Volume 15 - 2013

3,4-dichloroaniline (3,4-DCA) is a hardly biodegradable and hydrolysable compound, characterized as a persistent pollutant for water, soil and sediment and highly toxic for living organisms. In this work, the impact of different micrometeorological conditions on uptake of 3,4-DCA was investigated in maize (Zea mays L.) plants grown hydroponically. For this purpose, seedlings of a uniform vigor were developed in appropriate nutrient solution supplied with an initial amount of 3,4-DCA (growth solution) under controlled high light (HL) and low light intensity (LL) conditions and under high (HH) and low relative humidity (LH) conditions in the combinations of HL/HH, LL/HH and HL/LH. Plants grown under HL/LH were replenished with the initial amount of 3,4-DCA after 48 h from the application of the growth solution (AGS). The measurements which took place were related to the uptake of 3,4-DCA and of growth solution by plants. Also, the fresh weight of plants was measured. Results showed that maize was capable of removing noticeably high amounts of 3,4-DCA (up to three quarters of the initial amount) from the growth solution after completion of the first 24 h period from AGS, irrespective of micrometeorological conditions. It was also demonstrated that almost the whole available amount of 3,4-DCA was removed from the growth solution after a 48 h period from AGS under HL/LH. Plants under these conditions removed a significantly higher volume of growth solution compared to the HH conditions, irrespective of measurement time. The significant increase of the 3,4-DCA uptake (almost the whole available amount) by maize plants which were replenished with this compound under LH compared to HH, indicated a considerable capability of these plants to remove high concentrations of 3,4-DCA from the growth solution after 72 h from AGS. The fresh weight of maize plants under the examined micrometeorological conditions did not change significantly in the majority of the cases, as regards to different micrometeorological conditions. On the contrary, this plant parameter was significantly higher in 3rd compared to 1st measurement day in all examined conditions. The increase of 3,4-DCA uptake rates by maize plants grown under low relative humidity conditions, 72 hrs from AGS, could be associated with the expected acceleration of the plants transpiration rates and with the plant growth rate, as expressed by the fresh weight, as in these conditions plants remove considerably high volume of growth solution. The information obtained from the aforementioned results on plant uptake of 3,4-DCA in maize plants could be a first step in designing suitable management practices such as phytoremediation strategies which might reduce environmental pollution.

This study investigates the thermal and bioclimatic conditions in Erzurum plain and the nearby Palandoken Mountains. The data was obtained from Erzurum Meteorological Station (1758 m) and Palandoken Mountains Meteorological Station (2973 m) for 2009 and 2010 in order to compute physiologically equivalent temperatures (PET). The results indicated that the average annual PET value for Erzurum was -0.3 ºC while the corresponding value was -6.4 ºC for the Palandoken Mountains. The difference between the two locations was 6.3 ºC for 2009 and 5.9 ºC for 2010. During the summer months of 2009, the PET difference was 7.4 ºC while the corresponding difference was 6.4 ºC for 2010. During the winter months of 2009, the PET difference was 3.1 ºC while the corresponding difference was 3.7 ºC for 2010. It was determined that the 1179 m elevation difference between the two stations resulted in PET declines of 0.5 ºC for each 100 m. It was also observed that during days when the temperature is extremely low, due to the movement of cold spots to lower elevations, the PET values in Erzurum were observed to be lower than the ones in Palandoken mountains that are located only 13.5 km north-east of the city.

In Tunisian semi-arid regions, where water is a rare commodity and the large dams cannot be justified considering the very limited water contributions and the very high evapotranspiration, innovative techniques of harvesting water have been adopted. Tunisia has initiated a policy of small dam construction aiming to combine land and water management with socioeconomic development. They also target erosion control and protection of downstream infrastructure. Integrated rural development is achieved through the provision of a scarce but vital renewable resource. Using the results of multi-disciplinary research carried out in a network of 25 hill lakes implemented in a semi-arid area, the present article shows the role of small dams in the mobilization and management of water and soil resources. The issues involved in integrated development around hill reservoirs are closely linked to the sustainability of water. The agricultural development must be adapted to the life expectancy of the dam and the availability of water in dry periods. The recharge of the groundwater in the aquifers improves the potential for development. However, the impact of the stored water on health must be studied. The environmental impact of the lake structures is linked to the quality of the water and the maintenance of its supply.

The influence of microscale and mesoscale meteorology on the local scale variation of air temperature cannot be correctly simulated by the coarse resolution Global Climate Models. The scope of this work is to develop a hybrid dynamic-statistical downscaling procedure and quantify its predictive ability to estimate air temperature variability at finer spatial scales. The study focuses on the warm period of the year (June – August) and the method is applied to eight sites located in Greece with different topographical characteristics. The two-step methodology initially involves the dynamic downscaling of coarse resolution climate data via the RegCM4 regional climate model and subsequently the statistical downscaling of the modeled outputs by training site-specific artificial neural networks (ANN). The RegCM4 model is employed to enhance the representativity of the dataset, while the ANNs are used as function approximators to model the relationship between a number of atmospheric predictor variables and the observed air temperature time series. An insight of the ANN transfer function is obtained by examining the relative contribution of each input variable. The performance of the methodology is evaluated and the results indicate significant improvement from the inclusion of the ANN models in downscaling air temperature.