An Aegean island earthquake protection strategy: an integrated analysis and policy methodology

Viewing an insular setting as a distinct risk environment, an effort is made here to develop a methodology for identifying core issues related to earthquake risk and disaster protection policy, adjusted to the 'specificities' of such a context. The methodology's point of departure is the inherent condition of the 'island operating as a closed system', requiring an attempt to assess and optimise local capacity (social, political, economic, institutional and technical) to deal with an earthquake emergency. The island is then treated as an 'open system', implying that in the event of a disaster, it should be able to maximise its ability to receive and distribute external aid and to manage effectively population evacuation and inflows/outflows of aid resources. Hence, an appropriate strategic policy approach could be developed by integrating the 'open' and 'closed' system components of an island setting. Three islands from the Aegean Archipelagos in Greece--Chios, Kos and Nissyros--serve as case study areas.     

Inverse modeling for effective dispersal: Do we need tree size to estimate fecundity?

The estimation of the dispersal kernel for the seedling and sapling stages of the recruitment process was made possible through the application of inverse modeling to dispersal data. This method uses the spatial coordinates of adult trees and the counts of seedlings (or saplings) in small quadrats to estimate the dispersal kernel. The unknown number of recruits produced by an adult tree (the fecundity) is estimated - simultaneously with the dispersal kernel - via an allometric linear model relating the unknown quantity with a (easily) measured characteristic of the adult tree (usually the basal area). However, the allometric relation between tree size and reproductive success in the sapling (or seedling) stage may not be strong enough when numerous, well-documented, post-dispersal processes (such as safe-site limitation for recruitment) cause large post-dispersal seedling mortality, which is usually unrelated to the size of the tree that dispersed them. In this paper we hypothesize that when tree size and reproductive success in the seedling/sapling stage are not well correlated then the use of allometry in inverse modeling is counter-productive and may lead to poor model fits. For these special cases we suggest using a new model for effective dispersal that we term the unrestricted fecundity (UF) model that, contrary to allometric models, makes no assumptions on the fecundities; instead they are allowed to vary freely from one tree to another and even to be zero for trees that are reproductively inactive. Based on this model, we examine the hypothesis that when tree size and reproductive success are weakly correlated and the fecundities are estimated independently of tree size the goodness-of-fit and the ecological meaning of dispersal models (in the seedling or sapling stage) may be enhanced. Parameters of the UF model are estimated through the EM algorithm and their standard errors are approximated via the observed information matrix. We fit the UF model to a dataset from an expanding European beech population of central Spain as well as to a set of simulated dispersal data were the correlation between reproductive success and tree size was moderate. In comparisons with a simple allometric model, the UF model fitted the data better and the parameter estimates were less biased. We suggest using this new approach for modeling dispersal in the seedling and sapling stages when tree size (or other adult-specific covariates) is not deemed to be in strong relation to the reproductive success of adults. Models that use covariates for modeling the fecundity of adults should be preferred when reproductive success and tree size guard a strong relationship.     

Hydrology and pollution of lake vistonis in Northern Greece

The basic objective of this study is the understanding of the hydrology and hydraulic characteristics of Lake Vistonis, a very shallow lake in Northern Greece, connected to the Aegean Sea through an irregular shallow channel. In this paper we estimate the pollutant residence time and the discharge of lake to the Aegean Sea as a function of lake elevation. Also we determine the seasonal variations of salinity of the lake.     

Local deposition of mercury in topsoils around coal-fired power plants: is it always true?

Mercury (Hg) is a toxic element that is emitted to the atmosphere through human activities, mainly fossil fuel combustion. Hg accumulations in soil are associated with atmospheric deposition, while coal-burning power plants remain the most important source of anthropogenic mercury emissions. In this study, we analyzed the Hg concentration in the topsoil of the Kozani–Ptolemais basin where four coal-fired power plants (4,065 MW) run to provide 50 % of electricity in Greece. The study aimed to investigate the extent of soil contamination by Hg using geostatistical techniques to evaluate the presumed Hg enrichment around the four power plants. Hg variability in agricultural soils was evaluated using 276 soil samples from 92 locations covering an area of 1,000 km². We were surprised to find a low Hg content in soil (range 1–59 μg kg^?1) and 50 % of samples with a concentration lower than 6 μg kg^?1. The influence of mercury emissions from the four coal-fired power plants on soil was poor or virtually nil. We associate this effect with low Hg contents in the coal (1.5–24.5 μg kg^?1) used in the combustion of these power plants (one of the most Hg-poor in the world). Despite anthropic activity in the area, we conclude that Hg content in the agricultural soils of the Kozani–Ptolemais basin is present in low concentrations.     

A multi-objective programming model for assessment the GHG emissions in MSW management

In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH₄ generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region.     

Exposure of Tribolium castaneum (Herbst) females to pirimiphos-methyl alters the fitness of their progeny

Environmental Science and Pollution Research - Insecticidal treatment is a common practice for the control of stored-product insect pests. Most studies are focused on the direct effects of...     

Analysis of air quality observations with the aid of the source-receptor relationship approach

In this study, an attempt was made to analyze time series of air quality measurements (O3, SO2, SO4(2-), NOx) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify "areas of influence" have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of "areas of influence." When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).     

Analysis of Air Quality Observations with the Aid of the Source-Receptor Relationship Approach

Abstract

In this study, an attempt was made to analyze time series of air quality measurements (O₃, SO₂, SO₄ ^2?NO_x) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify “areas of influence” have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of “areas of influence.” When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).