Health risk assessment of mercury and arsenic associated with consumption of fish from the Persian Gulf

Concentrations of mercury and arsenic in fish from the Persian Gulf were determined by graphite furnace atomic absorption spectrometry. Concentrations of the metals in muscle samples were 0.049–0.402 μg g^?1 for mercury and 0.168–0.479 μg g^?1 for arsenic, with means of 0.133 and 0.312 μg g^?1, respectively. The maximum daily consumption rate (grams per day) and meal consumption limit (meals per month) was calculated to estimate health risks associated with fish consumption. According to the results, the maximum allowable consumption rate varies between 8–56 and 15–96 g/day base on mercury and arsenic content, respectively. The results of this study indicate that the concentration of mercury and arsenic is well below the maximum permissible levels for mercury (0.5 μg g^?1) and arsenic (6 μg g^?1) according to international standards.     

The effect of size and sex on PCB and PAH concentrations in crab Portunus pelagicus

Polychlorinated biphenyl and polycyclic aromatic hydrocarbon concentrations in the hepatopancreas of blue swimming crab (Portunus pelagicus) from the north Persian Gulf were measured. In addition, the relationships between crab size (carapace width) and polychlorinated biphenyl (PCB) and polycyclic aromatic hydrocarbon (PAH) levels in hepatopancreas were investigated by linear regression analysis. Among the PCBs, congeners 110 and 153 were the most frequent and abundant. The results showed that, except in a few cases, significant relationships between PCB and PAH levels and crab size were positive. Comparison between male and female indicated that the average PCB16, 44, 153, and acenaphthylene, acenaphthene, and anthracene concentrations in hepatopancreas of male crab were found to be significantly higher than those found in the female crab.     

Optimized processing power and trainability of neural network in numerical modeling of Al Matrix nano composites

In this research, an experimental study of reinforcing alumina nano-particles into the aluminum alloy matrix was implemented to verify the accuracy of modeling results obtained by feed forward neural networks. Artificial neural network combined with numerical technique were used to predict the various parameters of mechanical properties such as hardness, tensile and compressive yield stress, UTS and elongation percentage. Much experimentation were taken to discover a suitable number of hidden neurons, avoid detraction from the trainability and enable feed forward neural networks to solve more complex problems. The predictions were found to be consistent with experimental measurements.     

Rapid photodegradation and detection of zolpidem over β-SnWO4 and α-SnWO4 nanoparticles: optimization and mechanism

Environmental Science and Pollution Research - We reported the tin (II) tungstate nanoparticles as the photocatalyst and sensor modifier that were synthesized via chemical precipitation reaction...     

Propagation and extinction of dust flames in narrow channels

This article has investigated the propagation and extinction of aluminum dust cloud flame in a narrow channel. The burned and burning dust particles act as heat sources and the channel walls act as heat sinks. In this method, discrete heat source has been used to analyze dust combustion in a narrow channel. Using the superposition of sources and sinks, the preheat zone temperature is predicted as an indicator of flame propagation or extinction. Dust concentration and channel width are two major parameters which affect the quenching distance and flame propagating speed. Wall temperature affects the heat loss; and by preheating the walls, quenching distance is reduced and flame propagation speed is increased.     

Benzene removal by nano magnetic particles under continuous condition from aqueous solutions

Benzene removal evaluated using Fe304 nano continuous condition. A 44 initial benzene concentration, from aqueous solutions was magnetic particles （NM） in factorial design including NM dose, contact time and pH was investigated in 16 experiments （Taguchi OA design）. The results indicated that all factors were significant and the optimum condition was： pH 8, NM dose of 2000 mg.L-1, benzene concentrations of 100 mg.L-1 and contact time of 14min. The maximum benzene uptake and distribution ratio in the optimum situation were 49.4mg.g-1 and 38.4L.g-1, respectively. The nano particles were shown to capture 98.7% of the benzene in optimum batch condition and 94.5% in continuous condition. The isotherm data proved that the Bmnauer-Emmett-Teller model fit more closely and produced an isotherm constant （b） less than one, indicating favorable adsorption. Regeneration studies verified that the benzene adsorbed by the NM could be easily desorbed by temperature, and thereby, NM can be employed repeatedly in water and wastewater management.     

Cadmium removal from Cd-contaminated soils using some natural and synthetic chelates for enhancing phytoextraction

The influence of a natural (citric acid) and two synthetic chelates (HEDTA, EGTA) on Cd phytoextraction with radish was studied. The experiment was conducted with Cd treatments including 0 (control), 5, 20, 60 and 100?mg?Cd?kg^?1 soil. When plants were fully developed, the designated HEDTA, EGTA and citric acid were applied to establish experimental treatments. Ten days after chelate applications, soil and plant samples were taken. Results indicated that synthetic chelates can considerably increase Cd concentration in soil solution compared with citric acid. Among the applied chelates, HEDTA provided more significant influences on soil solution. Cadmium concentration in both shoots and roots of radish was increased due to enhancing influence of chelate applications on Cd concentration in soil solution. Cadmium concentration in radish shoots was more than that of roots. This can be attributed to higher bioavailability and solubility of Cd in soil solution. In all treatments which received HEDTA, the cadmium concentration in both shoots and roots of radish was increased more than that of other applied chelates. Although HEDTA is more efficient in phytoextracting Cd than other chelates, due to durability of synthetic chelates toxic effects on soils, we recommend using larger amounts of light acids.     

Investigation on diazinon and oxydemeton-methyl residues in cucumbers grown in Kerman greenhouses

Pesticides are considered as the most polluting substances. The residue of pesticides in agricultural crops, especially in greenhouse harvests, has been reported critical. Cucumber, considered as a vegetable, is an agricultural product which is commonly found in the Iranian food basket. The current study aims to assess the level of diazinon and oxydemeton-methyl existing in cucumbers sampled from Kerman greenhouses. The pesticide residue was extracted by acetone and dichloromethane. The extracts were cleaned up according to the solid-phase extraction method. The pesticide residues were then determined by capillary gas chromatography with nitrogen-phosphorus detection. The recoveries were 83 and 85 %, the limit of detection was 0.028 and 0.034 mg/kg, and the limits of qualification were 0.093 and 0.113 mg/kg for diazinon and oxydemeton-methyl in cucumber samples, respectively. The median of diazinon residue was detected 0.582 mg/kg, which was 11.64 times the national maximum residue limit (MRL) (0.05 mg/kg), and the median for oxydemeton-methyl was 1.910 mg/kg, being 1.91 times the MRL (1 mg/kg).     

Mathematical Model for Pollution Source Identification in Rivers

Release of pollution into rivers is required to be handled with special consideration to environmental standards. For this purpose, it is essential to specify the contribution of each pollution source in contamination of water resources. In this study, a mathematical model is proposed for determining locations and concentration release histories of polluting point sources using measured downstream river concentrations via an inverse problem framework. The inverse solution is based on the integral equation obtained from applying the Green's function method on the one-dimensional advection-dispersion contaminant transport equation. Discretization of this integral equation results in a linear, over-determined and ill-posed system of algebraic equations that are solved by using the Tikhonov regularization method. Several examples and some real field data are investigated to illustrate the abilities of the proposed model. Results imply that the proposed method is effective and can identify the pollution sources in rivers with acceptable accuracy.