Global NEST Journal

A technique for green manufacturing of zinc oxide based nanoparticles utilising cassava peel has been approached in this research for antibacterial investigation. Especially, the cassava peel is an agro waste from starch and food processing industries and the extract of Cassava peel is used for synthesising the zinc oxide nanoparticles (ZnO-NPs). The peel based zinc oxide nanoparticles were synthesized using bioreduction method. The plasmon peak from UV–Visible spectroscopy is observed at 380 nm, while the XRD shows an average crystallite size of 67.31nm with hexagonal structure and also the stability of bio synthesised nanoparticles are confirmed by FTIR study. Additionally, FESEM confirms the structure is found to be spherical whereas Zeta potential analysis has confirmed the nanoparticles have a stable and well-dispersed form. Furthermore, the anti bacterial study against bio synthesized ZnO-NPs is carried out for both gram positive and gram negative bacteria. Therefore, the results proved that the bacteria are found to be more active against the synthesized nanoparticles.

The dumping of solid waste in uncontrolled landfills can cause significant impacts on the environment and human health. The open dumps cause the formation of leachate which contaminated the groundwater; use of these groundwater reported danger to the human health. The goal of groundwater protection is necessary to control the release and migration of pollutants from the leachate in the subsurface. In this paper, the above-mentioned problems were dealt with the case study of Ariyamangalam open dumping site, Tiruchirappalli, Tamilnadu. The dump site receives 71% of organic waste. The groundwater flow and leachate transport model was developed using Visual MODFLOW and MT3DMS (Version 4.3), to study the leachate transport in the subsurface and to predict the plume behavior under different scenarios. The conceptual model of the system was derived from the information on geology, geo physical and geo hydrology of the study area. The total dissolved solids (TDS) were taken as a parameter, to study the extent of contaminant plume for the next nine years (2014-2022). From the groundwater flow model, it was found that the increase in water level by 2.5 m above MSL from December 2010 (70.9 m above MSL) to December 2022 (73.4 m above MSL) around the study area. From the leachate transport model, the predicted TDS plume movement was identified towards the west and south east directions of the open dumping area. As a conclusion, the developed groundwater flow and leachate transport model can be effectively used for studying the leachate migration from the open dumping site into subsurface system.

Water famine is very cruel. The desalination plant was brought in to alleviate the water shortage. A desalination plant has been set up in many places around the world. In the view of expanding worldwide need of fresh water, the usage of desalination plant becomes more common. There are more than twenty-five thousand desalination plants around the world. Many industries require treated water for production, water treatment, and other functions. Water quality is occasionally insufficient or does not satisfy the quality criteria for manufacturing causes. So, the enterprises utilize desalination systems to purify water for their own usage. It makes the water safe to drink as well as suitable for a variety of industrial applications. The fault occurring in the desalination plant, it slows down the processing the speed and reduce the output rate. In this study, focuses on the faults like not under system control, electrical fault, pump fault, control valve fault, inaccurate signal, old data fault, derived fault and transmitter fault. The proposed artificial neural network with the single and double component fault (ANN S-DCF) is introduced to detect the faults occurring in the desalination plant. The faults are splitted into two catagories and characteristics of each fault are trained in the artificial neural network. The result of this work achieves the best accuracy comparing to the existing techniques of SVR (support vector regression), PCA (principal component analysis) and DPLS (dynamic partial least square) method. This study achieves the accuracy rate of 96%, precision rate of 93% and sensitivity rate of 95% respectively with low complexity and high operational speed.

In order to explore an effective assessment method for the treatment effect of heavy metal pollution in the sediment of Taihu Lake in China, based on the research background analysis and literature review, this paper reconstructs the spatial niche suitability model and applies it to the effect assessment of heavy metal pollution treatment in Taihu Lake sediment. The study found that the pollution degree of heavy metals in Taihu Lake sediment is as follows: North water area, West water area, South water area and East water area. The assessment results of the effect of heavy metal pollution treatment in Taihu Lake sediment by using SNSM are as follows: As > Cd > Hg > Ni > Mn > Zn > Pb > Cr > Cu. The four heavy metals that pose the greatest threat to the effect of Taihu Lake sediment are As, Cd, Hg and Ni; in particular, As and Cd are carcinogenic heavy metals, which the management authorities should pay special attention to. The research results of this paper are of great significance in supporting the government to formulate relevant policies for treating Taihu Lake and helping the management departments improve the treatment effect of heavy metal pollution in Taihu Lake sediments.