Estimating the long-term impact of market power on the welfare gains from groundwater markets

Environmental Economics and Policy Studies - Water markets are considered an effective groundwater management instrument. However, the emergence of market power during their operation, i.e., price...     

Levels of dioxins, furans and PCBs in human serum and milk of people living in Greece

In an attempt to evaluate the background levels of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), non-ortho, mono-ortho and indicator polychlorinated biphenyls (PCBs) in people living in an urban (Athens) and a rural (Kozani) area of Greece, blood serum and mother milk samples were analyzed. Analytical results are reported in this study. Statistically significantly differences were observed between regions, sexes and ages. Contamination levels in blood and human milk from Greece reported here are low compared to the previously reported dioxin data from other European countries and give no indication of particular health risk.     

Factors affecting accident severity inside and outside urban areas in Greece

Objectives: This research aims to identify and analyze the factors affecting accident severity through a macroscopic analysis, with a focus on the comparison between inside and outside urban areas. Disaggregate road accident data for Greece for the year 2008 were used. Methods: Two models were developed, one for inside and one for outside urban areas. Because the dependent variable had 2 categories, killed/severely injured (KSI) and slightly injured (SI), the binary logistic regression analysis was selected. Furthermore, this research aims to estimate the probability of fatality/severe injury versus slight injury as well as to calculate the odds ratios (relative probabilities) for various road accident configurations. The Hosmer and Lemeshow statistic and other diagnostic tests were conducted in order to assess the goodness-of-fit of the model. Results: From the application of the models, it appears that inside urban areas 3 types of collisions (sideswipe, rear-end, with fixed object/parked car), as well as involvement of motorcycles, bicycles, buses, 2 age groups (18-30 and older than 60?years old), time of accident, and location of the accident, seem to affect accident severity. Outside urban areas, 4 types of collisions (head-on, rear-end, side, sideswipe), weather conditions, time of accident, one age group (older than 60?years old), and involvement of motorcycles and buses were found to be significant. Conclusions: Factors affecting road accident severity only inside urban areas include young driver age, bicycles, intersections, and collision with fixed objects, whereas factors affecting severity only outside urban areas are weather conditions and head-on and side collisions, demonstrating the particular road users and traffic situations that should be focused on for road safety interventions for the 2 different types of networks (inside and outside urban areas). The methodology and the results of this research may provide a promising tool to prioritize programs and measures to improve road safety in Greece and worldwide.     

Sea-level rise impacts on Africa and the effects of mitigation and adaptation: an application of DIVA

This paper assesses sea-level rise impacts on Africa at continental and national scales including the benefits of mitigation and of applying adaptation measures, considering four scenarios of global mean sea-level rises from 64 to 126 cm in the period of 1995–2100. We find that in 2100, 16–27 million people are expected to be flooded per year, and annual damage costs range between US5 and US 5 and US 9 billion, if no adaptation takes place. Mitigation reduces impacts by 11–36%. Adaptation in the form of building dikes to protect against coastal flooding and nourishing beaches to protect against coastal erosion reduces the number of people flooded by two orders of magnitude and cuts damage costs in half by 2100. Following such a protection strategy would require substantial investment. First, Africa’s current adaptation deficit with respect to coastal flooding would need to be addressed. DIVA suggests that a capital investment of US300 billion is required to build dikes adapted to the current surge regime and US 300 billion is required to build dikes adapted to the current surge regime and US 3 billion per year for maintenance. In addition, between US2 and US 2 and US 6 billion per year needs to be spent on protecting against future sea-level rise and socio-economic development by 2100. This suggests that protection is not effective from a monetary perspective but may still be desirable when also taking into account the avoided social impact. We conclude that this issue requires further investigation including sub-national scale studies that look at impacts and adaptation in conjunction with the development agenda and consider a wider range of adaptation options and strategies.     

