Assessing the zooplankton community and environmental factors in a Mediterranean wetland

Mediterranean wetlands represent unique repositories of biodiversity, but these ecosystems are increasingly threatened by human-induced habitat loss. Seventy percent of Greek wetlands (ponds, mires, marshes, etc.) have been lost in the past 80 years due to human intervention. In Greece habitat types of mires, listed in Directive 92/43/EEC, have been recorded in a few locations, one of the most important is Kalodiki wetland. Eutrophication key elements were determined at four sampling stations throughout 1 year in order to monitor the trophic conditions. Moreover, the zooplankton community was described as biological element relevant in the assessment of the ecological status of Kalodiki wetland. Kalodiki wetland exhibits nutrient concentrations corresponding to eutrophic conditions while according to chlorophyll-a values it is classified between mesotrophic and eutrophic status depending mostly on the sampling period. As concerning zooplankton community, it appears poor in species and dominated by small-sized organisms, which is generally typical of eutrophic, disturbed systems. Differences among zooplankton assemblages over seasons as well as among sampling sites highlight the role of both abiotic and biotic factors.     

Arsenate removal from drinking water using by-products from conventional iron oxyhydroxides production as adsorbents coupled with submerged microfiltration unit

Environmental Science and Pollution Research - Arsenic is among the major drinking water contaminants affecting populations in many countries because it causes serious health problems on long-term...     

Biogas upgrading to methane and removal of volatile organic compounds in a system of zero-valent iron and anaerobic granular sludge

Environmental Science and Pollution Research - The current study presented a novel process of biogas upgrading to biomethane (higher than 97%) based on anaerobic sludge and zero-valent iron (ZVI)...     

Adverse Effects on Alfeios River Basin and an Integrated Management Framework Based on Sustainability

The Alfeios River, the longest and highest flow-rate river in Peloponnisos, constitutes an important water resource and ecosystem in Greece. In the present study, human activities in the Alfeios River Basin are described, and their impacts on water quality and the ecosystem are analyzed; effects resulting from interventions on river geomorphology between Flokas Dam and the river delta are determined. These actions have caused significant adverse impacts on the infrastructure (the dam, railroad, and road bridges), the level of aquifer water table and area water uses, and the aquatic and riparian ecosystem. A general integrated management strategy is formulated and a master management plan is proposed for resolving management problems in river basins. The plan considers local conditions and national requirements and complies with the European Communities legislation; it would help prevent further basin deterioration, improve water quality, and protect water resources and ecosystems in the area in accordance to sustainable development. The Alfeios River Basin serves as a case study in the development of the plan.Published online Note: This version was published online in June 2005 with the cover date of August 2004.     

Combining neural network models to predict spatial patterns of airborne pollutant accumulation in soils around an industrial point emission source

Neural networks (NNs) have the ability to model a wide range of complex nonlinearities. A major disadvantage of NNs, however, is their instability, especially under conditions of sparse, noisy, and limited data sets. In this paper, different combining network methods are used to benefit from the existence of local minima and from the instabilities of NNs. A nonlinear k-fold cross-validation method is used to test the performance of the various networks and also to develop and select a set of networks that exhibits a low correlation of errors. The various NN models are applied to estimate the spatial patterns of atmospherically transported and deposited lead (Pb) in soils around an historical industrial air emission point source. It is shown that the resulting ensemble networks consistently give superior predictions compared with the individual networks because, for the ensemble networks, R2 values were found to be higher than 0.9 while, for the contributing individual networks, values for R2 ranged between 0.35 and 0.85. It is concluded that combining networks can be adopted as an important component in the application of artificial NN techniques in applied air quality studies.     

Determining Visitors’ Dispositions Toward the Designation of a Greek National Park

This article presents the findings of the first major visitor survey conducted at the Central Rhodope Mountain Complex, situated in northern Greece. The study area is one of a number of sites planned to become National Parks under a recent initiative of the Greek government. We used a logistic regression method to define significant predictors of visitors’ awareness and attitude toward park designation, as well as their willingness to pay a conditional entrance fee. Study findings demonstrated that the probability of being aware of the park designation initiative is higher for visitors who obtained information from travel agencies or media to make their destination choice, compared to visitors who resorted to word-of-mouth recommendations. Knowledge and attitudes toward animals living in the study area revealed a limited influence on visitors’ dispositions toward park designation. The results of this study call for action to implement education programs for National Park users. These programs should aim at rendering the environmental characteristics of the Central Rhodope Mountain Complex to be significant predictors of visitors’ dispositions toward the study area. This would favor its uniqueness as a destination, as well as contribute to its long-term economic sustainability.