Water crisis is one of the most serious problems faced by the world today. Phytoremediation is one of the serious efforts towards sustainability. Macrophyte-based wastewater treatment systems have several potential advantages compared with conventional treatment systems. Duckweeds (Lemna spp., Spirodela spp., Wolffia spp.) are small, green freshwater, free-floating aquatic plants. The primary objective of this work was to analyze the role of duckweeds in organic waste and nutrient removal from domestic wastewater being generated from hostels of Birla Institute of Technology, Mesra, Ranchi (India). Interesting results were obtained in which the BOD value reduced by 94.45% and the level of orthophosphate at the end of the work was found to be reduced by 79.39%. The duckweeds flourished well during the experimental period in the pH range of 7 to 8; it can be said that, other factors remaining favorable, the optimum pH for duckweed growth ranges from 7 to 8. Therefore, it can be concluded that this treatment can be successfully carried out on a large scale. Also, it is a low-cost solution to wastewater treatment problems and could satisfy the discharge standards.
Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.
Groundwater is one of the main sources of drinking water in Ranchi district and hence its vulnerability assessment to delineate areas that are more susceptible to contamination is very important. In the present study, GISbased fuzzy pattern recognition model was demonstrated for groundwater vulnerability to pollution assessment. The model considers the seven hydrogeological factors [depth to water table (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C)] that affect and control the groundwater contamination. The model was applied for groundwater vulnerability assessment in Ranchi district, Jharkhand, India and validated by the observed nitrate concentrations in groundwater in the study area. The performance of the developed model is compared to the standard DRASTIC model. It was observed that GIS-based fuzzy pattern recognition model have better performance than the standard DRASTIC model. Aquifer vulnerability maps produced in the present study can be used for environmental planning and predictive groundwater management. Further, a sensitivity analysis has been performed to evaluate the influence of single parameters on aquifer vulnerability index.
Phytoremediation is an emerging technology that uses green plants (living machines) for removal of contaminants of concern (COC). These plant species have the potential to remove the COC, thereby restoring the original condition of soil or water environment. The present study focuses on assessing the heavy metals (COC) present in the contaminated water bodies of Ranchi city, Jharkhand, India. Phytoremedial potential of three plant species: Typha latifolia, Eichornia crassipes and Monochoria hastata were assessed in the present study. Heterogenous accumulation of metals was found in the three plant species. It was observed that the ratio of heavy metal concentration was different in different parts, i.e., shoots and roots. Positive results were also obtained for translocation factor of all species with minimum of 0.10 and maximum of 1. It was found experimentally that M. hastata has the maximum BFC for root as 4.32 and shoot as 2.70 (for Manganese). For T. latifolia, BCF of maximum was observed for root (163.5) and respective shoot 86.46 (for Iron), followed by 7.3 and 5.8 for root and shoot (for Manganese) respectively. E. crassipes was found to possess a maximum BCF of 278.6 (for Manganese and 151 (for Iron) and shoot as 142 (for Manganese) and 36.13 (for Iron).
Fluoride in groundwater is known to contaminate the water sources globally. Jharkhand, one of the states in the eastern part of India, is known to have excessive fluoride content in groundwater sources. The present work involves assessment of water quality with special reference to fluoride in Majhiaon block of Garwa district in Jharkhand. Iron, nitrate and arsenic were also tested for the water samples collected from site. Eight hundred forty samples were tested for fluoride on site using colourimetry method, and one tenth of the samples were brought to laboratory for iron, nitrate, arsenic and fluoride analysis. Results show that 402 samples were having fluoride above permissible limit. Iron and nitrate were found to be beyond permissible limits in 302 and 286 water samples, respectively. More than 50% of samples collected from school had fluoride levels above permissible limits. Arsenic was well within the limits. However, few samples shown were excessive of iron and nitrate.
Groundwater pollution due to anthropogenic activities is one of the major environmental problems in urban and industrial areas. The present study demonstrates the integrated approach with GIS and DRASTIC model to derive a groundwater vulnerability to pollution map. The model considers the seven hydrogeological factors [Depth to water table (D), net recharge (R), aquifer media (A), soil media (S), topography or slope (T), impact of vadose zone (I) and hydraulic Conductivity(C)] for generating the groundwater vulnerability to pollution map. The model was applied for assessing the groundwater vulnerability to pollution in Ranchi district, Jharkhand, India. The model was validated by comparing the model output (vulnerability indices) with the observed nitrate concentrations in groundwater in the study area. The reason behind the selection of nitrate is that the major sources of nitrate in groundwater are anthropogenic in nature. Groundwater samples were collected from 30 wells/tube wells distributed in the study area. The samples were analyzed in the laboratory for measuring the nitrate concentrations in groundwater. A sensitivity analysis of the integrated model was performed to evaluate the influence of single parameters on groundwater vulnerability index. New weights were computed for each input parameters to understand the influence of individual hydrogeological factors in vulnerability indices in the study area. Aquifer vulnerability maps generated in this study can be used for environmental planning and groundwater management.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.