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    Land-use land-cover changes in east singbhum mineralized zone: A case study
    (2011) Kashinath, P.; Deb, D.; Vardhan, H.; Mangalpady, M.; Samanta, B.
    Remote sensing images and techniques are widely used for environmental monitoring, climate changes, forest management and for water resource management. In the present work, identification of land-use land-cover (LULC) changes was studied based on Landsat Satellite (MSS) and IRS Satellite (LISS-III) images by Maximum Likelihood Classification (MLC) method. The study finds that the areas of water bodies and dense forest have decreased by more than 11 % and 6 %, respectively, while area covered by vegetation and habitats have increased by 16 % and 5 %, respectively. It was also found that dense forest was increased by 30 % around Norwapahar mine site area.
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    Identification and Apportionment of Pollution Sources to Groundwater Quality
    (Springer Basel info@birkhauser-science.com, 2016) Gulgundi, M.S.; Shetty, A.
    Characterizing groundwater quality and apportionment of pollution sources to groundwater pollution is important for managing water resources effectively. Owing to rapid industrialization and population growth in Bengaluru city, the groundwater quality is getting deteriorated. Receptor modeling by Multi-Linear Regression of the Absolute Principal Component Scores (APCS-MLR) has been used to evaluate the source apportionment of groundwater pollution in order to recognize and quantify the pollution sources. Groundwater quality data measured for pre-monsoon and post-monsoon in the year 2014, comprising 14 physico-chemical parameters from 68 sites distributed across the study area, have been used. Principal component analysis identified four factors explaining 79.2 % of the total variance. Receptor modeling using APCS-MLR provided apportionment of different sources responsible for the groundwater quality along with percentage contribution of the recognized sources to each parameter. Results revealed that most of the variables were primarily affected by rock water interactions, seepage of sewage and industrial effluent. It was also found that few parameters gained significant contribution from the unidentified sources. Finally, the model performance was evaluated based on the ratio of estimated mean to measured mean (E/M). It was found that except for Fe with (E/M) ratio as high as 7.1, the model showed moderate strength with (E/M) values ranging from 0.51 to 2.83 of all the other parameters. © 2016, Springer International Publishing Switzerland.
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    Isolation and identification of Pseudomonas from wastewater, its immobilization in cellulose biopolymer and performance in degrading Triclosan
    (Academic Press, 2019) Devatha, C.P.; Narasimhappa, N.
    Triclosan (TCS) is a well-known emerging contaminant got wide use in daily use products of domestic purpose, which provides the way to enter the ecological cycle, and is preferably detected in sewage treatment plants. In this study, TCS degrading bacteria (TDB) was isolated and identified from a wastewater treatment plant at the National Institute of Technology-Karnataka, Surathkal (NITK), India. The isolate was reported as Pseudomonas strain by performing 16S RNA Sequencing using BLAST analysis. Bacterial growth depends upon several environmental factors. Hence its growth optimization was carried out by response surface method (RSM) based central composite design (CCD) and validated by the artificial neural network (ANN). The Parameters or inputs used for optimization are pH, time (days), agitation (rpm) and sorbent dosage (?g/L). Experiments were conducted in batch mode to achieve optimum growth of bacteria based on RSM trial runs. The RSM model predictions were in better agreement with the experimental results and it was confirmed by ANN. The deviation lies within ±10% with experimental results compared to ANN for maximum trials. Hence optimized parameters were established and arrived at pH - 7, time - 13 days, agitation - 150 rpm, dosage - 1.5 ?g/L presented 69% removal of TCS. Minimum inhibitory assay of isolated strain was conducted to identify the degradation capacity of TCS and it was found out to be lesser than 0.025 mg of TCS. Later the strain was immobilized in two different matrices. One is biopolymer extracted from cellulose (Water Hyacinth) along with sodium alginate and second is free bacteria with sodium alginate and was made in the form of beads. The removal of TCS by TDB-cellulose-alginate (BCA) and TDB-Alginate (BA) beads were 58% and 30% respectively. Hence it was concluded that BCA beads showed effective removal compared to BA beads. Therefore, isolate can degrade TCS when the concentration ranges from 0.025 mg/L to 5.5 ng/L. © 2018 Elsevier Ltd