values of the human thermal index, physiologically equivalent temperature (PET) was evaluated. Pearson's 2 test and generalized linear models (GLM) with Poisson distribution were applied. The ACS syndromes present a multiple variation within the year, with the primary maximum in August and the secondary in May, while relative high ACS frequencies exist in early winter time. The impact of the weather variability on the ACS incidence is not statistically significant (C.L. 95%). © 2013 Copyright Taylor and Francis Group, LLC.

The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in Greece, per decade, during the 50-year period (1951-2000). Besides, the projected changes in ensemble mean AI between the period 1961-1990 (reference period) and the periods 2021-2050 (near future) and 2071-2100 (far future) along with the inter-model standard deviations were presented, based on the simulation results, derived from a number of Regional Climatic Models (RCMs), within the ENSEMBLE European Project. The projection of the future climate was done under SRES A1B.The climatic data used, concern monthly precipitation totals and air temperature from 28 meteorological stations (22 stations from the Hellenic National Meteorological Service and 6 stations from neighboring countries, taken from the Monthly Climatic Data for the World). The estimation of the AI was carried out based on the potential evapotranspiration (PET) defined by Thornthwaite (1948). The data processing was done by the application of the statistical package R-project and the Geographical Information Systems (GIS).The results of the analysis showed that, within the examined period (1951-2000), a progressive shift from the "humid" class, which characterized the wider area of Greece, towards the "sub-humid" and "semi-arid" classes appeared in the eastern Crete Island, the Cyclades complex, the Evia and Attica, that is mainly the eastern Greece. The most significant change appears during the period 1991-2000. The future projections at the end of twentieth century, using ensemble mean simulations from 8 RCMs, show that drier conditions are expected to establish in regions of Greece (Attica, eastern continental Greece, Cyclades, Dodecanese, eastern Crete Island and northern Aegean). The inter-model standard deviation over these regions ranges from 0.02 to 0.05 against high values (0.09-0.15) illustrated in western mountainous continental Greece, during 2021-2050. Higher values of inter-model standard deviation appear in the 2071-2100 ranging from 0.02 to 0.10 reaching even 0.50 over mountainous regions of the country. © 2011 Elsevier B.V.

The forecast of extreme weather events become imperative due to the emerging climate change and possible adverse effects in humans. The objective of this study is to construct predictive models in order to forecast rain intensity (mm/day) in Athens, Greece, using Artificial Neural Networks (ANN) models. The ANNs outcomes concern the projected mean, maximum and minimum monthly rain intensity for the next four consecutive months in Athens. The meteorological data used to estimate the rain intensity, were the monthly rain totals (mm) and the respective rain days, which were acquired from the National Observatory of Athens, for a 111-year period (1899-2009). The results of the developed and applied ANN models showed a fairly reliable forecast of the rain intensity for the next four months. For the evaluation of the results and the ability of the developed prognostic models, appropriate statistical indices were taken into consideration. In general, the predicted rain intensity compared with the corresponding observed one seemed to be in a very good agreement at a statistical significance level of p. <. 0.01. © 2011 Elsevier B.V.

The objective of this work is the assessment of human thermal bioclimatic conditions in the Athens University Campus (AUC), including the Faculties and their respective Departments of the largest state institution of higher learning in Greece, and among the largest universities in Europe. The analysis of bioclimate was carried out, using the physiologically equivalent temperature (PET), which is based on the energy balance model of the human body. The meteorological data required for the calculation of PET concern hourly values of air temperature, relative humidity, wind speed and total solar radiation, for the time period 1999-2007. The recorded data sets were obtained from the meteorological station of the Laboratory of Climatology and Atmospheric Environment of the University of Athens. The results revealed the hours of the day in which thermal comfort or stress prevails, as well as the trends and variability of PET, for the studied period. Finally, the intense heat waves occurred during summer 2007 along with extreme cold conditions during December 2003-February 2004 were analyzed in terms of PET classes and compared to the respective average bioclimatic conditions of the study period. © 2013 Panagiotis T. Nastos and Andreas Matzarakis.

