Fatality risk assessment and modeling of drivers responsibility for causing traffic accidents in Dubai

Introduction: This paper examines crash and safety statistics from the Emirate of Dubai in an attempt to identify factors responsible for making this population at greater risk of crashes compared to other countries. Problem: In developing countries such as the United Arab Emirates (U.A.E.), motor-vehicle-related mortalities frequently exceed those of the industrialized nations of North America and Europe. Method: Fatality and injury data used in the analysis mainly come from Dubai Emirate police reports and from other relevant international sources. Groups of the population are identified according to associated risk and exposure factors. Influence and strength of the most common risk factors are quantified using relative risk, the Lorenz curve, and the Gini index. Further analysis employed logit modeling, and possible predictors available in Dubai police reports, to estimate probability and odds ratios associated with drivers that are deemed responsible for causing traffic accidents. Results: Traffic fatality risk was found to be higher in Dubai, compared to some developed nations, and to vary considerably between different classes of road users and groups of the resident population. The likelihood of a driver causing an accident is considerably higher for those driving goods vehicles, but it is also associated with other factors. Impact: Results provide epidemiological inferences about traffic mortality and morbidity, and suggest priorities and appropriate measures for intervention, targeting resident population.     

MEASURING ECONOMIC LOSSES FROM GROUND WATER CONTAMINATION: AN INVESTIGATION OF HOUSEHOLD AVOIDANCE COSTS1

ABSTRACT: Economic losses from ground water contamination were estimated in a central Pennsylvania community. The averting expenditures method was applied via a mail survey of households in which water contained the unregulated volatile organic chemical, perchloroethylene (PCE). Expenditures were estimated at $148,900 (1987 dollars) over the six-month contamination period or approximately $252 per household annually. These costs underestimate the lower bound measure of welfare losses to households from ground water contamination. An upper bound measure of welfare losses was estimated at $383 per household annually. These estimates do not represent the full economic losses resulting from ground water contamination since the study did not address municipal-level and business avoidance costs and losses from actual health effects, increased fear and anxiety, ecological damages, and nonuser ground water benefits. The results expand the existing empirical base of information about municipal-level responses and economic losses from ground water contamination to include household-level impacts. The findings indicate that households undertake substantial averting actions in response to ground water contamination and that such actions can have significant economic consequences. The extent and magnitude of avoidance costs documented suggests that policy-makers should give greater attention to this category of economic losses.     

Comparison of Advection-Diffusion Models and Neural Networks for Prediction of Advanced Water Treatment Effluent

An artificial neural network (ANN) can help in the prediction of advanced water treatment effluent and thus facilitate design practices. In this study, sets of 225 experimental data were obtained from a wastewater treatment process for the removal of phosphorus using oven-dried alum residuals in fixed-bed adsorbers. Five input variables (pH, initial phosphorus concentration, wastewater flow rate, porosity, and time) were used to test the efficiency of phosphorus removal at different times, and ANNs were then used to predict the effluent phosphorus concentration. Results of experiments that were conducted for different values of the input parameters made up the data used to train and test a multilayer perceptron using the back-propagation algorithm of the ANN. Values predicted by the ANN and the experimentally measured values were compared, and the accuracy of the ANN was evaluated. When ANN results were compared to the experimental results, it was concluded that the ANN results were accurate, especially during conditions of high phosphorus concentration. While the ANN model was able to predict the breakthrough point with good accuracy, the conventional advection-diffusion equation was not as accurate. A parametric study conducted to examine the effect of the initial pH and initial phosphorus concentration on the effluent phosphorus concentration at different times showed that lower influent pH values are the most suitable for this advanced treatment system.     

