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This study deals with the flood-hazard assessment and mapping in the catchment of Megalo Rema (East Attica, Greece). Flood-hazard zones were identified utilizing Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information System (GIS). Five factors were considered as the most influential parameters for the water course when high storm-water runoff exceeds drainage system capacity and were taken into account. These factors include slope, elevation, distance from stream channels, geological formations in terms of their hydro-lithological behavior and land cover. To obtain the final weights for each factor, rules of the Analytic Hierarchy Process (AHP) were applied. The final flood-hazard assessment and mapping of the study area were produced through Weighted Linear Combination (WLC) procedures. The final map showed that approximately 26.3 km2, which corresponds to 22.7% of the total area of the catchment, belongs to the high flood risk zone, while approximately 25 km2, corresponding to ~15% of the catchment, is of very high flood risk. The highly and very highly prone to flooding areas are located mostly at the southern and western parts of the catchment. Furthermore, the areas on both sides of the channel along the lower reaches of the main stream are of high and very high risk. The highly and very highly prone to flooding areas are relatively low-lying, gently sloping and extensively urbanized, and host the densely populated settlements of Rafina-Pikermi, Penteli, Pallini, Peania, Spata, Glika Nera, Gerakas and Anthousa. The accuracy of the flood-hazard map was verified by correlating flood events of the last 30 years, the Hydrologic Engineering Center’s River Analysis System (HEC–RAS) simulation and quantitative geomorphological analysis with the flood-hazard level. The results of our approach provide decision makers with important information for land-use planning at a regional scale, determining safe and unsafe areas for urban development.

This review summarizes the recent advances in light driven catalytic H2evolution and CO2reduction systems towards the production of solar fuels, utilizing porphyrin or phthalocyanine derivatives.

In a world with climate change and environmental pollution, modern Biology is concerned with organismic susceptibility. At the same time, policy and decision makers seek information about organismic susceptibility. Therefore, information about organismic susceptibility may have far-reaching implications to the entire biosphere that can extend to several forthcoming generations. Here, we review a sample of approximately 200 published peer-reviewed articles dealing with plant response to ground-level ozone to understand how the information about susceptibility is communicated. A fuzzy and often incorrect terminology was used to describe the responsiveness of plants to ozone. Susceptibility was classified too arbitrarily and this was reflected to the approximately 50 descriptive words that were used to characterize susceptibility. The classification of susceptibility was commonly based on calculated probability (p) value. This practice is inappropriate as p values do not provide any basis for effect or susceptibility magnitude. To bridge the gap between science and policy decision making, classification of susceptibility should be done using alternative approaches, such as effect size estimates in conjunction with multivariate ordination statistics.

Geostatistical techniques were applied and a series of spatial indicators were calculated (occupation, aggregation, location, dispersion, spatial autocorrelation and overlap) to characterize the spatial distributions of European anchovy and sardine during summer. Two ecosystems were compared for this purpose, both located in the Mediterranean Sea: the Strait of Sicily (upwelling area) and the North Aegean Sea (continental shelf area, influenced by freshwater). Although the biomass of anchovy and sardine presented high interannual variability in both areas, the location of the centres of gravity and the main spatial patches of their populations were very similar between years. The size of the patches representing the dominant part of the abundance (80%) was mostly ecosystem- and species-specific. Occupation (area of presence) appears to be shaped by the extent of suitable habitats in each ecosystem whereas aggregation patterns (how the populations are distributed within the area of presence) were species-specific and related to levels of population biomass. In the upwelling area, both species showed consistently higher occupation values compared to the continental shelf area. Certain characteristics of the spatial distribution of sardine (e.g. spreading area, overlapping with anchovy) differed substantially between the two ecosystems. Principal component analysis of geostatistical and spatial indicators revealed that biomass was significantly related to a suite of, rather than single, spatial indicators. At the spatial scale of our study, strong correlations emerged between biomass and the first principal component axis with highly positive loadings for occupation, aggregation and patchiness, independently of species and ecosystem. Overlapping between anchovy and sardine increased with the increase of sardine biomass but decreased with the increase of anchovy. This contrasting pattern was attributed to the location of the respective major patches combined with the specific occupation patterns of the two species. The potential use of spatial indices as auxiliary stock monitoring indicators is discussed.

