PREDICTION OF LOCAL SCOUR AROUND BRIDGE PIERS USING ARTIFICIAL NEURAL NETWORKS1

This paper describes a method for predicting local scour around bridge piers using an artificial neural network (ANN). Methods for selecting input variables, calibrations of network control parameters, learning process, and verifications are also discussed. The ANN model trained by laboratory data is applied to both laboratory and field measurements. The results illustrate that the ANN model can be used to predict local scour in the laboratories and in the field better than other empirical relationships that are currently in use. A parameter study is also carried out to investigate the importance of each input variable as reflected in data.     

Catalytic liquid-phase oxidation of acetaldehyde to acetic acid over a Pt/CeO2–ZrO2–SnO2/γ-alumina catalyst

Pt/CeO₂–ZrO₂–SnO₂/γ-Al₂O₃ catalysts were prepared by co-precipitation and wet impregnation methods for catalytic oxidation of acetaldehyde to acetic acid in water. In the present catalysts, Pt and CeO₂–ZrO₂–SnO₂ were successfully dispersed on the γ-Al₂O₃ support. Dependences of platinum content and reaction time on the selective oxidation of acetaldehyde to acetic acid were investigated to optimize the reaction conditions for obtaining both high acetaldehyde conversion and highest selectivity to acetic acid. Among the catalysts, a Pt(6.4 wt.%)/Ce_0.68Zr_0.17Sn_0.15O_2.0(16 wt.%)/γ-Al₂O₃ catalyst showed the highest acetaldehyde oxidation activity. On this catalyst, acetaldehyde was completely oxidized after the reaction at 0°C for 8 hr, and the selectivity to acetic acid reached to 95% and higher after the reaction for 4 hr and longer.     

Distributions of heavy metals in the sediments of South Korean harbors

Bottom sediments of harbors in the South Korea have been long suspected for metal contamination due to ship-based and urban-based activities for the past several decades. A number of areas have been suspected to impair ecosystem services to the local residents and drawn complaints from main stakeholders. Twelve contamination suspected harbors were subject to evaluate the level of contamination of Cr, Ni, Cu, Zn, As, Cd, Pb and Hg. The level of sediment contamination for each metal was evaluated comparing the relative enrichment of a given metal to pollution-insensitive aluminum. Regional background concentration of a given metal was also determined based on its down core measurement and sediment texture. Ecological risk posed by the presence of heavy metals was evaluated using the sediment quality guidelines (SQGs) developed by United States National Ocean and Atmosphere Administration (US NOAA) as benchmarks for evaluating sediment chemistry to aquatic organisms. Cu, Zn, Cd, Pb and Hg in the surface sediment were found to be higher than a factor of 1.5 than background sediments, and the overall metal contaminations of surface sediment can be regarded as medium-high- to high-priority sites in the sense of SQGs.     

High removal of phosphate from wastewater using silica sulfate

This report shows that silica sulfate is removing phosphate from wastewater very efficiently. Phosphorus removal and recovery from wastewater is a worldwide issue due to pollution of natural waters by phosphate and depletion of phosphate ores. Adsorption is a process that can remove phosphate at low concentrations. Adsorption also allows the recovery of phosphate for possible re-use. Here, we studied the adsorption of phosphate from wastewater using commercial Zr ferrite, Zr-MCM 41 and silica sulfate. We calculated equilibrium isotherms, kinetic models and thermodynamic effects under conditions similar to real wastewaters. We found that the equilibrium data for the adsorption of phosphate were best fitted to the Freundlich model. The results show that the maximum uptake of phosphate was 3.36 mg g⁻¹ for Zr-MCM, 27.73 mg g⁻¹ for Zr ferrite and 46.32 mg g⁻¹ for silica sulfate. The kinetic results of the three adsorbents were satisfactorily predicted using a pseudo-second-order model. We found that silica sulfate provided excellent characteristics in terms of the maximum adsorption and rate constant for the adsorption of phosphate. The thermodynamic data showed that increasing the temperature enhanced the adsorption of phosphate onto silica sulfate. Our findings will help to define efficient methods to remove phosphate from wastewater.     

