Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU

Investments in power generation constitute a typical budget allocation problem in the context of multiple objectives, while all factors influencing investor’s decisions for power plants are subject to considerable uncertainties. The paper introduces a multi-objective stochastic model designed to optimize budget allocation decisions for power generation in the context of risk aversion taking into account several sources of uncertainty, especially with regard to volatility of fossil fuel and electricity prices, technological costs, and climate policy variability. Probability distributions for uncertain factors influencing investment decisions are directly derived from the stochastic global energy model PROMETHEUS and thus they take into account complex interactions between variables in the systemic context. In order to fully incorporate stochastic characteristics of the problem, the model is specified as an optimization problem in which the probability that an objective exceeds a given threshold is maximized (risk aversion) subject to a set of deterministic and probabilistic constraints. The model is formulated as a mixed integer program providing complete flexibility on the joint distributions of rates of return of technologies competing for investments, as it can handle non-symmetric distributions and take automatically into account complex covariance patterns as emerging from comprehensive PROMETHEUS stochastic results. The analysis shows that risk is a crucial factor for power generation investments with investors not opting for technologies subject to uncertainty related to climate policies and fossil fuel prices. On the other hand, combination of options with negative covariance tends to benefit in the context of risk-hedging behavior.     

Increasing extremes of heat and drought associated with recent severe wildfires in southern Greece

Mountains of the northern Mediterranean basin face two major threats under global change. Aridity and available fuel are both expected to increase because of climatic and land-use changes, increasing fire danger. There may already be signs of such effects in the case of the Pinus nigra and Abies cephalonica forests on Mt. Taygetos (southern Greece). We reconstructed climate (mid- to late-fire-season drought) using tree-rings for the last 150 years and compared it with the mountain’s fire history reconstructed from P. nigra fire scars. Seven, out of the ten, large fires Mt. Taygetos experienced were associated with below-normal precipitation (P) or above-normal maximum temperature (T _max). The largest fires occurred in late summer of 1879, 1944, 1998, and 2007. However, only the recent fires (1998 and 2007) had both low P and high T _max, also confirmed from long-term meteorological data. The synergy between climate and fuel availability may explain the very high intensity of 1998 and 2007 fires that burned mostly as stand-replacing crown fires. The other two large fire events (1879 and 1944) most likely occurred under reduced availability in burning fuel and were related to above-normal T _max. Our findings are among the first based on long-term and site-specific empirical data to support the prediction that Mediterranean mountainous areas will face a very large threat from wildfires in the twenty-first century, if socioeconomic changes leading to land abandonment and thus burning fuel accumulation are combined with the drought intensification projected for the region under global warming.     

Validation of oxidative stress responses in two populations of frogs from Western Ukraine

Although amphibians are considered to be good bioindicators of environmental pollution, few data are available concerning their biochemical parameters in natural populations. We investigated seasonal (spring, summer, autumn) and spatial (wetlands in rural and urban areas) fluctuations of oxidative stress biomarkers in the liver of frog Rana ridibunda in Western Ukraine. The Centroid grouping analysis demonstrated that despite the fluctuations of separate indices, frogs from an urban site in summer and autumn are differed widely from those at the same site in spring and frogs from the rural site in all three seasons, joined in common set. In summer, suppression of Mn-superoxide dismutase and catalase activity, as well as increase in oxidized glutathione and lipid peroxidation levels demonstrate a collapse of antioxidant defense system in frogs from an urban site. The integrated oxidative stress index confirms this conclusion.     

