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.
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