A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.     

Mapping fire behaviour under changing climate in a Mediterranean landscape in Greece

Understanding how future climate periods influence fire behaviour is important for organizing fire suppression strategy and management. The meteorological factors are the most critical parameters affecting fire behaviour in natural landscapes; hence, predicting climate change effects on fire behaviour could be an option for optimizing firefighting resource management. In this study, we assessed climate change impacts on fire behaviour parameters (rate of fire growth, rate of spread and fireline intensity) for a typical Mediterranean landscape of Greece. We applied the minimum travel time fire simulation algorithm by using the FlamMap software to characterize potential response of fire behaviour for three summer periods. The results consisted of simulated spatially explicit fire behaviour parameters of the present climate (2000) and three future summer periods of 2050, 2070 and 2100, under the A1B emissions scenario. Statistical significant differences in simulation outputs among the four examined periods were obtained by using the Tukey’s significance test. Statistical significant differences were mainly obtained for 2100 compared to the present climate due to the significant projected increase in the wind speed by the end of the century. The analysis and the conclusions of the study can be important inputs for fire suppression strategy and fire management (deployment of fire suppression resources, firefighter safety and exposure, transportation logistics) quantifying the effect that the expected future climate periods can have on fire suppression difficulty in Mediterranean landscapes.     

Inference and model determination for temperature-driven non-linear ecological models

Environmental and Ecological Statistics - This paper is concerned with a contemporary Bayesian approach to the effect of temperature on developmental rates. We develop statistical methods using...     

Combining neural network models to predict spatial patterns of airborne pollutant accumulation in soils around an industrial point emission source

Neural networks (NNs) have the ability to model a wide range of complex nonlinearities. A major disadvantage of NNs, however, is their instability, especially under conditions of sparse, noisy, and limited data sets. In this paper, different combining network methods are used to benefit from the existence of local minima and from the instabilities of NNs. A nonlinear k-fold cross-validation method is used to test the performance of the various networks and also to develop and select a set of networks that exhibits a low correlation of errors. The various NN models are applied to estimate the spatial patterns of atmospherically transported and deposited lead (Pb) in soils around an historical industrial air emission point source. It is shown that the resulting ensemble networks consistently give superior predictions compared with the individual networks because, for the ensemble networks, R2 values were found to be higher than 0.9 while, for the contributing individual networks, values for R2 ranged between 0.35 and 0.85. It is concluded that combining networks can be adopted as an important component in the application of artificial NN techniques in applied air quality studies.     

Adverse Effects on Alfeios River Basin and an Integrated Management Framework Based on Sustainability

The Alfeios River, the longest and highest flow-rate river in Peloponnisos, constitutes an important water resource and ecosystem in Greece. In the present study, human activities in the Alfeios River Basin are described, and their impacts on water quality and the ecosystem are analyzed; effects resulting from interventions on river geomorphology between Flokas Dam and the river delta are determined. These actions have caused significant adverse impacts on the infrastructure (the dam, railroad, and road bridges), the level of aquifer water table and area water uses, and the aquatic and riparian ecosystem. A general integrated management strategy is formulated and a master management plan is proposed for resolving management problems in river basins. The plan considers local conditions and national requirements and complies with the European Communities legislation; it would help prevent further basin deterioration, improve water quality, and protect water resources and ecosystems in the area in accordance to sustainable development. The Alfeios River Basin serves as a case study in the development of the plan.Published online Note: This version was published online in June 2005 with the cover date of August 2004.     

Determining Visitors’ Dispositions Toward the Designation of a Greek National Park

This article presents the findings of the first major visitor survey conducted at the Central Rhodope Mountain Complex, situated in northern Greece. The study area is one of a number of sites planned to become National Parks under a recent initiative of the Greek government. We used a logistic regression method to define significant predictors of visitors’ awareness and attitude toward park designation, as well as their willingness to pay a conditional entrance fee. Study findings demonstrated that the probability of being aware of the park designation initiative is higher for visitors who obtained information from travel agencies or media to make their destination choice, compared to visitors who resorted to word-of-mouth recommendations. Knowledge and attitudes toward animals living in the study area revealed a limited influence on visitors’ dispositions toward park designation. The results of this study call for action to implement education programs for National Park users. These programs should aim at rendering the environmental characteristics of the Central Rhodope Mountain Complex to be significant predictors of visitors’ dispositions toward the study area. This would favor its uniqueness as a destination, as well as contribute to its long-term economic sustainability.