The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m(3) s(-1), representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size > 0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5%. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20%) compared to group 2 (16.90 to 45.55%). Two Fisher's linear discriminant functions, F 1 and F 2, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F 1 = -9.405 + 4232.119 × A - 1795.805 × B + 281.224 × C, and F 2 = -2.842 + 2725.137 × A - 1307.688 × B + 231.353 × C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m(3) s(-1), respectively. The model correctly predicts 88.9 and 100.0% of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8% are correctly classified. The model predicts that 31.4% of the model domain areas consist of high-sand mass composition areas and the remaining 68.6% comprise low-sand mass composition areas.
Anaerobic treatment processes to remove organic matter from palm oil mill effluent (POME) have been used widely in Malaysia. Still the amounts of total organic and total mineral released from POME that may cause degradation of the receiving environment need to be verified. This paper proposes the use of the hydrodynamic equations to estimate performance of the cascaded anaerobic ponds (CAP) and to calculate amounts of total organic matter and total mineral released from POME. The CAP efficiencies to remove biochemical oxygen demands, chemical oxygen demands, total solids and volatile solids (VS) as high as 94.5, 93.6, 96.3 and 98.2 %, respectively, are estimated. The amounts of total organic matter and total mineral as high as 538 kg VS/day and 895 kg FS/day, respectively, released from POME to the receiving water are calculated. The implication of the proposed hydrodynamic equations contributes to more versatile environmental assessment techniques, sometimes replacing laboratory analysis.
Evaluation of health risks due to heavy metals exposure via drinking water from ex-mining ponds in Klang Valley and Melaka has been conducted. Measurements of As, Cd, Pb, Mn, Fe, Na, Mg, Ca, and dissolved oxygen, pH, electrical conductivity, total dissolved solid, ammoniacal nitrogen, total suspended solid, biological oxygen demand were collected from 12 ex-mining ponds and 9 non-ex-mining lakes. Exploratory analysis identified As, Cd, and Pb as the most representative water quality parameters in the studied areas. The metal exposures were simulated using Monte Carlo methods and the associated health risks were estimated at 95th and 99th percentile. The results revealed that As was the major risk factor which might have originated from the previous mining activity. For Klang Valley, adults that ingested water from those ponds are at both non-carcinogenic and carcinogenic risks, while children are vulnerable to non-carcinogenic risk; for Melaka, only children are vulnerable to As complications. However, dermal exposure showed no potential health consequences on both adult and children groups.
Heavy metals are highly toxic at trace levels and their pollution has shown great threat to the environment and public health worldwide where current detection methods require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Herein, we report a low-cost, paper-based microfluidic analytical device (μPAD) for facile, portable, and disposable monitoring of mercury, lead, chromium, nickel, copper, and iron ions. Triple indicators or ligands that contain ions or molecules are preloaded on the μPADs and upon addition of a metal ion, the colorimetric indicators will elicit color changes observed by the naked eyes. The color features were quantitatively analyzed in a three-dimensional space of red, green, and blue or the RGB-space using digital imaging and color calibration techniques. The sensing platform offers higher accuracy for cross references, and is capable of simultaneous detection and discrimination of different metal ions in even real water samples. It demonstrates great potential for semiquantitative and even qualitative analysis with a sensitivity below the safe limit concentrations, and a controlled error range.