One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling

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

Weekend-Weekday Effect Assessment of PM10 in Volos, Greece (2010-2014)

Several epidemiological studies have shown an association between particulate air pollution and adverse health effects. The consensus among the scientific community is that suspended particulate matter is one of the most harmful pollutants, particularly the inhalable particulate matter with aerodynamic diameters less than 10 mu m (PM10) causing respiratory health effects and heart diseases. The effects of aerosols on human health are determined by both their size and their chemical composition. Average daily concentrations exceeding the EU daily threshold concentration appear, among other cases, during Sahara dust episodes, a natural phenomenon that degrades the air quality in the urban area of Volos. The city of Volos is a coastal city of medium size in the eastern seaboard of Central Greece. The main objective of this work is the study of the temporal evolution and the assessment of weekend effect in particulate matter concentration levels in the centre of the city of Volos. PM10 data obtained by a fully automated station that was established by the Hellenic Ministry of Environment and Energy, for a 5-year period (2010-2014) are analyzed in order to study the day-of-week variations during the cold and warm period of the year. As these variations are mostly expected to be due to the human working cycle, a strong weekly cycle would be indicative of the dominance of anthropogenic particles

Autonomous SoC for fuzzy robot path tracking

In this paper a System-on-a-Chip (SoC) for the path following task of autonomous non-holonomic mobile robots is presented. The SoC consists of a digital fuzzy logic processor and a flow control program that runs under the Xilinx Microblaze™ soft processor core. The fuzzy processor implements a fuzzy path tracking algorithm introduced by the authors. The system was tied to an actual P3-DX8 robot and field experiments have been performed in order to assess the overall performance. Quantization problems and limitations imposed by the system configuration are also discussed

Tracking control using the strip-wise affine transformation: an experimental SoC design

This paper presents the analysis and application of the strip-wise affine map to the path following task for autonomous non-holonomic mobile robots. The mapping was implemented on a Spartan 3-1500 FPGA board with the use of VHDL and advanced EDA tools and was used in field experiments on a Khepera H differential robot. A fully parameterized DFLC previously published by the author has been tailored accordingly for the needs of this design implementation. Experiments were performed using a calibrated camera and a video tracking algorithm in order to extract the actual robot's path, compare it to the odometry solution and analyze the tracker's performanc

BIOCLIMATIC AND AIR QUALITY CONDITIONS IN THE GREATER ATHENS AREA, GREECE, DURING THE WARM PERIOD OF THE YEAR: TRENDS, VARIABILITY AND PERSISTENCE

The aim of this work is to study the bioclimatic conditions as well as the air quality for three different regions of the greater Athens area (GAA), during the warm period of the year for the time period 2001-2005. Furthermore, the thermal discomfort and the air pollution persistence within 24 hours were studied. Finally, both the variability and the trend of the bioclimatic and air quality conditions during the examined period were studied. In order to determine the human thermal comfort-discomfort levels, a widely used biometeorological index, the Cooling Power Index, and microclimatic data (air temperature and wind speed) were used. On the other hand, data concerning the air pollutant concentrations surface ozone (O-3) and particulate matter with aerodynamic diameter less than 10 mu m (PM10) measured over this area were used for the determination of the air quality levels. The performed analysis indicates throughout the examined area degradation of the air quality and intensive thermal discomfort episodes. More specifically, during the warm period of the year a relatively high frequency of days, in the city center of Athens showing thermal discomfort and air quality degradation, simultaneously, is observed. On the contrary, on the suburban GAA's monitoring sites a reduction of the frequency of days with thermal discomfort is observed while the number of days with air pollution exacerbations is relatively high. In any case, during the examined period the environmental conditions due to bioclimatic and air quality parameters seem to be rather degraded

Application of Multiple Linear Regression Models and Artificial Neural Networks on the Surface Ozone Forecast in the Greater Athens Area, Greece

An attempt is made to forecast the daily maximum surface ozone concentration for the next 24 hours, within the greater Athens area (GAA). For this purpose, we applied Multiple Linear Regression (MLR) models against a forecasting model based on Artificial Neural Network (ANN) approach. The availability of basic meteorological parameters is of great importance in order to forecast the ozone’s concentration levels. Modelling was based on recorded meteorological and air pollution data from thirteen monitoring sites within the GAA (network of the Hellenic Ministry of the Environment, Energy and Climate Change) over five years from 2001 to 2005. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that in every aspect, the prognostic model by far is the ANN model. This suggests that the ANN model can be used to issue warnings for the general population and mainly sensitive groups

Estimation of Hospital Admissions Respiratory Disease Attributed to PM10 Exposure Using the AirQ Model Within the Greater Athens Area

The main objective of this work is the assessment of the annual number of hospital admissions for respiratory disease (HARD) due to the exposure to inhalable particulate matter (PM10), within the greater Athens area (GAA), Greece. Towards this aim, the time series of the particulate matter with aerodynamic diameter less than 10 mu m (PM10) recorded in six monitoring stations located in the GAA, for a 13-year period 2001-2013, is used. In this study AirQ2.2.3 software developed by the WHO, was used to evaluate adverse health effects by PM10 in the GAA during the examined period. The results show that, the mean annual HARD cases per 100,000 inhabitants ranged between 20 (suburban location) and 40 (city centre location). Approximately 70 % of the annual HARD cases are due to city centre residents. In all examined locations, a declining trend in the annual number of HARD cases is appeared. Moreover, a strong relation between the annual number of HARD cases and the annual number of days exceeding the European Union daily PM10 threshold value was found