The Bio-Ecological Drainage System (BIOECODS) is a sustainable drainage (SUDS) to demonstrate the 'control at source' approaches for urban stormwater management in Malaysia. It is an environmentally friendly drainage system that was designed to increase infiltration, reduce peak flow at outlet, improve water quality, through different BMPs, such as grass swale, retention pond, etc. A special feature of BIOECODS is ecological swale with on-line subsurface detention. This study attempted to create a model of ecological swale with on-line subsurface conveyance system with InfoWorks SD. The new technique has been used Storm Water Management Model (SWMM) model to describe overland flow routing and Soil Conservation Service Method (SCS) used to model infiltration or subsurface flow. The modeling technique has been proven successful, as the predicted and observed closely match each other, with a mean error of 4.58 to 7.32%. The calibrated model then used to determine the ratio of the flow exchange between the surface and subsurface drainage system. Results from the model showed that the runoff ratio exchange between the surface and subsurface is 60 to 90%.
In this study two deep eutectic solvents (DESs) were prepared using ethylene glycol (EG) and two different ammonium-based salts. The potential of these DESs as novel agents for CNTs functionalization was examined by performing a comprehensive characterization study to identify the changes developing after the functionalization process. The impact of DESs was obvious by increasing the surface area of CNTs to reach 197.8 (m2/g), and by adding new functional groups to CNTs surface without causing any damage to the unique structure of CNTs. Moreover, CNTs functionalized with DESs were applied as new adsorbents for the removal of methyl orange (MO) from water. The adsorption conditions were optimized using RSM-CCD experimental design. The kinetics and the equilibrium adsorption data were analyzed using different kinetic and isotherm models. According to the regression results, adsorption kinetics data were well described by pseudo-second order model, whereas adsorption isotherm data were best represented by Langmuir isotherm model. The highest recorded maximum adsorption capacity (qmax) value was found to be 310.2 mg/g.
In the recent decade, deep eutectic solvents (DESs) have occupied a strategic place in green chemistry research. This paper discusses the application of DESs as functionalization agents for multi-walled carbon nanotubes (CNTs) to produce novel adsorbents for the removal of 2,4-dichlorophenol (2,4-DCP) from aqueous solution. Also, it focuses on the application of the feedforward backpropagation neural network (FBPNN) technique to predict the adsorption capacity of DES-functionalized CNTs. The optimum adsorption conditions that are required for the maximum removal of 2,4-DCP were determined by studying the impact of the operational parameters (i.e., the solution pH, adsorbent dosage, and contact time) on the adsorption capacity of the produced adsorbents. Two kinetic models were applied to describe the adsorption rate and mechanism. Based on the correlation coefficient (R2) value, the adsorption kinetic data were well defined by the pseudo second-order model. The precision and efficiency of the FBPNN model was approved by calculating four statistical indicators, with the smallest value of the mean square error being 5.01 × 10-5. Moreover, further accuracy checking was implemented through the sensitivity study of the experimental parameters. The competence of the model for prediction of 2,4-DCP removal was confirmed with an R2 of 0.99.