Greenhouse gas emissions from two hydroelectric reservoirs in Mediterranean region

Water reservoirs are used for many purposes, such as water supply, irrigation, flood mitigation, and hydroelectric energy generation. Although hydroelectric energy is considered “green,” many studies show that the construction of a reservoir enhances greenhouse gas (GHG) emissions at the transformed area. These emissions, mainly of CO₂, CH₄, and N₂O gases, depend on the age of the reservoir, landscape and soil composition, fauna and flora remnants of the impounded area, climatic conditions, and basin runoffs. Consequently, GHG emissions significantly vary between reservoirs and depending on local specificities. Several studies have investigated GHG emissions from reservoirs around the world, focusing mainly on reservoirs located in cold regions, temperate regions, and tropical regions. Research is lacking for reservoirs in Mediterranean countries, like Greece, and similar regions. This work initially assesses the net GHG emissions of a newly created reservoir (Ilarion est. 2012) in Western Macedonia, Greece. The methodology for net GHG emission calculation was based on the use of literature data concerning pre-impoundment emission factors and local specificities of the reservoir (terrain type, canopy cover), as well as on the 2-year measurement data that were collected using a “static floating chamber.” Furthermore, in this work, the gross GHG emissions of an older, in-line reservoir (Polyfytos est. 1974) were also calculated, based on 2-year measurement data. The results show that the global warming potential (GWP) of the reservoirs is dictated by methane emissions; it minimizes during winter and spring and maximizes during summer and autumn. Hydroelectric energy production at Ilarion Reservoir results in 32 to 97 times less total CO₂ equivalent emissions in comparison to fossil fuels, while at Polyfytos Reservoir only 8 to 24 times less (based on gross emissions). It appears that the impact of a reservoir’s morphology on GHG emissions is more significant than that of a reservoir’s age.     

Quantification of Water, Salt and Nutrient Exchange Processes at the Mouth of A mediterranean Coastal Lagoon

Vassova lagoon is a typical Mediterranean (small, shallow, micro-tidal, well-mixed) coastal lagoon, receiving limited seasonal freshwater inflows from direct precipitation and underground seepage. An intensive study was carried out in order to quantify the mechanisms responsible for the intra-tidal and residual transport of water, salt, nutrients and chlorophyll at the mouth of this lagoon and to assess the lagoon's flushing behavior. Results indicated that although the system is micro-tidal, tidal effects appeared to be the dominant factor for the longitudinal distribution of physical and chemical parameters, while the associated residual flow is also important and serves as a baseline measure of overall circulation. However, analysis of the net longitudinal currents and fluxes of water, salt and nutrients revealed the importance of non-tidal effects (wind effect and precipitation incidents) in the mean tidal transport. It is shown that the Eulerian residual currents transported water and its properties inwards under southern winds, while a seaward transport was induced during precipitation incidents and northern winds. The Stokes drift effect was found an order of magnitude lower than the Eulerian current, directed towards the lagoon, proving the partially-progressive nature of the tide. Nutrients and chlorophyll-α loads are exported from the lagoon to the open sea during the ebb phase of the autumn and winter tidal cycles, associated with the inflow of nutrient-rich freshwater, seeped through the surrounding drainage canal. The reverse transport occurs in spring and early summer, when nutrients enter the lagoon during the flood tidal phase, from the nutrient-rich upper layer of the stratified adjacent sea. Application of a tidal prism model shows that Vassova lagoon has a mean flushing time of 7.5 days, ranging between 4 to 18 days, affected inversely by the tidal oscillation.     

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.     

Neural Network and Multiple Regression Models for PM10 Prediction in Athens: A Comparative Assessment

Abstract

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 µm (PM₁₀) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2–9.4%) and of episodic prediction ability (false alarm rate values lower by 7–13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.     

The Narrative Cycle of Climate Change in the Greek Newspapers, 2001–2008

This paper aims to establish whether the longitudinal framing of climate change (CC) in Greek newspapers exhibits the characteristics of a “narrative cycle,” with different themes becoming prominent at different periods in accordance with the media’s narrative considerations. In order to test this assumption, we formulate a number of hypotheses which we test with data originating from three Greek newspapers over the period 2001–2008. We find that the scientific and ecological/meteorological themes of CC are more often mentioned during the initial phase of media coverage, arguably due to media’s attempt to open the narrative and capture the public’s attention. Public protests and debate feature more prominently during the peaked phase of coverage, in accordance with the narrative need for a climax, while the later period of coverage, when some kind of resolution to the story should be offered, is characterized by the prominence of policy-making and economy-related issues.     

Wastewater substrate disinfection for cyanobacteria cultivation as tertiary treatment

Environmental Science and Pollution Research - Cultivation of microalgae or/and cyanobacteria in nutrient-rich wastewaters offers an opportunity for enhancing sustainability of tertiary wastewater...     

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)...     

Coastal landscape and the Greek spatial planning: evidence from windpower in the South Aegean islands

This paper discusses issues about the coastal and the insular landscape integration in the Greek spatial planning framework. Case study area is the region of the South Aegean, where the proliferation of wind turbines is one of the principal factors of landscape change. The methodological approach adopted is mainly quantitative and is based on viewshed analysis. This paper is also demonstrates that zones with varying impact on landscape can be identified. It also emerges that the spatial planning framework in Greece promotes an ad hoc project-led instead of a plan-based approach to coastal and insular landscape management.