The study of atmospheric concentration levels at a local scale is one of the most important topics in environmental sciences. Multivariate analysis, fuzzy logic, and neural networks have been introduced in forecasting procedures in order to elaborate operational techniques for level characterization of specific atmospheric pollutants at different spatial and temporal scales. Particularly, approaches based on artificial neural networks (ANNs) have been proposed and successfully applied for forecasting concentration levels of PM10, NO2, SO2, CO, and O3. The present study explores the development and application of ANN models for forecasting, 24 h ahead, not only the daily concentration levels of PM10 but also the number of hours exceeding the PM10 concentration threshold during the day in five different regions within the greater Athens area (GAA). The ANN modeling was based on measurements and estimates of the mean daily PM10 concentration, the maximum hourly NO2 concentration, air temperature, relative humidity, wind speed, and the mode daily value of wind direction from five different monitoring stations for the period 2001-2005. The evaluation of the model performance showed the risk of daily PM10 concentration levels exceeding certain thresholds as well as the duration of the exceedances can be successfully predicted. Despite the limitations of the model, the results indicate that ANNs, when adequately trained, have considerable potential to be used for 1 day ahead PM10 concentration forecasting and the duration within the GAA. © Springer Science+Business Media Dordrecht 2013.

The objective of this study is to compare and analyze satellite precipitation extremes of Tropical Rainfall Measuring Mission level 3 output (TRMM 3B42) over Mediterranean region against the respective high resolution gridded precipitation datasets (0.25. ×. 0.25) based on the E-OBS project, for the period 2000-2011.The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. The E-OBS data set (a European daily high-resolution gridded dataset of surface temperature and precipitation) was developed as part of the European Union Framework 6 ENSEMBLES project, with the aim being to use it for validation of Regional Climate Models (RCMs) and for climate change studies.The indices used in the analysis can be divided in three categories: percentile, absolute and duration indices. The percentile indices concern: very wet days (the number of days with daily precipitation amount above the 95th percentile from the examined period) and extremely wet days (the number of days with daily precipitation amount above the 99th percentile from the examined period). The absolute threshold indices concern: number of heavy precipitation days (number of days with daily precipitation amount above 10. mm), number of very heavy precipitation days (number of days with daily precipitation amount above 20. mm) and simple daily intensity index (daily precipitation amount on wet days in a period per number of wet days in the period). The duration indices concern consecutive dry days (the largest number of consecutive days with daily precipitation amount below 1. mm) and consecutive wet days (the largest number of consecutive days with daily precipitation amount above 1. mm).The spatial distribution of the differences between the two datasets along with the spatial distribution of the correlation coefficients are presented and analyzed. Results show considerable regional differences of precipitation indices over the Mediterranean Region. © 2013 Elsevier B.V.

The objective of this study is to present and analyse the indoor and outdoor temporal variability of the particulate matters of different sizes (namely: PM10, with diameter less than 10 μm; PM7, with diameter less than 7 μm; PM2.5, with diameter less than 2.5 μm and PM1, with diameter less than 1 μm) found in Athens, Greece. Four detectors were used for indoor and outdoor recordings. More specifically, the indoor recordings were performed in seminar rooms, full of students attending lectures, at the University of Athens and the Technological Education Institute of Piraeus. Findings of this research show that on one hand, the indoor particulate matter concentrations remained at lower levels than the thresholds set by the European Council Directives, but on the other hand, the outdoor particulate matter concentrations exceeded the thresholds many times. © The Author(s) 2012 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

The surface ozone is a pollutant of major concern due to its impact on receptors, at currently occurring ambient levels in many regions of the world. The aim of this work is to present the results derived from an analysis of hourly surface ozone concentrations, measured at the urban station of Volos, a coastal medium-sized city at the eastern seaboard of Central Greece, during the 8-year period 2001-2008. The regional climate that is characterized by hot and dry summers with intense sunshine plays an important role in the observed exceedances of the air quality ozone limits. The analysis showed that, ozone diurnal patterns depict daytime photochemical ozone built up, during the sunlight hours of the day. It is remarkable that the maximum daily 8-h averages often exceeded the standard value that is assigned by the EU Directive for human health protection, during almost the warm period of the year, mainly at noon and afternoon hours. © 2013 Global NEST Printed in Greece. All rights reserved.

