Volume 19 - 2017

The composite media, ZeliacTM was developed with the initial aim to provide low cost adsorbent with promising adsorption capacity. This study was conducted to investigate the removal of UV absorbance at 254 nm (UV254) in Kerian river water using ZeliacTM as the media. Batch experiments study was carried out to determine the optimum removal of UV254 by ZeliacTM. The experimental data were fitted to Langmuir and Freundlich isotherms to investigate the adsorption mechanism. The results from batch study exhibit that ZeliacTM is capable to remove 74.4% UV254 at the dosage of 7g/100 ml. Linear isotherm analysis suggests that the best fitting linear line is Freundlich isotherm with R2 values of 0.9294 indicating multilayer adsorption. Similarly, non-linear regression analysis reveals that the adsorption of UV254 by ZeliacTM is attributed by physisorption. The non-linear Freundlich isotherm gives a better fit to the adsorption of UV254 than Langmuir isotherm with R2 values of 0.9488. The results are supported with low values of X2, ARE, HYBRID and MPSED from the error function analysis.  Additionally, it is noted that the linear analysis overestimates the constant parameters’ values for Freundlich isotherm, which cause larger errors as estimated by the error function analysis. Hence, non-linear analysis is more appropriate in explaining the batch experiment data.

The scientific community has recognized the necessity for more efficiently selected inputs in artificial neural network models (ANNs) in river flows and has worked on this despite some shortcomings. Moreover, there is none or limited inclusion of ANN inputs coupled with atmospheric circulation under various patterns arising from the need of data downscaling for climate change predictions in hydrology domain. This paper presents the results of a novel multi-stage methodology for selecting input variables used in artificial neural network (ANN) models for river flow forecasting. The proposed methodology makes use of data correlations together with a set of crucial statistical indices for optimizing model performance, both in terms of ANN structure (e.g. neurons, momentum rate, learning rate, activation functions, etc), but also in terms of inputs selection. The latter include various previous time steps of daily areal precipitation and temperature data coupled with atmospheric circulation in the form of circulation patterns, observed river flow data and time expressed via functions of sine and cosine. Additionally, the no-linear behavior between river flow and the respective inputs is investigated by the ANN configuration itself and not only by correlation indices (or other equivalent contingency tools). The proposed methodology revealed the river flow of past four days, the precipitation of past three days and the seasonality as robust input variables. However, the temperature of three past days should be considered as an alternative against the seasonality. The produced models forecasting ability was validated by comparing its one-step ahead flow prediction ability to two other approaches (an auto regressive model and a genetic algorithm (GA)-optimized single input ANN). 

In this study, the post-fire regeneration of three coniferous species (Pinus brutia, Cupressus sempervirens and Cupressus arizonica) was examined in the peri-urban forest of Thessaloniki, Northern Greece. The wildfire took place in July 1997 and burned almost 60% of the forest vegetation. During the autumn of 2010, 34 experimental plots were established in all aspects within the burned area. In each experimental plot the following measurements were carried out: height, diameter at breast height and crown projection in two perpendicular diameters. The results show that the Pinus brutia individuals, most of which came from natural regeneration, presented the best growth, in relation to the two other species in all aspects. As for Cupressus sempervirens, equal parts of which came from natural and artificial regeneration was characterized by remarkable growth especially in the Northeastern aspect. Finally, Cupressus arizonica existed in all aspects except the Northeastern. It also presented a satisfactory development, especially on the Southern aspect. Fourteen years after the fire pure or mixed stands of the above mentioned species show vigorous growth and good stem quality. Finally, the rates of participation of individual forest species indicate that the restoration has been achieved mainly by natural regeneration.

The aim of this study is to achieve a greater insight regarding quiet areas in agglomerations and contribute to their identification. The small urban setting of Mytilene located in the island of Lesvos (North Aegean, Greece), was the case study of this research. The need to control and manage environmental noise has led to the implementation of legislation that in many cases overlooks the acoustic perception of individuals. Due to the fact that noise management efforts along with the promotion of quietness in agglomerations, concerns primarily the residents of the city under consideration, it was essential to practically involve them in the decision making process.  Based on citizen science contribution, a number of “places” were highlighted. The “places” mentioned from this procedure were checked by means of acoustic measurements, concerning the noise levels that occurred within the 24h period. A novel method regarding the duration, repetition, check spot and the positioning of measurement was used, in order to calculate the day, evening and night period’s noise levels (Lden). A performance matrix was then created in order to compare the results, in relation to acoustical, functional and visual criteria. Furthermore, in order to evaluate all the potential Quiet Areas in pairwise comparisons, an Analytical Hierarchy Process (AHP) was implemented. The provision of quietness, as a direct ecosystem service, is a major indicator of environmental quality. Additionally, the way that city inhabitants perceive their acoustic surroundings could determine the character of the landscape along with the quality of the soundscape and define the meaning of quietness that still remains vague.