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.     

Annoyance due to aircraft noise has increased over the years—Results of the HYENA study

In the HYENA study (HYpertension and Exposure to Noise near Airports) noise annoyances due to aircraft and road traffic noise were assessed in subjects that lived in the vicinity of 6 major European airports using the 11-point ICBEN scale (International Commission on Biological Effects of Noise). A distinction was made between the annoyance during the day and during the night. L_den and L_night were considered as indicators of noise exposure. Pooled data analyses showed clear exposure–response relationships between the noise level and the noise annoyance for both exposures. The exposure–response curves for road noise were congruent with the EU standard curves used for predicting the number of highly noise annoyed subjects in European communities. Annoyance ratings due to aircraft noise, however, were higher than predicted by the EU standard curves. The data supports other findings suggesting that the people's attitude towards aircraft noise has changed over the years, and that the EU standard curve for aircraft noise should be modified.     

Leaching of the organophosphorus nematicide fosthiazate

Fosthiazate is an organophosphorus nematicide which was recently included in Annex I of the Directive 91/414/EEC under the clause that it should be used with special care in soils vulnerable to leaching. Thus, the leaching of fosthiazate was investigated in columns packed with three different soils which represented situations of high (site 2), intermediate (site 1) and low (site 3) leaching potential. The recommended dose of fosthiazate was applied at the surface of the soil columns and fosthiazate fate and transport was investigated for the next two months. Fosthiazate concentrations in the leachate collected from the bottom of the columns packed with soil from site 2 exceeded 0.1 microgl(-1) in most cases. This soil was characterized as acidic, indicating longer fosthiazate persistence, with low organic matter content, indicating weak adsorption, thus representing a situation vulnerable to leaching. In contrast, the lowest concentrations of fosthiazate in the leachate were evident in the columns packed with soil from site 3. This soil was characterized as alkaline, indicating faster degradation, with higher organic matter content, indicating stronger adsorption, thus representing a situation not favoring leaching of fosthiazate. The highest concentration of fosthiazate in the leachate from the columns packed with soil from site 2 was 3.44 microgl(-1) compared to 1.17 and 0.16 microgl(-1), which were the corresponding maximum values measured in columns packed with soil from sites 1 and 3, respectively. The results of the current study further suggest that fosthiazate is mobile in soil and can leach under conducive soil conditions like acidic soils with low organic matter content.     

Statistical Modelling of CO and NO2 Concentrations in the Athens Area - Evaluation of Emission Abatement Policies (7 pp)

- DOI: http://dx.doi.org/10.1065/espr2006.04.299 Goal, Scope and Background This paper describes a statistical modelling approach, suggested as a policy tool in the Athens area for the assessment of the emissions reduction level required to meet the air quality standards for two criteria air pollutants, namely CO and NO2. Methods. More than ten years of hourly CO and NOx-NO2 concentration data measured by the monitoring network of the Hellenic Ministry for the Environment, Physical Planning and Public Works were analyzed and the original dataset has been reduced using a data evaluation procedure. Results and Discussion Seasonal pollutant concentration trends suggested that the reduction of CO and NOx concentrations observed in the beginning of the '90s is almost entirely attributed to the increase of the catalyst-equipped cars during this period. The numerical parameters of an empirical model relating EU standard exceedances with mean annual concentrations were defined and the model was validated using datasets from years that were not used for the estimation of these parameters. This model was used in conjunction with a roll-back equation as a policy tool for the assessment of the effect of different CO and NOx emissions reduction scenarios on air quality standard compliance for CO and NO2. Results predicted with this empirical modelling approach were assessed with monitored data averaged over a 3-year period, giving satisfactory results. Conclusion A methodology suggested for assessing the effects of different emissions reduction scenarios on air quality standard attainment was successfully applied for CO and NO2 in the Athens area. Recommendation and Perspective The proposed methodology can provide a useful tool for the evaluation of policies already in progress as well as the development of future policies for emissions reduction in urban areas with similar characteristics, aiming at air quality standard compliance on a timely manner. Such a methodology could be applied in other urban areas of Greece characterized by dense traffic, therefore assisting the development of national policies in relation to air pollutants for which standard exceedances occur.     

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.     

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.     

Quality of tube well water intended for irrigation and human consumption with special emphasis on arsenic contamination at the area of Punjab,Pakistan

In the present study, the tube well water quality and the associated health risks, emphasizing on arsenic contamination, were investigated in rural and urban samples from Tehsil Mailsi located in Punjab, Pakistan. Arsenic concentrations (μg/L) were ranged from 12 to 448.5 and which exceeded the WHO recommended limit (10 μg/L) in all cases. The calculated average daily dose (3.3 × 10^?0.4 to 1.2 × 10^?0.2 mg/kg day) and hazard quotient (1.1–40) reflected the potential health risk to local population due to tube well water consumption as drinking purpose. Sodium percent (Na%), sodium absorption ratio, residual sodium carbonate, Kelly’s index and magnesium absorption ratio were also determined to assess the suitability of tube well water for irrigation purpose. The resulting piper plot revealed the Na–Ca–HCO₃ type water chemistry of the area and generally alkaline environment. The spatial distribution of arsenic in the tube well waters pinpoints the significant contribution of anthropogenic activities to arsenic pollution. Nevertheless, different statistical tools, including principal component analysis, hierarchical cluster analysis and correlation matrices, revealed the contribution of both natural and anthropogenic activities and alkaline type of aquifers toward the high level of arsenic contamination.