Potential of bioretention plants in treating urban runoff polluted with greywater under tropical climate.

Bioretention systems are among the most popular stormwater best management practices (BMPs) for urban runoff treatment. Studies on plant performance using bioretention systems have been conducted, especially in developed countries with a temperate climate, such as the USA and Australia. However, these results might not be applicable in developing countries with tropical climates due to the different rainfall regimes and the strength of runoff pollutants. Thus, this study focuses on the performance of tropical plants in treating urban runoff polluted with greywater using a bioretention system. Ten different tropical plant species were triplicated and planted in 30 mesocosms with two control mesocosms without vegetation. One-way ANOVA was used to analyze the performance of plants, which were then ranked based on their performance in removing pollutants using the total score obtained for each water quality test. Results showed that vetiver topped the table with 86.4% of total nitrogen (TN) removal, 93.5% of total phosphorus (TP) removal, 89.8% of biological oxygen demand (BOD) removal, 90% of total suspended solids (TSS) removal, and 92.5% of chemical oxygen demand (COD) removal followed by blue porterweed, Hibiscus, golden trumpet, and tall sedge which can be recommended to be employed in future bioretention studies.

One step acid activation of bentonite derived adsorbent for the effective remediation of the new generation of industrial pesticides.

Herein, the facile one step acid activation of bentonite derived functionalized adsorbent (AB) for the effective remediation of both ionic and non-ionic secondary pesticides, ametryn and metolachlor has been attempted. The surface characteristics of AB were examined by the nitrogen adsorption-desorption analysis, scanning electron microscopy (SEM), and Fourier Transforms Infrared (FTIR) Spectroscopy. The adsorptive behavior was evaluated with respect to the effect of contact time, initial concentrations and solution pH. The equilibrium data were fitted to the Langmuir, Freundlich and Temkin isotherm models, while the adsorption kinetic was analyzed using the pseudo-first order and pseudo-second order kinetic equations. Thermodynamic parameters including the standard enthalpy change (ΔH°), standard entropy change (ΔS°), and Gibbs free energy change (ΔG°) were established. Thermodynamic analysis illustrated that the adsorption process was feasible and exothermic in nature, while the characterization findings verified the alteration of FTIR bands, and a high specific surface area of 464.92 m2/g, with a series of pores distributed over the surface. Equilibrium data was best confronted to the pseudo-second order kinetic model, while the adsorptive removal of ametryn and metolachlor onto AB was satisfactory described by the Langmuir isotherm model, with the monolayer adsorption capacities for ametryn and metolachlor of 2.032 and 0.208 mmole/g respectively. The findings outlined the potential of the newly develop AB for the on-site treatment of pesticide polluted water.

A review of bioretention components and nutrient removal under different climates-future directions for tropics.

Bioretention systems have been implemented as stormwater best management practices (BMPs) worldwide to treat non-point sources pollution. Due to insufficient research, the design guidelines for bioretention systems in tropical countries are modeled after those of temperate countries. However, climatic factors and stormwater runoff characteristics are the two key factors affecting the capacity of bioretention system. This paper reviews and compares the stormwater runoff characteristics, bioretention components, pollutant removal requirements, and applications of bioretention systems in temperate and tropical countries. Suggestions are given for bioretention components in the tropics, including elimination of mulch layer and submerged zone. More research is required to identify suitable additives for filter media, study tropical shrubs application while avoiding using grass and sedges, explore function of soil faunas, and adopt final discharged pollutants concentration (mg/L) on top of percentage removal (%) in bioretention design guidelines.

Development of emergency food assistance design: a nutritionally balanced, culturally tailored and cost-effective strategy for flood mitigation.

Emergency food assistance forms an integral component of flood mitigation in Malaysia. A cross-sectional survey investigating emergency food assistance among 202 flood victims was conducted and alternative food assistance plan was developed using linear programming targeting post-disaster food requirement scenarios. From the study, the receipt of food aid was significantly associated with ethnicity, household income, residential area and evacuation into temporary shelters. Linear programming analysis identified nutritionally appropriate food assistance targeting mass feeding, emergency food basket, and immediate food requirement for as low as MYR 6.07 (1.55 USD), MYR 7.14 (1.82 USD), and MYR 8.00 (2.04 USD), respectively. This study provides nutritional guidelines for disaster food assistance policy.

Prediction of water quality index in constructed wetlands using support vector machine.

Poor water quality is a serious problem in the world which threatens human health, ecosystems, and plant/animal life. Prediction of surface water quality is a main concern in water resource and environmental systems. In this research, the support vector machine and two methods of artificial neural networks (ANNs), namely feed forward back propagation (FFBP) and radial basis function (RBF), were used to predict the water quality index (WQI) in a free constructed wetland. Seventeen points of the wetland were monitored twice a month over a period of 14 months, and an extensive dataset was collected for 11 water quality variables. A detailed comparison of the overall performance showed that prediction of the support vector machine (SVM) model with coefficient of correlation (R(2)) = 0.9984 and mean absolute error (MAE) = 0.0052 was either better or comparable with neural networks. This research highlights that the SVM and FFBP can be successfully employed for the prediction of water quality in a free surface constructed wetland environment. These methods simplify the calculation of the WQI and reduce substantial efforts and time by optimizing the computations.

Spatial pattern analysis for water quality in free-surface constructed wetland.

Free-surface constructed wetlands are known as a low-energy green technique to highly decrease a wide range of pollutants in wastewater and stormwater before discharge into natural water. In this study, two spatial analyses, principal factor analysis and hierarchical cluster analysis (HACA), were employed to interpret the effect of wetland on the water quality variables (WQVs) and to classify the wetland into groups with similar characteristics. Eleven WQVs were collected at the 17 sampling stations twice a month for 13 months. All sampling stations were classified by HACA into three clusters, with high, moderate, and low pollution areas. To improve the water quality, the performance of Cluster-III (micropool) is more significant than Cluster-I and Cluster-II. Implications of this study include potential savings of time and cost for long-term data monitoring purposes in the free-constructed wetland.

Prediction of scour below submerged pipeline crossing a river using ANN.

The process involved in the local scour below pipelines is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of artificial neural networks (ANN) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published works and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANN was found to be more effective when compared with the results of regression equations in predicting the scour depth around pipelines.

Water balance: case study of a constructed wetland as part of the bio-ecological drainage system (BIOECODS).

The Bio-ecological Drainage System, or BIOECODS, is an urban drainage system located at the Engineering Campus, Universiti Sains Malaysia. It consists of a constructed wetland as a part of the urban drainage system to carry storm water in a closed system. In this closed system, the constructed wetland was designed particularly for further treatment of storm water. For the purpose of studying the water balance of the constructed wetland, data collection was carried out for two years (2007 and 2009). The results show that the constructed wetland has a consistent volume of water storage compared to the outflow for both years with correlation coefficients (R(2)) of 0.99 in 2007 and 0.86 in 2009.

Gene expression programming for total bed material load estimation--a case study.

This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.