All

Adsorption and removal of commercial dyes were studied in aqueous suspensions of fly ash mixtures
with a sandy clay loam soil of low organic matter content. The commercial dyes, acid orange 7, acid yellow
23, disperse blue 79, basic yellow 28 and direct yellow 28 represent the widely used nitroazo structures.
Batch and column experiments were carried out at equilibrium conditions for concentrations of
dyes between 5 and 60 mg l-1. The logarithmic form of Freundlich equation gave a high linearity and
the k constants are increasing with the increase of fly ash content in adsorbent mixtures and the affinity
between the adsorbent surface and adsorbed solute. The mean removed amounts of dyes by adsorption
batch experiments in soil mixture with 20% fly ash content were up to 53.0% for acid yellow 7,
44.9% for acid yellow 23, 99.2% for direct yellow 28, 96.8% for basic yellow 28 and 88.5% for disperse
blue 79. The removal of dyes from column experiments decrease with the increase of the solution concentration
form 10 to 50 mg l-1 at 20 °C, showing the process to be highly dependent on the concentration
of the solution. The mean removed amounts of dyes by adsorption on columns of soil mixture
with 20% fly ash content and for initial concentration of dye solutions 50 mg l-1 were up to 33.8% for
acid yellow 7, 59.4% for acid yellow 23, 84.2% for direct yellow 28, 98.2% for basic yellow 28 and 60.3%
for disperse blue 79.

The paper presents some interesting results of metal speciation studies employing Anodic Stripping
Voltammetry (ASV) applied in a dynamic natural system such as the brakish – marine interface formed
between the polluted waters discharged by the Koumoundouros lake and the marine ones of the Gulf
of Elefsis.
The distributions and behaviour of various forms of Pb, Cd and Zn have been followed seasonally. Four
categories of dissolved species were identified (very labile, moderately labile, slowly labile and inert),
as well as particulate species. It was found that their relative contribution and patterns are determined
by three main factors: salinity, pH, and the presence of dissolved organic carbon. Increasing salinity
stimulates formation of very labile chloro-complexes, while increasing pH stimulates the formation of
inert species and particulates. A considerable part of slowly labile species seems to be metal complexes
with organic ligands.

This work illustrates the use and some related results of Artificial Neural Networks (ANNs) for data
quality control of environmental time series and for reconstruction of missing data. ANNs are applied
to the following problems: i) short and medium-term predicting of air pollutant concentrations in urban
areas, ii) interpolating and extrapolating daily maximum temperature, iii) replacing time distribution
with spatial distributed information (pollutant concentrations at different measuring sites). Observed
versus predicted data are compared to test the efficacy of ANNs in simulating environmental processes.
Results confirm ANNs as an improvement of classical models and show the utility of ANNs for
restoration of time series..

The present work argues that sustainable tourism is essential to the long-term survival of the tourism
industry in Europe. Sustainable tourism may be regarded as a means of redressing economic imbalances
between European regions and nations without producing adverse environmental, social and cultural
effects on host communities. Conflicts between the development of a local economy and the interests
of ‘outside’ investors from elsewhere among EU member nations must be resolved in the best
interests of the local people and the environment. The degree to which profits are expropriated from a
local area or region is a particular concern. The transnational character of tourism businesses makes
necessary a European-wide policy, where the quality of life and nature’s conservation will obtain a premortial
place.