Rashid Atta Khan

Preparation and characterizations of activated carbon from kenaf fiber for equilibrium adsorption studies of copper from wastewater

The potential of activated carbon prepared from kenaf fiber (KF) to remove copper (II) from aqueous effluents was investigated. The fibers were first semi-carbonized, then impregnated with potassium hydroxide (KOH) and finally activated by using carbon dioxide (CO2) gas to produce activated carbon. Pore structure and physical characteristics of the prepared kenaf fiber activated carbon (KFAC) were determined. Adsorption studies for divalent copper (Cu) ions were carried out to delineate the effect of contact time, temperature, pH and initial metal ion concentration on equilibrium adsorption capacity. The experimental data followed pseudo-second-order kinetics and Elovich Model than pseudo-first-order. Langmuir, Freundlich and Temkin models were implemented to analyze the parameters for adsorption at 30 °C, 50 °C and 70 °C. Thermodynamic parameters such as ΔGo, ΔHo and ΔSo which represent Gibbs free energy, enthalpy and entropy, respectively, were evaluated. It was concluded that activated carbon from kenaf fiber (KFAC) can be used as an efficient adsorbent for removal of Cu (II) from synthetic wastewater.

PREPARATION AND CHARACTERIZATION OF CHITOSAN/AGAR BLENDS: RHEOLOGICAL AND THERMAL STUDIES

In this work, a number of mixture aqueous solutions of chitosan/agar (CS/AG) at different ratios (considering chitosan as the main component) were prepared. The rheological properties i.e. shearing viscosity and shear stress of the blend solutions as a function of shear rate as well as the thermal properties of the blend films were investigated. Among the parameters studied were temperature, shearing time and storage time. Results showed that almost Newtonian behavior was observed at temperatures from 40°C to 55°C for the ratios 100/0, 90/10, 80/20 and 70/30. However, the proportions 60/40 and 50/50 showed a clear shear thinning behavior (pseudoplastic non-Newtonian behavior). It was also found that all the blend solutions obeyed the Arrhenius equation. In addition, the effect of shearing time on the shearing viscosity of all blends did not show any significant differences at all shearing times applied in this study except the proportion 50/50 wherein decreasing in shearing viscosity and shear stress was observed as the shearing time increased. Furthermore, different behaviors were observed for the blend solutions when the period of storage was extended to three weeks. The FTIR results and the differential scanning calorimetery (DSC) curves showed that the interaction between chitosan and agar can occur.

Preparation, characterization and adsorption performance of the KOH-activated carbons derived from kenaf fiber for lead (II) removal from waste water.

In this study, activated carbon was prepared from kenaf fiber (KF) by using physiochemical activation method consisting of potassium hydroxide (KOH) impregnation with carbon dioxide (CO2) gasification. Pore structure and physical characteristics of the prepared activated carbon were determined. Adsorption studies for divalent lead (Pb) were carried out to delineate the effect of contact time, temperature, pH and initial metal ion concentration. About 93.23% of Pb (II) was removed from 100 mg/l solution at pH 5.5. The experimental data followed pseudo second order kinetics which confirms chemisorptions. The linear plots of intra particle diffusion demonstrated that, the adsorption process is mainly governed by pore diffusion. The values of Langmuir dimensionless constant, RL and Freundlich constant, 1/n were less than 1 representing favorable process for adsorption. Thermodynamic parameters such as ∆G°, ∆H° and ∆S° which are related to Gibbs free energy, enthalpy and entropy were evaluated. The research concluded that activated carbon from kenaf fiber (KFAC) has sufficient porosities and surface area and it has got good potential to remove Pb (II) from waste water.

Study the Effect of Imposing Surfactants toward the Evaporation of Low Molecular Weight Alcohol

In this paper, Reversed-Flow Gas Chromatography (RF-GC) is utilized to investigate the evaporation of low molecular weight alcohol. Evaporation rates as well as the diffusion rates of methanol are determined with a surfactant monolayer on the surface of the liquid; while nitrogen acts as carrier gas, at 313 K. The precision (>99.9%) and accuracy of this investigation demonstrates the potential of current methodologies for environmental impact studies; this is further verified when the results are compared with the available literature. The varying evaporation rates of methanol in the presence of varying amounts of Triton X-100 reflects that application of surfactants do damper the evaporation rates of liquid pollutants; without interference with the former’s diffusion coefficients. High amounts of Triton X-100 are required for retardation of evaporation rates, suggesting the formation of a densely packed surface monolayer or the formation of an insoluble monolayer.

Determination of Diffusion Coefficients of Selected Long Chain Hydrocarbons using Reversed- Flow Gas Chromatographic Technique

The reversed-flow gas chromatography (RF-GC) technique was used to study the evaporation rate and estimating the diffusion coefficient of samples. The RF-GC system comprises of six-port valve, sampling and diffusion column, detector and modified commercial gas chromatography machine. Selected long chain of hydrocarbons (99.99% purity) was used as samples. The solute (stationary phase) were carried out by carrier gas (mobile phase) to the detector. The data obtained from the RF-GC analysis were analysed by deriving the elution curve of the sample peaks using mathematical expression to find the diffusion coefficients values of respective liquids. The values obtained were compared with theoretical values to ensure the accuracy of readings. The interesting findings of the research showed the theoretical values of equilibrium at liquid-gas interphase lead to profound an agreement with the experimental evidence, which contributes for the references of future studies.

Using Principal Component Scores and Artificial Neural Networks in Predicting Water Quality Index

The management of river water quality is a major environmental challenge. One of the major challenges is in determining point and non-point sources of pollutants. Industrial and municipal wastewater discharges can be considered as constant polluting sources, unlike surface water runoff which is seasonal and highly affected by climate. According to Aiken et al. (1982), 42 tributaries in Peninsular Malaysia are categorized as very polluted including the Langat River. Until 1999, there were about 13 polluted tributaries and 36 polluted rivers due to human activities such as, industry, construction and agriculture (Department of Environment, Malaysia (DOE), 1999). In 1990, there were 48 clean rivers classified as clean but the number is reduced to 32 rivers in 1999 (Rosnani Ibrahim, 2001).