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.     

Glutathione Related Enzyme Levels of Freshwater Fish as Bioindicators of Pollution

The livers and kidneys of freshwater fish species, Oreochromis niloticus and Clarias lazera, collected from sewage polluted sites (Ismailia and El-Bahr El-Azam) and industrial polluted sites (Shubra and El-Tebin) of Nile River were analyzed for different antioxidant defense enzymes. The liver and kidney glutathione transferase (GST), glutathione reductase (GR) and glutathione peroxidase (GPx) were higher in O. niloticus captured from all the polluted areas compared to the control. Low GST activities were found in 33.3%, 60% and 53% in the livers and 100%, 80% and 53% in the kidneys of C. lazera captured from El-Bahr El-Azam, Shubra and El-Tebin. GR and GPx activities increased in livers and kidneys of C. lazera collected from all areas except for Shubra, in which, GPx of livers and kidneys were low in 100% of C. lazera. Metals Ni, Co, Cr, Se, Cd and Pb resulting from industrial wastes and metal mining wastes were enhanced at the polluted sites. SDS-PAGE of liver and kidney of O. niloticus and C. lazera indicated the increase in bands number and intensity of protein bands with subunit molecular weights between 30–20 KDa in polluted areas. Several enzymes from glutathione system (activity and protein) constitute a sensitive biochemical indicator of chemical pollution. Relative changes of glutathione-dependent enzymes in both fish species suggest a different susceptibility to toxins.     

Selenium and nano-selenium in plant nutrition

Selenium (Se) is a naturally occurring metalloid element which occurs nearly in all environments. Se is considered as a finite and non-renewable resource on the Earth. The common sources of Se in earth’s crust occur in association with sulfide minerals such as metal selenide, whereas it is rarely found in elemental form (Se⁰). While there is no evidence of Se need for higher plants, several reports show that when Se added at low concentrations, Se exerts beneficial effects on plant growth. Se may act as quasi-essential micronutrient through altering different physiological and biochemical traits. Thus, plants vary considerably in their physiological and biochemical response to Se. This review focusses on the physiological importance of Se forms as well as different Se fertilizers for higher plants, especially plant growth, uptake, transport, and metabolism.     

Sorption and mobility of polyethylene glycol (PEG 4000) in tropical soils

Millions of tons of polyethylene glycols (PEGs) are manufactured worldwide and most of them will reach conventional sewage disposal systems after industrial utilization. This raises environmental concerns, but not much is known about the environmental fate of these polymers. The main goals of this research were to evaluate sorption and mobility of PEG in sandier soils of Brazil. PEG 4000 was applied to the soils either freely in solution or as a simulated bioassay residue. The bioassay was prepared to simulate PEG as it is present in the animal feces. It allowed us to compare PEG mobility for both forms of environment disposal. PEG showed very low sorption (<22% of the applied PEG) and high mobility potential (>43% of the applied amount in the free-PEG and >24% of the applied amount in the bioassay-PEG experiment) in the studied soils. When PEG was applied, simulating its supply to animal diets, about 30% of its applied amount was retained into the bioassay residues and its leaching potential was reduced, whereas the remaining amount (about 70%) was readily available in solution and could be directly released into the environment.     

A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management

Environmental Science and Pollution Research - Energy is the source of economic growth, and energy consumption indicates the country’s state of development. Energy engineering is a relatively...