Abstract Wind climate analysis and modelling is of most importance during site selection for offshore wind farm development. In this regard, reliable long-term wind data are required. Buoy measurements are considered as a reference source in relevant applications including evaluation and calibration of wind data obtained from less reliable sources, combined assessment, blending and homogenization of multi-source wind data, etc. Most of these applications are based on regression techniques elaborated by using the principle of ordinary least squares (OLS). However, wind data usually contain several outliers, which may question the validity of the regression analysis, if not properly considered. This study is focused on the implementation of the most important robust regression methods, which can identify and reveal outliers, and retain at the same time their efficiency. Long-term reference wind data series obtained from buoys at six locations in the Mediterranean Sea are used to calibrate hindcast (model) wind data by applying robust methods and OLS. The obtained results are compared according to several statistical measures. The effects of the calibration methods are also assessed with respect to the available wind power potential. The results clearly suggest that least trimmed squares and L1-estimator perform in all respects better than OLS.

Liquid biowaste represents more than 98% of the total municipal waste streams on wet basis and 4–5% on dry basis. Recent attention has been focused on how to manage it optimally, and several novel technologies are being developed to valorize it. Among the developing alternatives is a technology that operates continuously by integrating a hydrothermal reactor, a gasifier and condenser to recover hydrochar using any produced gases to power the system. This study introduces the “3-step evolution model” in order to simulate the hydrothermal reactor. The model has been developed in a MATLAB/Cantera environment and calculates the outputs as the products of a series of sub-stoichiometric char-gas reactions. Experiments with chicken manure slurry as feedstock were implemented for the validation of the model. Treatment of 32.16 kg/h of chicken manure produces 4.57 kg/h of hydrochar and 3.45 kg/h of syngas. The 3-step evolution model simulated the correct ratio of solid-to-gas, 57–43% (excluding the liquids). The experimentally measured carbon dioxide is used as a correction factor to calculate all the other parameters that cannot be assessed during the continuous operation of the hydrothermal reactor. The simulated compositions for carbon dioxide and methane were 94–96% and 0.5–0.8%, respectively. The values were close to the experimental results that ranged from 94.7% to 95.6% for the carbon dioxide and from 0.5% to 0.7% for the methane. The model predicts that higher temperatures of operation would increase carbon monoxide composition from 4–5% up to 7–8%.

This work intended to explore some motivations that influence people’s eating habits towards sustainability. This was an observational, cross-sectional study, carried out by questionnaire survey on a non-probabilistic sample of 10,067 participants from 13 countries (Argentina, Brazil, Croatia, Greece, Hungary, Latvia, Lithuania, Poland, Portugal, Serbia, Slovenia, Romania and United States). Results indicated that people prefer fresh local foods from the season, being important because it allows transportation and storage to be reduced, which in many cases implies refrigeration systems and consequent energy expenditure. Although people avoid food waste at home, the awareness for the waste at restaurants still needs to be improved. Consumers seem to prefer foods that have been produced and packed in sustainable ways but still give importance to the package—understandable for food products. The results also indicated significant differences in the food choice motivations between groups for all sociodemographic variables tested (age, sex, marital status, education, professional area, living environment and country), but the association was high only for variable country. Additionally, a tree classification analysis allowed to identify the relative importance of the influential variables on the sustainable food choices, with country being the most important, followed by age and sex. Additionally, discriminant function analysis allowed establishing a model for the relation between country and six variables accounting for preservation of biodiversity, respect for life, save natural resources, save energy, reduce industrial pollution and minimal packaging. Although with some limitations, this study brings valuable insight into some aspects linked with sustainable food choices on a number of countries and how people shape their food choices according to some sustainability issues.

A stochastic age-structured population model was developed to explore biologically favourable levels of effort and closing periods within the sardine pelagic fishery in the eastern Mediterranean Sea. Results suggested that the developed age-structured model captured the observed biomass fluctuations and catches reasonably well and represents the first comprehensive investigation of alternative management strategies for eastern Mediterranean sardine fishery that include stochasticity. The present study provided direct evidence for the importance of the correct timing of the temporal fishing ban. Significant benefits were found both in terms of biomass and catch from a corrective shift in the fishing closed period. The current findings suggested that protecting the younger age groups from fishing in the period October-December, by shifting the ban period earlier than December may profit, biologically, the stock and economically the fishing sector. Progressive reductions in fishing mortality/effort also yield significant positive biological and fishery benefits in the short term.