The potential of activated carbon from palm kernel shell (PKS-AC) to improve the quality of surface water and greywater based on the measurements of the parameters pH, turbidity, chemical oxygen demand (COD), total dissolved oxygen (TDS) and total suspended solids (TSS) was investigated in the present study. The PKS was acid treated with aqueous H 3 PO 4 (1 N) for overnight at room temperature and then subjected to heat treatment at 550 C for 2 h. The efficiency of the PSK-AC samples of 30 and 40 mm thicknesses was examined for reduction of the above parameters in surface water and greywater samples for 5, 15, 30 and 60 min of the filtration process. The efficiency of COD reduction by 50 and 56.44%, that of TDS by 57.81% and 22%, and that of TSS by 83.11 and 42.11% were detected using the PSK-AC samples above, respectively. The OH group contributed most to the removal of pollutants among the OH, N-H, C¼O, C¼C, C-O-C, C-O-H main functional groups pointed out via Fourier Transform Infra-red (FTIR) analysis on the surface. The scanning electron microscopy (SEM) images revealed that the surface of the raw PSK-AC appeared smooth with holes on the external surface, while the grains were filled in the PSK-AC after the adsorption process. ARTICLE HISTORY
Abstract. Industrial company such as textile, leather, cosmetics, paper and plastic generated wastewater containing large amount of dye colour. The removal of dye materials are importance as the presence of this kind of pollutant influence the quality of water and makes it aesthetically unpleasant. As their chemical structures are complicated, it is difficult to treat dyes with municipal waste treatment operations. Even a small quantity of dye does cause high visibility and undesirability. There have been various treatment technique reviewed for the removal of dye in wastewater. However, these treatment process has made it to another expensive treatment method. This review focus on the application of adsorbent in dye removal from textile wastewater as the most economical and effective method, adsorption has become the most preferred method to remove dye. The review provides literature information about different basis materials used to produce activated carbon like agricultural waste and industrial waste as well as the operational parameters factors in term of contact time, adsorbent dosage, pH solution and initial dye concentration that will affect the process in removing textile dye. This review approach the low cost and environmental friendly adsorbent for replacing conventional activated carbon.
Electrokinetic Stabilisation (EKS) method has the potential to overcome problems on highly compressible clay. This study presents the monitoring results from an experimental study of EKS on soft clay soil. Inactive kaolinite clay, inert electrode and distilled water (DW) were used as a pure system mechanism before any chemical stabilisers are utilised for stabilisation. Therefore, this monitoring data will provide a baseline study to improve efficiency of the EKS approach for ground improvement application. An inert electrode of Electrokinetic Geosythentic (EKG) developed at the Newcastle University was utilised to apply a constant voltage gradient of 50 V/m across a soil sample of 400 mm length. The distilled waters were used at the pore electrolyte fluid compartments and supplied under zero hydraulic gradient conditions for periods of 3, 7 and 14 days. Throughout, monitoring data of electric current for all treatments were measured. Results showed that the electric current trend in this pure system was attributed to the electrochemical effects in the clay-water electrolyte system.
Malaysia is currently a rapidly developing country to achieve a 2020 vision. However the development that has been carried out contributed to a negative impact on the environment especially on water quality. Due to the deterioration of water quality, serious management efforts on water quality has been taken. Thus, the aim of this study is to investigate a technique that can automatically classify the water quality. The technique is based on the concept of Artificial Neural Network (ANN). Since the greater part of their methodologies depend on the idea of `pattern recognition’. Thus, it is convenient to inspect its ability in classify water quality. There are six environmental data were used in this study such as pH, total suspended solids (TSS), dissolved oxygen (DO), chemical oxygen demand (COD), biological oxygen demand (BOD), and ammonia. The data was obtained by in-site measurement and laboratory analysis. Then, the data was used as the feeder of input variables in the ANN database system. After training and testing the network of ANN, the result showed that 80.0% of accuracy classification with 0.468 of root mean square error (RMSE). This showed the encouraging results for classification.
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