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...     

Analyzing material flow in Alborz industrial estate,Ghazvin, Iran

Journal of Material Cycles and Waste Management - Industrial ecology and models such as material flow analysis make operational approaches in order to reuse produced waste as primary resources in...     

Accumulation and elimination of cadmium and lead in juvenile milkfish during sublethal exposure

Pollution of aquatic environments by trace metals is a worldwide environmental problem. Metal pollutants are increasingly being released into the environment as a result of industrialization. In this study, the bioaccumulation of cadmium and lead in young juvenile milkfish liver (Chanos chanos) was investigated after exposure to three sublethal concentration of each pollutants (1/20, 1/10, and 1/5 LC₅₀ of 96-h LC₅₀) for acute time 12, 24, and 96 h and subchronically for 7, 14, and 21 days. Cadmium and lead accumulation in liver increased with the exposure period and concentrations of pollutant. Compared to controls, the uptake of cadmium is much higher than that of lead. Accumulation factors showed an increase with exposure time and for lead an inverse relationship between accumulation factor and exposure concentration. The elimination of the two pollutants during the 30 days depuration was investigated after 30 days depuration time. During this phase, cadmium and lead concentrations decreased.     

Distribution,geochemistry, and mineralogy of aerosols in the Angouran Mine area,northwest Iran

The Angouran Mine, located in northwest Iran, is the largest Zn–Pb producer in the Middle East. This study was designed to investigate the distribution, geochemistry, and mineralogy of the aerosols in the mining area and to assess their likely health impacts on the local residents. For this purpose, 36 aerosol samples were collected from 2014 to 2015 at nine sites located in mine district and upwind and downwind directions. The concentration of potentially toxic elements in the aerosols was determined using AAS instrument. Size, morphology, and mineralogy of the particles were studied using SEM and EDX spectra. The results indicate that the amount of total suspended particles in upwind, mine district, and downwind sites is 95.5, 463.4 and 287.5 µg/m³, respectively. The concentrations of PM_2.5 in the three locations are 8.9, 134.7, and 51.8 µg/m³, whereas the PM₁₀ contents are 2.9, 74.4, and 15.5 µg/m³, respectively. These observations point to the impact of mining activities on the concentration of aerosols in the local atmosphere. The values of air quality index also show the probable effects of the mining activities on the health of the local populations, especially for allergic peoples. The average concentration of Zn in the samples collected from the mining district (290 µg/kg) is much higher than its value in the upwind sites (27 µg/kg). The highest concentration of As (70 µg/kg), Cd (10 µg/kg), and Pb (3 µg/kg) is in downwind sites, which shows the negative impact of mining activities on the local air quality. Temporally, the highest concentration of the studied elements is recorded in spring season, especially for PM_2.5 collected in downwind stations. Based on the results of SEM and EDX spectra, three groups of minerals, i.e., carbonates, silicates, and sulfides, are present in the aerosol particles, confirming the local source for the aerosols. SEM analyses showed that the aerosol particles with dissimilar chemical composition have different morphologies such as irregular, rounded, elongated, and angular. On the basis of the results, the mining activities in the Angouran Zn–Pb Mine may have various short- and long-term consequences on the public health, especially due to high amount of the finer particles (PM_2.5) and the higher concentration of the potentially toxic elements in PM_2.5 which can penetrate into the lungs.

     

Indigenous knowledge about climate change and sustainability of nomadic livelihoods: understanding adaptability coping strategies

Environment, Development and Sustainability - Indigenous knowledge about climate change that makes adaptability necessary by coping strategies leads to the sustainability of nomadic livelihoods....     

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.     

Assessment of temporal and spatial water quality in international Gomishan Lagoon,Iran, using multivariate analysis

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO₂), nitrate (NO₃), biological oxygen demand (BOD), phosphate (PO₄), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R², RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.     

The <Emphasis Type="Italic">AhRR</Emphasis>-c.565C&gt;G transversion may increase total antioxidant capacity levels of the seminal plasma in infertile men

The Aryl hydrocarbon receptor (AhR)-repressor (AhRR) is a regulator of the AhR pathway, which plays an important role in xenobiotic and reactive oxygen species (ROS) metabolism. Total antioxidant capacity (TAC) is a major factor in semen quality that protects sperm against ROS stress. Malondialdehyde (MDA) is the indicator of lipid peroxidation damage that is occurred due to ROSs. In this study, we determined and compared the MDA and TAC levels of infertile men’s semen and blood plasma regarding genotype groups of AhRR-c.565C>G transversion. Semen and blood samples of 123 infertile males were collected from the Fatemeh Zahra IVF Centre, Babol, Iran. TAC and MDA levels of seminal and blood plasma were measured by TBARS and FRAP methods, respectively. Cases were genotyped by the PCR-RFLP method. The frequency of c.565C>G genotypes was determined as CC (34.14%), CG (55.28%) and GG (10.58%). Mean levels of TAC μm/L and MDA nmol/mL in semen plasma of CC, CG and GG groups were (1365.7, 1.28), (1542.8, 1.51) and (1860.2, 0.82), respectively. Also, mean levels of TAC μm/L and MDA nmol/mL in blood plasma samples in CC, CG and GG genotypes were (806.14, 1.168), (727.1, 1.006) and (635.7, 0.83), respectively. Comparison of marker levels between genotypes revealed that the TAC level of semen plasma in the GG genotype was significantly higher than its level in the CC group (p < 0.05). Our findings showed that in seminal plasma of infertile men with the GG genotype of AhRR-c.565C>G transversion, the level of total antioxidant capacity is significantly higher in comparison with the CC genotype. Then, the G allele of AhRR-c.565C>G transversion may have a role in the increase in antioxidant capacity of seminal plasma.     

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.