Flexible modeling for stock-recruitment relationships using Bayesian nonparametric mixtures

The stock and recruitment relationship is fundamental to the management of fishery natural resources. However, inferring stock-recruitment relationships is a challenging problem because of the limited available data, the collection of plausible models, and the biological characteristics that should be reflected in the model. Motivated by limitations of traditional parametric stock-recruitment models, we propose a Bayesian nonparametric approach based on a mixture model for the joint distribution of log-reproductive success and stock biomass. Flexible mixture modeling for this bivariate distribution yields rich inference for the stock-recruitment relationship through the implied conditional distribution of log-reproductive success given stock biomass. The method is illustrated with cod data from six regions of the North Atlantic, including comparison with simpler Bayesian parametric and semiparametric models.     

Forecasting daily pollen concentrations using data-driven modeling methods in Thessaloniki,Greece

Airborne pollen have been associated with allergic symptoms in sensitized individuals, having a direct impact on the overall quality of life of a considerable fraction of the population. Therefore, forecasting elevated airborne pollen concentrations and communicating this piece of information to the public are key issues in prophylaxis and safeguarding the quality of life of the overall population. In this study, we adopt a data-oriented approach in order to develop operational forecasting models (1–7 days ahead) of daily average airborne pollen concentrations of the highly allergenic taxa: Poaceae, Oleaceae and Urticaceae. The models are developed using a representative dataset consisting of pollen and meteorological time-series recorded during the years 1987–2002, in the city of Thessaloniki, Greece. The input variables (features) of the models have been optimized by making use of genetic algorithms, whereas we evaluate the performance of three algorithms: i) multi-Layer Perceptron, ii) support vector regression and iii) regression trees originating from distinct domains of Computational Intelligence (CI), and compare the resulting models with traditional multiple linear regression models. Results show the superiority of CI methods, especially when forecasting several days ahead, compared to traditional multiple linear regression models. Furthermore, the CI models complement each other, resulting to a combined model that performs better than each one separately. The overall performance ranges, in terms of the index of agreement, from 0.85 to 0.93 clearly suggesting the potential operational use of the models. The latter ones can be utilized in provision of personalized and on-time information services, which can improve quality of life of sensitized citizens.     

Metal leachability, heavy metals, polycyclic aromatic hydrocarbons and polychlorinated biphenyls in fly and bottom ashes of a medical waste incineration facility

Medical waste from hospitals and other healthcare institutions has become an imperative environmental and public safety problem. Medical waste in Greece has become one of the most urgent environmental problems, because there are 14,000 tons produced annually, of which only a small proportion is incinerated. In the prefecture of Attica there is only one modern municipal medical waste incinerator (started 2004) burning selected infectious hospital waste (5-6 tons day(-1)). Fly and bottom residues (ashes) are collected and stored temporarily in barrels. High values of metal leachability prohibit the landfilling of these ashes, as imposed by EU directives. In the present study we determined quantitatively the heavy metals and other elements in the fly and bottom ashes of the medical waste incinerator, by inductively coupled plasma emission spectrometry (ICP) and by energy dispersive X-ray analysis (EDAX). Heavy metals, which are very toxic, such as Pb, Cd, Ni, Cr, Cu and Zn were found in high concentrations in both fly and bottom ashes. Metal leachability of fly and bottom ashes by water and kerosene was measured by ICP and the results showed that toxic metals in both ashes, such as Pb, Cr, Cd, Cu and Zn, have high leaching values. These values indicate that metals can become soluble and mobile if ash is deposited in landfills, thus restricting their burial according to EU regulations. Analysis of polychlorinated biphenyls and polycyclic aromatic hydrocarbons in fly and bottom ashes showed that their concentrations were very low. This is the first known study in Greece and the results showed that incineration of medical waste can be very effective in minimizing the most hazardous and infectious health-care waste. The presence of toxic metals with high leachability values remains an important draw back of incineration of medical waste and various methods of treating these residues to diminish leaching are been considered at present to overcome this serious technical problem.