Uptake studies of environmentally hazardous (51)Cr in Mung beans

Attempt has been made to study the accumulation behaviour of a common plant, Mung bean (Vigna radiata) towards Cr(III) and Cr(VI) to have an insight on the migration and bio-magnification of Cr. For this purpose healthy germinated Mung bean seeds were sown in the sand in the presence of Hoagland's nutrient solution containing measured amount of K(2)(51)Cr(2)O(7) and (51)Cr(NO(3))(3).9H(2)O. Growth rate was also studied in the presence and absence of phosphate salts in the medium. It has been found that the transfer of chromium from soil to plant is significantly low (maximum 5% for both Cr(III) and Cr(VI)). Maximum accumulation of Cr occurs in the root with respect to the total chromium accumulation by the plant. Other parts of the Mung bean plant, e.g. cotyledons, shoot and leaves, show negligible accumulation. Therefore, the chance of direct intake of Cr through food as well as through the grazing animals to human body is less.     

Correction to: Water‑induced erosion potentiality and vulnerability assessment in Kangsabati river basin,eastern India

Environment, Development and Sustainability -     

Photo-catalytic decolourisation of toxic dye with N-doped titania: A case study with Acid Blue 25

Dyes are one of the hazardous water pollutants.Toxic Acid Blue 25,an anthraquinonic dye,has been decolourised by photo-catalysing it with nitrogen doped titania in aqueous medium.The photo catalyst was prepared from 15% TiCl 3 and 25% aqueous NH 3 solution as precursor.XRD and TEM revealed the formation of well crystalline anatase phase having particle size in the nano-range.BET surface area of the sample was higher than that of pure anatase TiO 2.DRS showed higher absorption of radiation in visible range compared to pure anatase TiO 2.XPS revealed the presence of nitrogen in N-Ti-O environment.The experimental parameters,namely,photocatalyst dose,initial dye concentration as well as solution pH influence the decolourisation process.At pH 3.0,the N-TiO 2 could decolourise almost 100% Acid Blue 25 within one hour.The influence of N-TiO 2 dose,initial concentration of Acid Blue 25 and solution pH on adsorption-desorption equilibrium is also studied.The adsorption process follows Lagergren first order kinetics while the modified Langmuir-Hinselwood model is suitably fitted for photocatalytic decolourisation of Acid Blue 25.     

An IoT-based waste management system monitored by cloud

Clever solid waste bin is important to create a well-organized and dynamic waste management system. This paper presents the novel way of carrying out an integrated sensing system which automates the solid waste management process. The proposed smart waste bin is based on ultrasonic-level sensor and various gas sensors which automatically sense the hazardous gases and the maximum limit of waste. The approach is unique and uses cloud and mobile app-based monitoring. Two important features of work are it not only checks the maximum waste level of the bin but also checks various stinky gases. The other part of the work is conveying the information to the responsible authority. This unique approach takes the assistance of cloud sever because of its advantages in field of usability, accessibility and disaster recovery. The information can be linked with municipality web server for immediate action. The waste bins are tracked by a unique number which represents its location. The eccentric technique gives all information related to physical condition of a particular bin and can easily reach the corresponding authority. The whole information is interconnected with a cloud-based web-information system at the host server.     

GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.

     

Water-induced erosion potentiality and vulnerability assessment in Kangsabati river basin,eastern India

Environment, Development and Sustainability - The large-scale water-induced erosion is one of the most determining elements on land degradation in subtropical monsoon-dominated region. From this...