Effect of nitrogen fertilizer application on growing season soil carbon dioxide emission in a corn-soybean rotation

Nitrogen application can have a significant effect on soil carbon (C) pools, plant biomass production, and microbial biomass C processing. The focus of this study was to investigate the short-term effect of N fertilization on soil CO(2) emission and microbial biomass C. The study was conducted from 2001 to 2003 at four field sites in Iowa representing major soil associations and with a corn (Zea mays L.)-soybean (Glycine max L. Merr.) rotation. The experimental design was a randomized complete block with four replications of four N rates (0, 90, 180, and 225 kg ha(-1)). In the corn year, season-long cumulative soil CO(2) emission was greatest with the zero N application. There was no effect of N applied in the prior year on CO(2) emission in the soybean year, except at one of three sites, where greater applied N decreased CO(2) emission. Soil microbial biomass C (MBC) and net mineralization in soil collected during the corn year was not significantly increased with increase in N rate in two out of three sites. At all sites, soil CO(2) emission from aerobically incubated soil showed a more consistent declining trend with increase in N rate than found in the field. Nitrogen fertilization of corn reduced the soil CO(2) emission rate and seasonal cumulative loss in two out of three sites, and increased MBC at only one site with the highest N rate. Nitrogen application resulted in a reduction of both emission rate and season-long cumulative emission of CO(2)-C from soil.     

Elimination of Cs+ from aquatic systems by an adsorbent prepared by immobilization of potassium copper hexacyanoferrate on the SBA-15 surface: kinetic,thermodynamic, and isotherm studies

Environmental Science and Pollution Research - For elimination of cesium from aqueous solutions, mesoporous SBA-15 was synthesized and employed as the support for immobilization of potassium copper...     

The effect of greenhouse vegetation coverage and area on the performance of an earth-to-air heat exchanger for heating and cooling modes

The underground temperature at a depth of about 3–4 m is almost constant all the year round. In summer, the underground temperature is lower than the ambient temperature, but in winter it is vice versa. This potentiality is considered for greenhouse cooling and heating by using an earth-to-air heat exchanger (EAHE). This paper considers the effects of two parameters as independent variables including the area of greenhouse and the percentage of vegetation coverage inside the greenhouse on the performance of an EAHE system during both cooling and heating modes. The inside temperature, the thermal energy exchange and the coefficient of performance (COP) of the system were considered as dependent variables. The results showed that both greenhouse area and the percentage of vegetation coverage inside the greenhouse had significant effects on the performance of the EAHE system during both cooling and heating modes. However, the COP of the EAHE system was higher in the cooling mode (4.32) than during the heating mode (1.01). The percentage of vegetation coverage negatively affected the performance of the EAHE system in the cooling mode. However, the performance of the EAHE system improved with the increase in the percentage of vegetation coverage during the heating mode.     

Relationship between musculoskeletal disorders and anthropometric indices among bus drivers in Zahedan city

Introduction. Most work-related musculoskeletal disorders (MSDs) are associated with improper postures and poorly designed workstations. This study is an attempt to examine the prevalence and severity of MSDs as well as anthropometric dimensions among city bus drivers. Methodology. This cross-sectional study was carried out on 60 male bus drivers. A body discomfort chart was used to evaluate MSDs. Spearman correlation was employed to examine the relationship between body size and the severity of discomfort. Results. Data analysis showed that discomfort reported in the lower back (33.3%), upper back (18.3%) and knee (15%) was severe and there was a direct and significant correlation between the body mass index and the severity of discomfort in the shoulder, arm and hip (p?p?Conclusion. The results of the study can be used to address ergonomic risk factors and reduce their associated disorders. The findings of the study can be used in training programs to educate drivers how to decrease the risk associated with work-related MSDs by adopting appropriate behavior strategies.     

Predicting Carbon Monoxide Concentrations in the Air of Pardis City,Iran, Using an Artificial Neural Network

To date, several methods have been proposed to explain the complex process of air pollution prediction. One of these methods uses neural networks. Artificial neural networks (ANN) are a branch of artificial intelligence, and because of their nonlinear mathematical structures and ability to provide acceptable forecasts, they have gained popularity among researchers. The goal of our study as documented in this article was to compare the abilities of two different ANNs, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks, to predict carbon monoxide (CO) concentrations in the air of Pardis City, Iran. For the study, we used data collected hourly on temperature, wind speed, and humidity as inputs to train the networks. The MLP neural network had two hidden layers that contained 13 neurons in the first layer and 25 neurons in the second layer and reached a mean bias error (MBE) of 0.06. The coefficient of determination (R²), index of agreement (IA), and the Nash–Scutcliffe efficiency (E) between the observed and predicted data using the MLP neural network were 0.96, 0.9057, and 0.957, respectively. The RBF neural network with a hidden layer containing 130 neurons reached an MBE of 0.04. The R², IA, and E between the observed and predicted data using the RBF neural network were 0.981, 0.954, and 0.979, respectively. The results provided by the RBF neural network had greater acceptable accuracy than was the case with the MLP neural network. Finally, the results of a sensitivity analysis using the MLP neural network indicated that temperature is the primary factor in the prediction of CO concentrations and that wind speed and humidity are factors of second and third importance when forecasting CO levels.     

