A passively immobilized novel biomagsorbent for the effective biosorptive treatment of dye contamination

A new magnetic bio-based composite was designed by the magnetic modification of passively immobilized fungal cells. It was utilized for biosorptive decolorization of reactive dye-contaminated aquatic media. As a greener option, waste tea leaf tissues were used for the first time as an immobilization matrix for microbial cells. Immobilized magnetic cells (biomagsorbent) could be effectively used in both batch and dynamic flow mode treatment processes and real environmental application. Rapid equilibrium and high decolorization yields were observed for the target dye (reactive violet 1). The temperature did not significantly affect the process. Langmuir and the pseudo-second-order models could be better used to fit the process equilibrium and kinetics, respectively. Maximum monolayer sorption capacity was 152.88 mg g^?1. High biosorption and desorption yields for 50 consecutive dynamic flow decolorization cycles were recorded as striking results. The breakthrough time was 3420 min. Simulated and industrial water treatment performance of biomagsorbent was found to be more than 90%. The mechanism was evaluated by IR and zeta potential analysis. The magnetic character of the sorbent provided good mechanical durability, easy separation, and excellent regeneration ability. Consequently, this work provides new insight into scalar enhancement of water treatment.

     

Cadmium exposure from the cement dust emissions: a field study in a rural residence

The cement dust is one of the causes of pollution in the environment. In the present study, the cadmium concentrations of soil and plant specimens taken from a rural area exposed to cement factory emissions were determined and also the blood concentrations and sensitivity conditions in humans residing in this rural area were investigated. The 108 soil (36 for control) and plant specimens were collected from eight different directions of the cement plant located in Cukurhisar town in Eski?ehir city. Blood samples of the individuals residing in this area were taken from 258 subjects (258 for control) following a physical examination, and patch tests were also applied. The results show that the cadmium concentrations of the soil and plant specimens taken from different places in different directions of the factory were higher than in the control areas. The physical examination of subjects did not reveal results different from those of the control group except for the diagnosis of contact dermatitis. The analysis of venous blood samples showed that cadmium concentrations were found to be within the reference values given for both groups, but higher in the subjects (p<0.001). According to the results of patch tests, sensitivity to cadmium was found to be more frequent for the subject group than the control group (p<0.05). Those results show that, although clinical tools revealed no toxic effects for the subject, except contact dermatitis, the cement plant increases cadmium pollution on the surrounding environment.     

Nickel and Cadmium Concentrations in Plasma and Na+/K+ATPase Activities in Erythrocyte Membranes of the People Exposed to Cement Dust Emissions

The aim of this study was to determine the concentrations of nickel and cadmium in blood plasma of the people exposed to cement dust emissions and to investigate the effects of exposure period on the activities of Na⁺/K⁺ ATPase enzymes in their erythrocyte membranes. The study was carried out on people living in Eskiehir Çukurhisar rural area, located near a cement factory. Blood samples of the individuals residing in this area were taken from 80subjects (30 for control) following a physical examination. The analysis of plasma samples showed that nickel concentrations in subject group were found to be significantly higher than those of the control group (p < 0.001). Cadmium concentrations were found to be within the reference values for both group and no difference was found between the subjects and controls (p > 0.05). Furthermore, no correlation was observed between the levels of Na⁺/K⁺ ATPase activity in erythrocyte membranes of the subject group and the ages of people living in the region (p > 0.05, r = 0.133). It was also observed that nickel concentrations increased by age (p < 0.001, r = 0.646) while no effect was observed in means of cadmium. Na⁺/K⁺ ATPase activities in the erythrocyte membranes were not affected.In conclusion although there was no difference between the Na⁺/K⁺ ATPase activity in means of age, there was an environmental pollution and may be it was due to the industrial plant.     

Detection and object-based classification of offshore oil slicks using ENVISAT-ASAR images

The aim of this study is to propose and test a multi-level methodology for detection of oil slicks in ENVISAT Advanced Synthetic Aperture Radar (ASAR) imagery, which can be used to support the identification of hydrocarbon seeps. We selected Andrusov Ridge in the Central Black Sea as the test study area where extensive hydrocarbon seepages were known to occur continuously. Hydrocarbon seepage from tectonic or stratigraphic origin at the sea floor causes oily gas plumes to rise up to the sea surface and form thin oil films called oil slicks. Microwave sensors like synthetic aperture radar (SAR) are very suitable for ocean remote sensing as they measure the backscattered radiation from the surface and show the roughness of the terrain. Oil slicks dampen the sea waves creating dark patches in the SAR image. The proposed and applied methodology includes three levels: visual interpretation, image filtering and object-based oil spill detection. Level I, after data preparation with visual interpretation, includes dark spots identification and subsets/scenes creation. After this process, the procedure continues with categorization of subsets/scenes into three cases based on contrast difference of dark spots to the surroundings. In level II, by image and morphological filtering, it includes preparation of subsets/scenes for segmentation. Level III includes segmentation and feature extraction which is followed by object-based classification. The object-based classification is applied with the fuzzy membership functions defined by extracted features of ASAR subsets/scenes, where the parameters of the detection algorithms are tuned specifically for each case group. As a result, oil slicks are discriminated from look-alikes with an overall classification accuracy of 83% for oil slicks and 77% for look-alikes obtained by averaging three different cases.