Determination of dithiocarbamate fungicide propineb and its main metabolite propylenethiourea in airborne samples

A simple, rapid and sensitive GC–MS method for the determination of dithiocarbamate fungicide propineb [polymeric zinc propylenebis (dithiocarbamate)] and an improved HPLC procedure for the simultaneous determination of its main metabolite, propylenethiourea, and ethylenethiourea, the main metabolite of all ethylenedithiocarbamates, in airborne samples are described. The method for the analysis of propineb involves the evolution of carbon disulfide (CS₂), under acidic conditions in the presence of stannous chloride, extraction of the generated CS₂ into a layer of isooctane which is then analyzed for CS₂ content by GC–MS in SIM mode. Under the optimum conditions, the retention time of CS₂ was 1.89 min and the total time of chromatographic analysis was 5 min. Recoveries from spiking glass microfibre filters (GF/A) and silica gel filters were 86 ± 7 (n = 9) and 89 ± 4 (n = 9), respectively. The limit of detection is 0.7 ng per filter, which is equivalent to about 0.8–1.0 ng m⁻³ in air. In parallel, an HPLC method with ultraviolet detection is presented for the simultaneous analysis of the metabolites. Separation of the two metabolites was attained in less than 5 min. Recoveries from spiking GF/A and silica gel filters for ethylenethiourea were 100 ± 1 (n = 3) and 98 ± 2 (n = 3), respectively, while for propylenethiourea were 102 ± 1 (n = 3) and 98 ± 1 (n = 3), respectively. The detection limits are about 36–43 and 40–49 ng m⁻³ in air for ethylenethiourea and propylenethiourea, respectively. All the analytes spiked in the filters are proven to be stable for more than one month, at −4 °C.     

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.     

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.     

An alternative method for the treatment of waste produced at a dye and a metal-plating industry using natural and/or waste materials.

The aim of this study was to develop cost-effective, appropriate solidification technologies for treating hazardous industrial wastes that are currently disposed of in ways that may threaten the quality of local groundwater. One major objective was to use materials other than cement, and preferably materials that are themselves wastes, as the solidification additives, namely using wastes to treat wastes or locally available natural material. This research examines the cement-based and lime-based stabilization/solidification (S/S) techniques applied for waste generated at a metal-plating industry and a dye industry. For the lime-based S/S process the following binder mixtures were used: cement kiln dust/ lime, bentonite/lime and gypsum/lime. For the cement-based S/S process three binder mixtures were used: cement kiln dust/cement, bentonite/cement and gypsum/cement. The leachability of the wastes was evaluated using the toxicity characteristic leaching procedure. The applicability and optimum weight ratio of the binder mixtures were estimated using the unconfined compressive strength test. The optimum ratio mixtures were mixed with waste samples in different ratios and cured for 28 days in order to find the S/S products with the highest strength and lowest leachability at the same time. The results of this work showed that the cement-and lime-based S/S process, using cement kiln dust and bentonite as additives can be effectively used in order to treat industrial waste.     

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.     

Driving in mild cognitive impairment: The role of depressive symptoms

Objectives: Previous studies indicate a negative association between depression and driving fitness in the general population. Our goal was to cover a gap in the literature and to explore the link between depressive symptoms and driving behavior in individuals with mild cognitive impairment (MCI) through the use of a driving simulator experiment.

Methods: Twenty-four individuals with MCI (mean age = 67.42, SD = 7.13) and 23 cognitively healthy individuals (mean age = 65.13, SD = 7.21) were introduced in the study. A valid driving license and regular car use served as main inclusion criteria. Data collection included a neurological/neuropsychological assessment and a driving simulator evaluation. Depressive symptomatology was assessed with the Patient Health Questionnaire (PHQ-9).

Results: Significant interaction effects indicating a greater negative impact of depressive symptoms in drivers with MCI than in cognitively healthy drivers were observed in the case of various driving indexes, namely, average speed, accident risk, side bar hits, headway distance, headway distance variation, and lateral position variation. The associations between depressive symptoms and driving behavior remained significant after controlling for daytime sleepiness and cognition.

Conclusions: Depressive symptoms could be a factor explaining why certain patients with MCI present altered driving skills. Therefore, interventions for treating the depressive symptoms of individuals with MCI could prove to be beneficial regarding their driving performance.