Concentration and characterization of airborne particles in Tehran’s subway system

Particulate matter is an important air pollutant, especially in closed environments like underground subway stations. In this study, a total of 13 elements were determined from PM₁₀ and PM_2.5 samples collected at two subway stations (Imam Khomeini and Sadeghiye) in Tehran’s subway system. Sampling was conducted in April to August 2011 to measure PM concentrations in platform and adjacent outdoor air of the stations. In the Imam Khomeini station, the average concentrations of PM₁₀ and PM_2.5 were 94.4?±?26.3 and 52.3?±?16.5 μg m^?3 in the platform and 81.8?±?22.2 and 35?±?17.6 μg m^?3 in the outdoor air, respectively. In the Sadeghiye station, mean concentrations of PM₁₀ and PM_2.5 were 87.6?±?23 and 41.3?±?20.4 μg m^?3 in the platform and 73.9?±?17.3 and 30?±?15 μg m^?3, in the outdoor air, respectively. The relative contribution of elemental components in each particle fraction were accounted for 43 % (PM₁₀) and 47.7 % (PM_2.5) in platform of Imam Khomeini station and 15.9 % (PM₁₀) and 18.5 % (PM_2.5) in the outdoor air of this station. Also, at the Sadeghiye station, each fraction accounted for 31.6 % (PM₁₀) and 39.8 % (PM_2.5) in platform and was 11.7 % (PM₁₀) and 14.3 % (PM_2.5) in the outdoor. At the Imam Khomeini station, Fe was the predominant element to represent 32.4 and 36 % of the total mass of PM₁₀ and PM_2.5 in the platform and 11.5 and 13.3 % in the outdoor, respectively. At the Sadeghiye station, this element represented 22.7 and 29.8 % of total mass of PM₁₀ and PM_2.5 in the platform and 8.7 and 10.5 % in the outdoor air, respectively. Other major crustal elements were 5.8 % (PM₁₀) and 5.3 % (PM_2.5) in the Imam Khomeini station platform and 2.3 and 2.4 % in the outdoor air, respectively. The proportion of other minor elements was significantly lower, actually less than 7 % in total samples, and V was the minor concentration in total mass of PM₁₀ and PM_2.5 in both platform stations.     

Migration of VOC Plume in the Subsurface Domain at the Y‐12 National Security Site

During the production of thermonuclear fusion weapons at the Y‐12 National Security Complex (Y‐12 NSC) in Oak Ridge, Tennessee, between 1950 and 1963, the regional environment was extensively contaminated by volatile organic compounds (VOCs). Old Salvage Yard (OSY) on the western side of the site has been characterized as the major source of VOCs. In order to analyze the long‐term fate and transport of chlorinated VOC sources, an integrated surface and subsurface flow and transport model was developed for the Y‐12 NSC using the hydrodynamic and transport numerical package MIKE‐SHE. The model was developed considering the recent hydrogeological investigations on preferential flow and transport pathways at the site. The model was calibrated using the recorded groundwater flow and water‐quality data. The modeling simulated migration of the VOC plume for the next 100 years. Considering a range of hydrogeological and transport parameters, uncertainty of the results is discussed. The modeling predicted that tetrachloroethene, trichloroethene, and 1,2‐dichloroethene may exceed human health–related risk levels for the next 10 to 20 years. However, the contamination is unlikely to migrate to surface water under the current hydrogeological conditions and will decay below acceptable risk levels within approximately 20 years. © 2013 Wiley Periodicals, Inc.     

Determination trace amounts of copper, nickel, cobalt and manganese ions in water samples after simultaneous separation and preconcentration

In the present article, a simple, rapid, sensitive and economical method has been developed for the simultaneous separation and preconcentration of the trace amounts of copper, nickel, cobalt and manganese in water samples by using modified XAD-4 resins. The sorption was quantitative in the pH range 6.0–9.0, whereas quantitative desorption occurred instantaneously with 5.0 mL of 2 M HNO₃, and selected elements have been determined by using flame atomic absorption spectrometry. Dynamic ranges were 0.04–3.5, 0.1–6.0, 0.04–4.5 and 0.04–4.0 μg/mL for copper, nickel, cobalt and manganese, respectively. The detection limits were 9.2, 28.6, 12.3 and 5.7 ng/mL for Cu(II), Ni(II), Co(II) and Mn(II), respectively. The effects of the experimental parameters, including the sample pH, eluent type, interference ions and breakthrough volume, were studied for separation and preconcentration of Cu(II), Ni(II), Co(II) and Mn(II) ions. Determination of these ions in standard samples confirmed that the proposed method has good accuracy. The proposed method was used for the determination of these ions in water samples.     

Aminobenzenesulfonamide functionalized SBA-15 nanoporous molecular sieve: A new and promising adsorbent for preconcentration of lead and copper ions

A rapid method for the extraction and monitoring of nanogram level of Pb²⁺ and Cu²⁺ ions using uniform silanized mesopor (SBA-15) functionalized with aminobenzenesulfonamide groups and flame atomic absorption spectrometry (FAAS) is presented. Aminobenzenesulfonamide functionalized SBA-15 was synthesized according to procedure in the literature and the presence of organic groups in the silica framework was demonstrated by FT-IR spectra. The functionalized product showed the BET surface area 110 m²/g and pore diameter 5.1 nm, based on adsorption-desorption of N₂ at 77 K. The effect of several variables such as (amount of adsorbent, stirring time, pH and presence of other ions in the medium) has been studied. Lead and copper were completely extracted at pH greater than 3 after stirring for 10 min. The maximum capacity of the adsorbent was found to be 191.3 ± 1.4 and 155.0 ± 1.0 μg of lead and copper ions/mg functionalized SBA-15, respectively. The preconcentration factor of the method was found to be 200. The detection limit of the technique was 3.4 and 0.4 ng/mL for Pb²⁺ and Cu²⁺, respectively. The applications of this methodology for real samples were examined by various water type, black tea and pepper samples.     

Design and optimization of a hybrid process based on hollow-fiber membrane/coagulation for wastewater treatment

Environmental Science and Pollution Research - Treatment of textile wastewater using ultrafiltration membranes was carried out in this study. Since membrane fouling is a major operational problem...