Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.     

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

ABSTRACT

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O₃ and NO₂ from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.     

Soil Erosion Potential after Fire and Rehabilitation Treatments in Greece

Wildland fires are one of the more severe disturbances for natural ecosystems in the Mediterranean basin and can become a critical factor in the process of soil erosion. A quantitative assessment of soil erosion is needed in order to form an assessment on the extent and magnitude of post-fire soil erosion potential and to assess the effectiveness of the rehabilitation treatment. On 21 August 2006, a large wildland fire occurred in the Kassandra Peninsula in northern Greece, which burned one fifth of the Peninsula. After the fire, in order to protect the soil against erosion, the Forest Services applied a hillslope rehabilitation treatment of contour-felled logs and branch piles. In this paper, we report quantitative estimation of the wildland fire and erosion control treatment on soil erosion potential. The coupling of the Universal Soil Loss Equation and the Geographical Information Systems was implemented and the erosion potential was found to be 2.8 t/ha/year pre-fire, 29.5 t/ha/year post-fire, and 21.3 t/ha/year after rehabilitation treatment. The model can successfully contribute in the planning of the rehabilitation treatment but it cannot be used in the quantification of the soil loss after the application of the erosion control measures. The comparisons between the results of the three cases indicate the importance of the immediate erosion control measures in order to mitigate soil loss and restore the natural environment.     

Environmental Information, Asymmetric Information, and Financial Markets: A Game-Theoretic Approach

This paper examines the problem of asymmetric information in financial markets due to a lack of essential environmental information. The literature indicates that asymmetric information generates various problems for the actors of financial markets such as incomplete information for investment decisions and lending procedures, misallocation of financial market funds, the underestimating of stock price securities, and poor environmental risk management choices. To this end, this paper develops a game-theoretic approach to examine both the persistent nature of asymmetric information caused by the absence of accurate environmental information and to indicate how a well-organized, trustworthy, internationally agreed auditing accounting certification scheme could play a critical role in limiting the magnitude of this problem.     

A screening procedure for selecting the most suitable dredged material placement site at the sea. The case of the South Euboean Gulf, Greece

The selection of the best site for the placement of dredged sedimentary material (～7,000 m³) from the Aliveri coastal area in the adjacent South Euboean Gulf (Greece) was accomplished through a screening procedure. The initial stage comprised the determination of physical, chemical, and biological characteristics of the dredged sediment before the commencement of any dredging operation. Grain size measurements, geochemical analyses together with the use of pollution/toxicity indices and empirical sediment quality guidelines, and the conduct of an acute toxicity test showed that the dredged material consisted of “unpolluted to slightly polluted” silty sands and sandy silts. However, the local authorities planned to place this sediment in the neighboring open sea area, i.e., the South Euboean Gulf, due to the absence of any beneficial use or alternative dumping option (i.e., dumping on public lands). Therefore, the next stage of the screening procedure, based on criteria such as the national legislation, seabed and seawater column characteristics, influence of the water mass circulation pattern on the post-placement migration of dredged sediment, impact on living resources and human activities (i.e., aquaculture and fishing), effect on significant marine sites (i.e., sites of scientific, ecological, and historical importance, navigation routes, military zones), and seafloor engineering uses, led to the evaluation of the suitability of the South Euboean Gulf as a potential dumping area. Then, the identification of the appropriate dredged material placement sites in the South Euboean Gulf was based on a cluster analysis, which tested the physicochemical resemblance of the dredged material and the surface sediments of 19 potential placement locations in the gulf. After the statistical process, only four sites situated near the north shoreline of the South Euboean Gulf were qualified as the best dredged material placement locations.     

A multi-criteria approach for the dumping of dredged material in the Thermaikos Gulf,Northern Greece

A multi-criteria approach was applied for the disposal into the sea of ～1 100 000 m³ of sediment, dredged from a coastal area in the northeastern part of the Thermaikos Gulf. This sediment (classified as muddy) is distributed vertically into two distinct Layers (A and B) with the thickness of the surficial sedimentary unit ranging from 7 to 54 cm. Its geochemistry reveals increased Cr and Ni concentrations, which may be attributed to natural enrichment through the erosion of the adjacent igneous and metamorphic rocks. In addition, a low to moderate contamination from urban-originated heavy metals, like Cu, Pb and Zn as well as from aliphatic and polycyclic hydrocarbons was identified for the upper Layer A. However, the limited proportion (5.5%) of the polluted Layer A in the total volume of the dredged material could not affect the good quality (assessed by the Sediment Quality Guidelines) of the bulk sediment. The identification of the optimum marine dumping site was based on (a) the physicochemical similarity (detected by the application of a cluster analysis) of the dredged material with the surficial deposits of potential dumping sites in the Outer Thermaikos Gulf, and (b) the consideration, based on previous studies, of various criteria related to the disposal area such as deep-water circulation, influence on living resources, impact on economical (aquaculture, fishing, navigation), recreational (fishing) and military activities.     

Improving statistical distinctness in assessing trophic levels: the development of simulated normal distributions

The statistical distinctness in assessing differences of the trophic status between sampling sites was investigated in the present study. Nutrient (phosphate, nitrate, nitrite, ammonia) and phytoplankton (chlorophyll, cell number) variables from nine sampling stations were used for the validation of the statistical procedures. Raw data, transformed data, and simulated data derived on normalized nutrient–phytoplankton frequency distribution were tested. The Kruskal–Wallis (KW) nonparametric statistical procedure was also applied on the raw data as well as the analysis of variance on transformed and simulated data. In all cases, pairwise comparisons for each parameter between stations were performed. The results showed that maximum distinctness between sampling sites for all the six variables was attained using the simulated data. The KW method showed the poorest discrimination between stations. The methodology of producing and using simulated data is described step by step, and the advantages in cases of unequal sampling design or small sample size are discussed.