The effects of soil properties and temperature on the adsorption isotherms of lead on some temperate and semiarid surface soils of Iran

Sorption of metal ions by soil and clay minerals is a complex process involving different mechanisms, and controlled by different variables that can interact. The aim of this work was to study the retention mechanisms of Pb ions on different soil samples. Surface soils were sampled from Guilan and Hamadan provinces in north and northwest of Iran with temperate and semiarid climates. The adsorption isotherms of Pb on the soils have been studied at 15, 27 and 37°C. The adsorption data for different soils were fitted into Langmuir and Freundlich models. Temperate soil samples had higher clay content, cation exchange capacity, dichromate (oxidable) organic carbon, total Kjeldahl-nitrogen, biological activity, amorphous and crystalline Fe and Al, but semiarid soil samples had higher sand content, pH, equivalent calcium carbonate, available P and K. Lead adsorption data obtained from semiarid soils against those obtained from temperate soils were better fitted in both Langmuir and Freundlich models. Langmuir constants Q ₀ for Pb adsorption in semiarid soils were considerably lower than those for Pb adsorption in temperate soils. However, the binding energy (K _L) of Pb and Freundlich constant n were higher for data of semiarid soils. The effect of temperature on the Pb adsorption was positive especially in temperate soils; however, soil properties had higher effects on Pb adsorption.     

Evaluation of workers' exposure to methylene diphenyl diisocyanate (MDI) in an automobile manufacturing company, Iran.

Evaluation of personal inhalation exposure to methylene diphenyl diisocyanate (MDI) among 39 employees, working in the window fixation and window glue processes in an automobile manufacturing company was performed. This study was conducted for both case and control groups. After sampling and sample preparation processes, MDI was determined with a UV-VIS spectrophotometer at 590 nm; the lung function was assessed with a digital spirometer, too. The average concentration of MDI in the window fixation, and window glue workplaces were 34.53 and 27.37 micro g/m3, respectively, which was lower than the threshold limit value (TLV) recommended by the American Conference of Governmental Industrial Hygienists (ACGIH) (51 micro g/m3). Respiratory symptoms in the exposed group were significantly different compared to the unexposed group (p < .05). Lung capacities in the case group were lower than in the control group (p < .05). Therefore, MDI can be easily measured making it possible to evaluate the adverse effects caused by occupational exposure.     

Cadmium and copper heavy metal treatment from water resources by high-performance folic acid-graphene oxide nanocomposite adsorbent and evaluation of adsorptive mechanism using computational intelligence,isotherm, kinetic,and thermodynamic analyses

Environmental Science and Pollution Research - In this paper, folic acid–coated graphene oxide nanocomposite (FA-GO) is used as an adsorbent for the treatment of heavy metals including...     

A modified exergy evaluation of using carbon-black/water/EG nanofluids as coolant of photovoltaic modules

Environmental Science and Pollution Research - To provide the progressive global demand for energy, the use of renewable energies is being rapidly developed. Since solar radiation is available in...     

DRASTIC framework improvement using Stepwise Weight Assessment Ratio Analysis (SWARA) and combination of Genetic Algorithm and Entropy

Environmental Science and Pollution Research - Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment...     

Application of Artificial Neural Networks to Predict Total Dissolved Solids at the Karaj Dam

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural networks using data from two water quality monitoring stations at the Karaj Dam in Iran. Input data were calcium ions (Ca²⁺), magnesium ions (Mg²⁺), sodium ions (Na⁺), chloride ions (Cl^?), sulfate (), and pH, and the output data were total dissolved solids (TDS). An MLP with one hidden layer containing eight neurons was selected for the upstream water quality station using normalized input data. We developed a second MLP neural network for the downstream station with one hidden layer containing 10 neurons in the hidden layer using normalized input data. Considering applying normalized input data and one hidden layer, the coefficient of determination (R ²) and index of agreement (IA) between the observed and the predicted data for the upstream and downstream monitoring stations using the MLP neural networks were 0.985, 0.84, 0.99, and 0.92, respectively. The RBF neural network with 100 neurons in its hidden layer reached the minimum errors between the observed and the predicted results in upstream and downstream stations. The R ² between observed and predicted data for upstream and downstream monitoring stations for the RBF was 0.999 and 0.998, respectively. Data normalization improved the performance of the MLP neural networks. Sensitivity analysis indicated that magnesium is the most effective water quality parameter for predicting TDS, and sulfate is the second most effective water quality parameter affecting TDS prediction at the Karaj Dam.     

Minimum quantity lubrication in grinding: effects of abrasive and coolant–lubricant types

This research has been conducted to study the influence of the abrasive and coolant–lubricant types on the minimum quantity lubrication (MQL) grinding performance. One type of CBN and three types of conventional wheels (corundum) have been tested. The tests have been performed in presence of fluid, air jet and eleven types of coolant–lubricants, as well as, in dry condition. The results indicate that the finest surface quality and lower grinding forces could be obtained while grinding with CBN wheel. In case of conventional wheels, the coarser and high porosity wheels induce much proper grinding results. Furthermore, grinding when utilizing MQL with oil results in higher grinding performance.     

GIS aided prediction of CO2 emission dispersion from geothermal electricity production

CO₂ is the dominant constituent of non-condensable gases in the steam phase of most geothermal fluids. This paper attempts to present the results of a study conducted to develop prediction modeling of CO₂ dispersion in the surrounding atmosphere from a planned 50 MWe geothermal power plant prior to its production. Dispersion models are widely used for predicting future concentrations of environmental emissions on a range of geographic scales. The dispersion type for gases and their average removal rate depends on the meteorological conditions such as wind direction, wind speed, precipitation, atmospheric stability, and surface roughness and topography. Geographic Information System (GIS) capabilities were used for quality visualization of the model outputs and presenting an accurate numerical copy of the study area. The results by the prediction model show that the natural transfer of CO₂ will be from the power plant toward east and northeast and CO₂ concentration trends after the power plant utilization will be similar to the background conditions with minor changes. This dispersion test was carried out to validate and field test the GIS aided dispersion modeling approach described in the paper and the procedure may be applicable for other studies assessing the emission dispersion of pollutants from a point source.     

Performance of activated carbon coated graphite bipolar electrodes on capacitive deionization method for salinity reduction

• Graphite bipolar electrodes act as an appropriate bed for the CDI process. • Activated carbon Coating improves the application of the electrodes. • CDI is an environmentally friendly method to apply for brackish water. • Initial concentration is the most important parameter in the CDI method. • CDI process in a batch-mode setup needs more development. This research investigates a capacitive deionization method for salinity reduction in a batch reactor as a new approach for desalination. Reductions of cost and energy compared with conventional desalination methods are the significant advantages of this approach. In this research, experiments were performed with a pair of graphite bipolar electrodes that were coated with a one-gram activated carbon solution. After completing preliminary tests, the impacts of four parameters on electrical conductivity reduction, including (1) the initial concentration of feed solution, (2) the duration of the tests, (3) the applied voltage, and (4) the pH of the solution, were examined. The results show that the maximum efficiency of electrical conductivity reduction in this laboratory-scale reactor is about 55%. Furthermore, the effects of the initial concentration of feed solution are more significant than the other parameters. Thus, using the capacitive deionization method for water desalination with low and moderate salt concentrations (i.e., brackish water) is proposed as an affordable method. Compared with conventional desalination methods, capacitive deionization is not only more efficient but also potentially more environmentally friendly.