Vinci K.C. Lee

Modified design model for the adsorption of dye onto peat

For over 20 years, peat has been recognized as a potential biosorbent for the treatment of wastewaters. Several studies have been reported in the literature including its use in cleaning oil spills 1 , the removal of heavy metals from wastewaters 2 , the removal of herbicides 3 , the treatment of slaughterhouse wastewaters, septic tank effiuents and dairy wastes 4 . The ability of peat to remove several dyes from aqueous effiuent was reported some time ago 5 . Further studies on single component adsorption of basic and acid dyes were carried out to study equilibrium isotherms 6 , diffusion based mass transport processes for batch and fixed bed systems 7 . Carbon has been used for acid dyes in fixed beds 8 . However, in these previous studies, conventional simplifi ed design methods—namely, bed depth service time (BDST) and empty bed residence time (EBRT) models—were applied to the experimental breakthrough curve data but failed to correlate these data due to the non-linearity of the BDST versus bed height data obtained. In the present paper new modifications have been developed based on an expression, N t / N 0 = 1 – exp(– a * sqrt ( t )), where N t , N 0 , a, t represent the bedcapacity at service time t, the saturated bed capacity found in isotherm experiments, a rate constant and the service time of the bed respectively. The expression correlates the residence time in the adsorption bed with the time dependent fraction degree of saturation of the bed. It enables modified BDST and EBRT models to be applied and correlate the experimental data very accurately. This model is particularly suited to predicting the performance of fixed bed adsorbers, when the system requires a long time to reach equilibrium or when several fixed bed adsorbers are used in series.

Improved Monitoring Protocol for Evaluating the Performance of a Sewage Treatment Works Based on Sensitivity Analysis of Mathematical Modelling

Extensive historical data of a sewage treatment works are required by numerical models in order to simulate the biological processes accurately. However, the data are recorded mostly for daily operational purpose. They are basically not comprehensive enough to meet the modelling’s requirements. A comprehensive sampling protocol to accurately characterise the influent is required in order to determine all model components, which is very time-consuming and expensive. In a project of evaluating a sewage treatment works in Chongqing by using BioWin 4.1 for mathematical modelling, sensitivity analysis was conducted to determine the most critical parameters for process monitoring. It was found that influent characteristics, wasted sludge flow rate, water temperatures, DO levels of the biological tanks and five bio-kinetic parameters were the most influential parameters governing the plant performance. Therefore, apart from monitoring the effluent quality, regular checking of the afore-mentioned influential parameters can help examine the performance of a sewage treatment works. Moreover, operators of the sewage treatment works can conduct “what-if” analysis to determine how these most influential parameters can be adjusted to improve the treatment performance of the sewage treatment works.