Flow and mass balance analysis of eco-bio infiltration system

A structured stormwater infiltration system was developed and constructed at a university campus and monitoring of storm events was performed during a one-year operation period. The flow and pollutant mass balances were analyzed and the overall efficiency of the system was assessed. While significant positive correlations were observed among rainfall, runoff and discharge volume (R²= 0.93-0.99; p<0.05), there was no significant correlations existed between rainfall, runoff, discharge volume and pollutant load. The system was more effective in reducing the runoff volume by more than 50% for small storm events but the difference between the runoff and discharge volume was significant even with rainfall greater than 10 mm. Results showed that the pollutant reduction rates were higher compared to the runoff volume reduction. Average pollutant reduction rates were in the range of 72% to 90% with coefficient of variation between 0.10 and 0.46. Comparable with runoff reduction, the system was more effective in reducing the pollutant load for small storm events, in the range of 80% to 100% for rainfall between 0 and 10 mm; while 65% to 80% for rainfall between 10 and 20 mm. Among the pollutant parameters, particulate matters was highly reduced by the system achieving only a maximum of 25% discharge load even after the entire runoff was completely discharged. The findings have proven the capability of the system as a tool in stormwater management achieving both flow reduction and water quality improvement.     

Combined toxic effect of airborne heavy metals on human lung cell line A549

Many studies have demonstrated that heavy metals existing as a mixture in the atmospheric environment cause adverse effects on human health and are important key factors of cytotoxicity; however, little investigation has been conducted on a toxicological study of a metal mixture from atmospheric fine particulate matter. The objective of this study was to predict the combined effects of heavy metals in aerosol by using in vitro human cells and obtain a suitable mixture toxicity model. Arsenic, nickel, and lead were selected for mixtures exposed to A549 human lung cancer cells. Cell proliferation (WST-1), glutathione (GSH), and interleukin (IL)-8 inhibition were observed and applied to the prediction models of mixture toxicity, concentration addition (CA) and independent action (IA). The total mixture concentrations were set by an IC₁₀-fixed ratio of individual toxicity to be more realistic for mortality and enzyme inhibition tests. The results showed that the IA model was statistically closer to the observed results than the CA model in mortality, indicating dissimilar modes of action. For the GSH inhibition, the results predicted by the IA and CA models were highly overestimated relative to mortality. Meanwhile, the IL-8 results were stable with no significant change in immune reaction related to inflammation. In conclusion, the IA model is a rapid prediction model in heavy metals mixtures; mortality, as a total outcome of cell response, is a good tool for demonstrating the combined toxicity rather than other biochemical responses.     

PCB levels and congener patterns from Korean municipal waste incinerator stack emissions

Congener specific polychlorinated biphenyl (PCB) data from the stack gas of nine Korean municipal waste incinerators was used to determine characteristic congener patterns of emitted PCBs. Principal component analysis revealed three classes of incinerators according to their pattern of PCB congener emissions: those resembling the background sampling material; those producing large quantities of a few tetra-chlorinated congeners; those producing large proportions of mono (MO-) and non-ortho (NO-) congeners relative to di-ortho (DO-) levels. Also, correlations between individual PCB congeners and polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs) were discovered for several NO-PCBs and tetra and penta chlorinated PCDFs. Full PCB congener data is presented along with operating conditions for each incinerator.     

Effect of solids concentration on bacterial leaching of heavy metals from sewage sludge

Microbial metal leaching from sewage sludge (2-9% w/v) was carried out with the iron-oxidizing bacterium Thiobacillus ferrooxidans. Measurements of pH, oxidation-reduction potential, and concentration of Fe2+ indicated that T. ferrooxidans was effective in removing metals from an incubation bath containing less than 5% sludge solids concentration. Specifically, Cu leaching was completely suppressed at a high solids concentration of 9% (w/v). Results indicated that the deactivation of T. ferrooxidans at a high sludge content was mainly due to the presence of inhibiting materials such as organic matter. A mixed culture of sulfur-oxidizing bacteria was obtained by enrichment from anaerobically digested sewage sludge to enhance the efficiency of the microbial leaching process. These bacteria were much more effective in metal leaching than was iron-oxidizing T. ferrooxidans. At 9% (w/v) solids concentration, the leaching efficiencies of Zn and Cu were 78% (2.66 g/kg dry sludge) and 59% (1.36 g/kg dry sludge), respectively. Therefore, when removing heavy metals from the anaerobically digested sewage sludge, the indigenous sulfur-oxidizing bacteria isolated in the current study were more efficient than T. ferrooxidans, especially at high sludge solids concentrations.