Investigation of protozoa as indicators of wastewater treatment efficiency in constructed wetlands

Wetlands represent an efficient wastewater treatment technique, with several benefits over the conventional activated sludge system. Microfaunal community is of outmost importance in treatment processes as the microorganisms are able to achieve substantial decontamination through biodegradation. The objectives of this work were the monitoring of protozoan's abundance and diversity in the matrix of six bench scale Free Water Surface constructed wetlands and the investigation of their applicability as indicator organisms for treatment efficiency in these systems. A correlation between the phosphorous and Total Coliforms removal rates was observed in the presence of increased protozoan taxa, while removal of organic loading and inorganic nitrogen was increased in the case of increased protozoan diversity in the soil/water interface. Results revealed that protozoa may be used as bioindicators of treatment efficiency in constructed wetlands; in addition their presence was related to the effluent quality.     

A novel self‐organizing neuro‐fuzzy multilayered classifier for land cover classification of a VHR image

A novel self‐organizing neuro‐fuzzy multilayered classifier (SONeFMUC) is introduced in this paper, with feature selection capabilities, for the classification of an IKONOS image. The structure of the proposed network is developed in a sequential fashion using the group method of data handling (GMDH) algorithm. The node models, regarded as generic classifiers, are represented by fuzzy rule‐based systems, combined with a fusion scheme. A data splitting mechanism is incorporated to discriminate between correctly classified and ambiguous pixels. The classifier was tested on the wetland of international importance of Lake Koronia, Greece, and the surrounding agricultural area. To achieve higher classification accuracy, the image was decomposed into two zones: the wetland and the agricultural zones. Apart from the initial bands, additional input features were considered: textural features, intensity–hue–saturation (IHS) and tasseled cap transformation. To assess the quality of the suggested model, the SONeFMUC was compared with a maximum likelihood classifier (MLC). The experimental results show that the SONeFMUC exhibited superior performance to the MLC, providing less confusion of the dominant classes in both zones. In the wetland zone, an overall accuracy of 89.5% was attained.     

Influence of Initial Water Saturation on the Residual Saturation of an Organic Liquid in the Vadose Zone

The influence of initial water saturation on residual organic saturation was studied by determining pressure-saturation relationships with a pressure cell apparatus. Initial water saturations varying from 0.02 to 0.40 were investigated by allowing gasoline to imbibe into the water wet soil, displacing the mobile air. Subsequently, air was forced back into the soil in a series of incremental steps that resulted in gasoline drainage and a measurement of residual gasoline saturation. The data indicate that water saturation must be considered in order to understand retention and movement of liquid organics in the vadose zone. It is concluded that residual organic saturation decreases by the amount that initial water saturation increases, as Leverett's assumption implies, for initial water saturations less than a critical value. For initial water saturations greater than the critical values the residual oil saturation remained constant, the total liquid saturation increased and Leverett's assumption was no longer valid.     

A multistage genetic fuzzy classifier for land cover classification from satellite imagery

A linguistic boosted genetic fuzzy classifier (LiBGFC) is proposed in this paper for land cover classification from multispectral images. The LiBGFC is a three-stage process, aiming at effectively tackling the interpretability versus accuracy tradeoff problem. The first stage iteratively generates fuzzy rules, as directed by a boosting algorithm that localizes new rules in uncovered subspaces of the feature space, implicitly preserving the cooperation with previously derived ones. Each rule is able to select the required features, further improving the interpretability of the obtained model. Special provision is taken in the formulation of the fitness function to avoid the creation of redundant rules. A simplification stage follows the first one aiming at further improving the interpretability of the initial rule base, providing a more compact and interpretable solution. Finally, a genetic tuning stage fine tunes the fuzzy sets database improving the classification performance of the obtained model. The LiBGFC is tested using an IKONOS multispectral VHR image, in a lake-wetland ecosystem of international importance. The results indicate the effectiveness of the proposed system in handling multidimensional feature spaces, producing easily understandable fuzzy models.     

Development and evaluation of an alternative method for municipal wastewater treatment using homogeneous photocatalysis and constructed wetlands

In the preparation of Au/TiO₂ (P-25) catalysts by the method commonly but inaccurately known as deposition–precipitation (DP), the uptake of anionic complexes in solution onto the support is maximal close to the pH of the isoelectric point (6); below this pH, complexes are adsorbed electrostatically, but at higher pH values, especially at pH 8–9, the neutral Au(OH)₃·H₂O is reversibly adsorbed on the negatively charged surface. The specific activity (per gram of gold) peaks however at pH 8–9, because here the adsorbed complex is largely chlorine-free. The reversibility of the adsorption equilibrium is proved by alteration of the pH during the course of a single preparation through analysis of samples removed at intermediate points. This observation enables poorly dispersed precursors or sintered gold particles to be re-dispersed, and high activity restored.     

Differences of water retention curves obtained through capillary rise and steady-state equilibrium experiments

Capillary rise experiments were performed under constant temperature in columns of Metea sandy loam soil packed at different bulk densities. Moisture retention curves were obtained following the capillary rise activity. All curves exhibited a theta-straight region, followed by a parabolic region flattened at higher suctions. The parabolic region, when plotted on log-log scales, could be separated into three distinct zones in all none soil retention curves. These three zones suggest sharp transitions in the water content-matric potential relationship rather than the expected gradual change in a continuum. A power function was used to fit each of the three zones of wetting retention data. Comparison of retention curves obtained through capillary rise and steady-state equilibrium standard methods showed significant differences at high suction values. These retention curve differences were attributed to the reduction of the matric field for liquid phase wetting of capillary rise. Conductivity and diffusivity functions suitable for predicting upward water movement with infiltration models were determined from experimental retention data by applying the zonal constitutive relationships.