Preparation and Characterization of Polyaniline and Ag/ Polyaniline Composite Nanoporous Particles and Their Antimicrobial Activities

Polyaniline (PANI) and Ag/PANI nanoporous composite were prepared by an oxidative polymerization method. The oxidation process of PANI nanoparticles was occurred using (NH₄)₂S₂O₈ while the oxidation process of Ag/PANI nanoporous composite was occurred using AgNO₃ under the effect of artificial radiation. The structural, morphological, and optical properties of the PANI and Ag/PANI nanoporous structures were studied using different characterization tools. The results confirm the formation of polycrystalline nanoporous PANI and spherical nanoporous composite of Ag/PANI particles. Antibacterial activity tests against gram-positive bacteria, Bacillus subtilis and Staphylococcus aureus, and gram-negative bacteria, Escherichia coli, and Salmonella species were carried out using different concentrations of PANI nanoparticles and Ag/PANI nanoporous composites. PANI has not antibacterial effect against all studied pathogens. In contrast, Ag/PANI nanoporous composites possessed antibacterial activity that is identified by the zone of inhibition. The inhibition zones of bacteria are in order; Salmonella species?>?S. aureus?>?B. subtilis?>?E. coli. The inhibition zones of all bacteria increased with increasing concentrations of Ag/PANI nanoporous composites from 200 to 400 ppm then decreased with further increasing of the dose concentrations to 600 ppm. Finally, a simplified mechanism based on the electrostatic attraction is presented to describe the antimicrobial activity of Ag/PANI nanoporous composite.     

Adsorptive removal of iron and manganese ions from aqueous solutions with microporous chitosan/polyethylene glycol blend membrane

Microporous chitosan (CS) membranes were directly prepared by extraction of poly(ethylene glycol) (PEG) from CS/PEG blend membrane and were examined for iron and manganese ions removal from aqueous solutions. The different variables affecting the adsorption capacity of the membranes such as contact time, pH of the sorption medium, and initial metal ion concentration in the feed solution were investigated on a batch adsorption basis. The affinity of CS/PEG blend membrane to adsorb Fe(II) ions is higher than that of Mn(II) ions, with adsorption equilibrium achieved after 60 min for Fe(II) and Mn(II) ions. By increasing CS/PEG ratio in the blend membrane the adsorption capacity of metal ions increased. Among all parameters, pH has the most significant effect on the adsorption capacity, particularly in the range of 2.9-5.9. The increase in CS/PEG ratio was found to enhance the adsorption capacity of the membranes. The effects of initial concentration of metal ions on the extent of metal ions removal were investigated in detail. The experimental data were better fitted to Freundlich equation than Langmuir. In addition, it was found that the iron and manganese ions adsorbed on the membranes can be effectively desorbed in 0.1 mol/L HCl solution (up to 98% desorption efficiency) and the blend membranes can be reused almost without loss of the adsorption capacity for iron and manganese ions.     

Bioavailability of heavy metals in fresh water Tilapia nilotica (Oreachromis niloticus Linnaeus, 1758): Potential risk to fishermen and consumers

The study was undertaken to assess the accumulation of some heavy metals (Cr, Co, Cu, Ni, Zn, Pb and Cd) in different tissues (muscle, gills, heart, liver, brain, bone and skin) of Tilapia nilotica. It is one of the most edible fish species in Egypt and was collected from a commercial fish farm in order to evaluate their potential risk to fishermen and consumers. This fish farm is fed with discharged water containing agricultural, industrial, sewage and domestic wastes. The length-weight relation and condition factor calculation of Tilapia nilotica samples showed a significant linear regression (r² = 0.920) and an average condition factor of 4.1 g/cm³. This indicated that the health status for the studied fish samples was good. Metal pollution index (MPI) values for the determined heavy metals in the different tissues reflected that the muscle was the only tissue that had the lowest content. Provisional Tolerable Weekly Intake (PTWI) values for the investigated heavy metals were lower than those reported for the permissible limits. The data were evaluated by using ANOVA statistical analysis. For appraising the human health risk effects of heavy metals in fish muscle, estimated dietary intake (EDI) and hazard quotient (HQ) were determined. HQ levels indicated that Cr and Co were the only heavy metals among the determined ones that had values more than unity. Also, their relative contributions in fish consumptions were Cr> Co> Pb> Ni> Cu> Cd> Zn. The highest average HQ value of chromium determined in this study referred to the possible adverse effects of Cr on human health. Accordingly, the potential public health risks from dietary exposure to hazardous contaminants in fish species from fish farms must be continually subjected to research, regulation and debate.