A Study on Transfer Factors of 60Co and 65Zn from Soil to Plants in the Tropical Environment of Bangladesh

Soil to plant transfer factor (TF) of⁶⁰Co and ⁶⁵Zn was determined fromradioisotope experiments on plants grown in pots underoutdoor ambient tropical conditions for three growingseasons (1995–1998). The TFs were obtained fordifferent plants/crops such as, rice, bean, peanutspineapple, cabbage, tomato, spinach and grass. Theaverage TF values of ⁶⁰Co are found to be 0.087,0.15, 0.12, 0.67, 0.28, 0.79, 1.03 and 0.34respectively for the above mentioned plants/crops. Incase of ⁶⁵Zn, the average TF values are found tobe 2.24, 1.17, 0.89, 1.09, 0.78, 1.34, 2.92 and 1.78,respectively, for the above mentioned plants/crops. Thedata will be useful to assess the radiation exposureto man associated with the releases of radionuclidesfrom nuclear facilities by means of radiologicalassessment models that require transfer factors asinput parameters to predict the contamination ofradionuclides in foodchain.     

Acute ecotoxicity and genotoxicity assessment of two wastewater treatment units

Environmental Science and Pollution Research - Water contamination by discharge of untreated or poorly treated wastewater into water bodies is a current issue that may cause harm to humans. Water...     

Larvicidal and pupicidal activities of eco-friendly phenolic lipid products from Anacardium occidentale nutshell against arbovirus vectors

Environmental Science and Pollution Research - Aedes aegypti and Culex quinquefasciatus are vectors of diseases that constitute public health problems. The discovery of products capable of...     

Sediment integrative assessment of the Bay of Cádiz (Spain): An ecotoxicological and chemical approach

This study consisted of the sediment toxicity assessment of the Bay of Cádiz based on two endpoints: growth inhibition for Cylindrotheca closterium (benthic microalgae) and fecundity inhibition for Tisbe battagliai (harpacticoid copepod). A new methodology to eliminate (but not as storage technique) the autochthonous biota present in the sediment samples by immersing them in liquid nitrogen (? 196 °C) was also assessed. Sediment toxicity data showed different toxicity levels for both organisms. In general, T. battagliai was more sensitive; however a good correlation (r = 0.75; p  < 0.05) between sediment toxicity results for both species was found. Data in pore water (pH, redox potential, and toxicity for microalgae and copepod) and sediment (pH, redox potential, organic carbon, and metal concentrations) demonstrated that ultra-freezing did not alter sample characteristics; thus, this technique can be adopted as a pre-treatment in whole-sediment toxicity tests in order to avoid misleading results due to presence of autochthonous biota. Multivariate statistical analysis such as cluster and principal component analysis using chemical and ecotoxicological data were employed. Silt and organic matter percentage and lead concentration were found to be the factors that explain about 77% of sediment toxicity in the Bay of Cádiz. Assay methodology determined in this study for both assayed species is considered adequate to be used in sediment toxicity monitoring programs. Results obtained using both species show that the Bay of Cádiz can be considered a moderately polluted zone.     

Effect of pre-treatment and supporting media on Ni(II), Cu(II), Al(III) and Fe(III) sorption by plant root material

In this work Paspalum notatum root material was used to elucidate the influence of acid leaching pre-treatment and of sorption medium on metal adsorption. Ground P. notatum root was leached with 0.14M HNO(3). Leached root material (LRM) and non-leached root material (NLRM) were employed to flow sorption of Ni(II), Cu(II), Al(III) and Fe(III) in 0.5M CH(3)COONH(4) medium at pH 6.5. For LRM the sorption was also studied in 0.5M KNO(3) medium. The acid pre-treatment increased the sorption capacity (SC) for all ions studied. For the KNO(3) medium, Cu(II) and Fe(III) sorption was higher than in CH(3)COONH(4) and the type of the Ni(II) isotherm's model changed. The Freundlich model was the most representative isotherm model to describe metallic ions sorption. The (1)H NMR spectra showed differences between LRM and NLRM and the acid-basic potentiometric titration elucidated that acid-leaching procedure affected the root material sorption sites once only two predominant sorption sites were found for LRM (phenolic and amine, both able cations sorption) and five sorption sites (two carboxylic, amine and two phenolic) were founded for NLRM.     

Discriminating the pH toxicity to Poecilia reticulata Peters, 1859 in the Dunas Lake (Camaçari, BA, Brazil)

Toxic potential of the pH reduction to fingerlings of Poecilia reticulata, through acute toxicity bioassays, as well as the influence of increased pH on the toxicity were assessed. Acid lake samples (Dunas Lake) were collected during 19 months, and assessed with following treatments: water at local pH (+/-3.0) and samples with modified pH to 3.5, 3.8, 4.0, 4.3, 4.6, 5.0, 5.5, 6.0, and 6.5. Culture water samples with pH reduced to 3.0 were also assessed. Newborn P. reticulata were exposed during 96h, and dead/immobile organisms were counted at various time intervals during exposure (short intervals in the beginning and long towards the end). Mean results of LT(50) and confidence intervals from the Dunas Lake and control water with reduced pH were 1.36 (+/-0.48)h, and 1.03 (+/-0.50)h, respectively, with no statistical difference. Samples with increased pH showed a significant reduction in toxicity, with no toxicity detected at pH 6.0 and higher. Relationship between pH and lethal toxicity for fingerlings of P. reticulata demonstrated that pH exerted a strong effect on the survival of this species at the Dunas Lake, explaining about 80% of the toxicity observed.     

Feature extraction using Hough transform for solid waste bin level detection and classification

This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image’s gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.