The results of a comparison between monthly mean ozone column variations calculated from the chemical transport model Oslo CTM2 and those derived from solar backscatter ultraviolet (SBUV) satellite observations are presented for the period 1998-2009. Monthly mean total ozone derived from improved model simulations were used to compute monthly zonal means over 10 latitude zones over the northern and southern hemispheres. Ozone column variations from Oslo CTM2 are highly correlated with SBUV retrievals at all latitude zones. Equatorial zonal winds at 30 hPa were used as index to study the impact of quasi-biennial oscillation (QBO) on ozone. Correlations between modeled ozone and the QBO were found to be the order of +0.8 in the tropics. The impact of QBO was most pronounced at equatorial latitudes with amplitudes of +4 to -4 %. Seasonal variations in surface ozone and tropospheric ozone column calculated by the model are also presented. © 2013 Springer Science+Business Media Dordrecht.

Kriging interpolation technique is adapted to create the mapping of surface ozone seasonality and trends across Europe during 1997-2006, based on European Monitoring and Evaluation Programme ground measurements. The climatology, the annual and seasonal trends and the altitude above sea level (asl) dependence were studied as well as the relation with the North Atlantic Oscillation (NAO). The mean seasonal cycle amplitude and seasonal maximum display an increasing gradient from northwest to southeast, with high levels in Austria and eastern Mediterranean. Significantly close to 0 positive trends appear in UK, Slovakia, southern Scandinavia and Austria in winter and autumn. In Northern Hemisphere winter (December-February), about 40 % of near-surface ozone variability in the western edge of Europe may be attributed to circulation changes and ozone precursors' transport related to NAO. © 2013 Springer Science+Business Media Dordrecht.

Natural hazards pose an increasing threat to society and, for this reason, it is necessary to develop models and methodologies for better understanding and forecasting extreme weather events. A new structure of the Greek Regional Administration (Kallikratis) was established in 2011, based on geographical criteria, in order to create an operational and capable administration. An Atmospheric Hazards Early Warning System (AHEWS) could be characterised as an ultimate tool for the local authorities (first and second tier level) in order to organise and implement efficient plans to mitigate the risk. New operation centres (related to regional and municipality administration level) are suggested to be staffed and equipped with the proposed Early Warning System (EWS). The AHEWS will link to extensive Geographical Information Systems (GIS) datasets and methodologies for safety plans by government agencies and services in order to mitigate the impacts caused by atmospheric extreme events. AHEWS involves high-resolution Numerical Weather Prediction (NWP) products, ground observation network, lightning detection network and satellite information in terms of early convective, initiation and Now-Casting. Storms, lightings, gale winds, snow, hail, tornadoes, low temperatures, heatwaves and several others extreme events are weather phenomena that AHEWS deals with in order to prevent and mitigate impacts on humans and constructions. An automated dissemination procedure is described here for individual and administrative users, followed by safety and action plans, respectively. © 2013 Taylor & Francis.

The present study, deals with the 24-hour prognosis of the outdoor biometeorological conditions in an urban monitoring site within the Greater Athens area, Greece. For this purpose, artificial neural networks (ANNs) modelling techniques are applied in order to predict the maximum and the minimum value of the physiologically equivalent temperature (PET) one day ahead as well as the persistence of the hours with extreme human biometeorological conditions. The findings of the analysis showed that extreme heat stress appears to be 10.0% of the examined hours within the warm period of the year, against extreme cold stress for 22.8% of the hours during the cold period of the year. Finally, human thermal comfort sensation accounts for 81.8% of the hours during the year. Concerning the PET prognosis, ANNs have a remarkable forecasting ability to predict the extreme daily PET values one day ahead, as well as the persistence of extreme conditions during the day, at a significant statistical level of P < 0.01. © 2013 K. P. Moustris et al.