Synthesis and characterization of magnetic bio-adsorbent developed from Aegle marmelos leaves for removal of As(V) from aqueous solutions.

A novel magnetic bio-adsorbent was prepared from the leaves of Aegle marmelos tree (Indian bael) and Fe2O3 nanoparticles. The AMP@Fe2O3 nanocomposite (Aegle marmelos leaf powder) was synthesized by pyrolysis process and applied for As(V) removal through batch adsorption process. The synthesized AMP@Fe2O3 nanocomposite was analyzed by several instrumental techniques like XRD, FESEM, TEM, HRTEM, FTIR, BET, and VSM studies. Maximum amount of As(V) was removed at pH 3, contact time of 250 min, adsorbent dose of 0.1 g/L, and initial concentration of 0.5 mg/L at room temperature. The model study revealed that the pseudo-second-order kinetics and Langmuir isotherm models were best fitted with the experimental data. The nanocomposite showed a maximum adsorption capacity of 69.65 mg/g. The endothermic nature of the adsorption process was ascertained from the thermodynamics studies. The zeta potential and FTIR analysis before and after adsorption demonstrated two types of adsorption mechanism. The first one was the electrostatic attraction between negatively charged As(V) ions (H2AsO4-) and protonated -OH group present on the Fe2O3 surface and the second one was ligand exchange between the surface hydroxyl groups and As(V) ions. The AMP@Fe2O3 nanocomposite was desorbed with 0.5 M NaOH solutions and also used up to four cycles without any major decrease in removal efficiency. Thus, AMP@Fe2O3 nanocomposite can be applied as a potential adsorbent for As(V) removal from wastewater.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

Analysis of occupational health hazards and associated risks in fuzzy environment: a case research in an Indian underground coal mine.

This paper presents a unique hierarchical structure on various occupational health hazards including physical, chemical, biological, ergonomic and psychosocial hazards, and associated adverse consequences in relation to an underground coal mine. The study proposes a systematic health hazard risk assessment methodology for estimating extent of hazard risk using three important measuring parameters: consequence of exposure, period of exposure and probability of exposure. An improved decision making method using fuzzy set theory has been attempted herein for converting linguistic data into numeric risk ratings. The concept of 'centre of area' method for generalized triangular fuzzy numbers has been explored to quantify the 'degree of hazard risk' in terms of crisp ratings. Finally, a logical framework for categorizing health hazards into different risk levels has been constructed on the basis of distinguished ranges of evaluated risk ratings (crisp). Subsequently, an action requirement plan has been suggested, which could provide guideline to the managers for successfully managing health hazard risks in the context of underground coal mining exercise.