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Sulphuric acid-modified bagasse has been used as low-cost adsorbent for the removal of methylene blue (MB) dye from aqueous solution. In order to remove organic compounds that contribute to chemical oxygen demand (COD), pretreatment with thorough washing of adsorbent using boiling distilled water was performed instead of conventional washing using distilled water at room temperature only. This has resulted in the highest efficiency of color removal of 99.45% and COD reduction of 99.36% for MB dye solution at pH 9. Effects of initial pH, dye concentration, adsorbent dosage, temperature, and contact time have been studied. The adsorption of MB dye was pH dependent. Langmuir and Freundlich isotherm models were tested on the adsorption data. The kinetic experimental data were analyzed using pseudo-first order, pseudo-second order, and the intraparticle diffusion model in order to examine the adsorption mechanisms. The adsorption process followed the Langmuir isotherm as well as the Freundlich isotherm and pseudosecond-order kinetic model. The process was found to be endothermic in nature.

Multivariate statistical techniques such as cluster analysis (CA), factor analysis (FA) were used for the evaluation of spatial variations and the interpretation of a large complex water quality data set of two selected estuaries of Malaysia. The two locations of interest with 10 sites in each location were Kuala Juru (Juru estuary) and Bukit Tambun (Jejawi estuary). Cluster analysis showed that some sites in both locations have similar sources of pollution from point or non-point sources whereas FA yielded four factors which are responsible for water quality variations explaining more than 80% of the total variance of the data set and allowed to group the selected water quality. Correlation analysis of the data showed that some parameters have strong association with other parameters and they share a common origin source. This study illustrates the usefulness of multivariate statistical analysis for evaluation and interpretation of complex data sets to get better information about the pollution sources/factors and understanding the behavior of the parameters in water quality for effective river water quality management.

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A facile synthesis of carbon nanotube hybrid nanostructures: energy and environmental applications.