Testing the applicability of artificial intelligence techniques to the subject of erythemal ultraviolet solar radiation part one: the applicability of a fuzzy rule based approach.

This work presents the applicability of applying a fuzzy logic approach to the calculation of noontime erythemal UV irradiance for the plain areas of Egypt. When different combinations of data sets were examined from the test performance point of view, it was found that 91% of the whole series was estimated within a deviation of less than +/-10 mW/m(2), and 9% of these deviations lay within the range of +/-15 mW/m(2) to +/-25 mW/m(2).

Testing the applicability of artificial intelligence techniques to the subject of erythemal ultraviolet solar radiation. Part two: an intelligent system based on multi-classifier technique.

The problem we address here describes the on-going research effort that takes place to shed light on the applicability of using artificial intelligence techniques to predict the local noon erythemal UV irradiance in the plain areas of Egypt. In light of this fact, we use the bootstrap aggregating (bagging) algorithm to improve the prediction accuracy reported by a multi-layer perceptron (MLP) network. The results showed that, the overall prediction accuracy for the MLP network was only 80.9%. When bagging algorithm is used, the accuracy reached 94.8%; an improvement of about 13.9% was achieved. These improvements demonstrate the efficiency of the bagging procedure, and may be used as a promising tool at least for the plain areas of Egypt.

The relative influence of the anthropogenic air pollutants on the atmospheric turbidity factors measured at an urban monitoring station.

This work is based on simultaneous measurements of direct solar radiation along with other chemical measurements, with the objective of investigating the diurnal and seasonal variations of atmospheric turbidity factors (i.e., Linke's factor, Angström's coefficient, and aerosol optical depth). Relationships between atmospheric turbidity factors, expressing the solar radiation extinction, and anthropogenic air pollutants were also evaluated. The frequency of occurrence of the individual indices has been established to describe the sky conditions. The preliminary results obtained indicate high variability of aerosol loading, leading to high turbidity for most of the year. Annual averages of 0.2 and 6 with standard deviations of 0.096 and 0.98 were found for Angström and Linke turbidities, respectively. On the base of the frequency of occurrence, it has been found that over 50% of the dataset are around 0.25 and 6.3 for Angström and Linke turbidities, respectively. On average, the month of September experienced the highest turbidity, while December experienced the lowest. A possible reason for this is that the vertical distribution of the aerosol particles moves up in September due to the extent of the Sudan monsoon trough. We also note that spring values of the turbidity factors are closer to summer values, whereas the pronounced difference between the summer values in comparison with the winter values may be attributed to relatively greater difference in the water vapor level in the atmosphere.

Dependence of urban air pollutants on meteorology.

Dependence of air pollutants on meteorology is presented with the aim of understanding the governing processes pollutants phase interaction. Intensive measurements of particulate matter (PM10) and gaseous materials (e.g., CO, NO2, SO2, and O3) are carried out regularly in 2002 at 14 measurement sites distributed over the whole territory of Great Cairo by the Egyptian Environmental Affairs Agency to assess the characteristics of air pollutants. The discussions in this work are based upon measurements performed at Abbassiya site as a case study. The nature of the contributing sources has been investigated and some attempts have been made to indicate the role played by neighboring regions in determining the air quality at the site mentioned. The results hint that, wind direction was found to have an influence not only on pollutant concentrations but also on the correlation between pollutants. As expected, the pollutants associated with traffic were at highest ambient concentration levels when wind speed was low. At higher wind speeds, dust and sand from the surrounding desert was entrained by the wind, thus contributing to ambient particulate matter levels. We also found that, the highest average concentration for NO2 and O3 occurred at humidity