Biodegradation of polycyclic aromatic hydrocarbons, toxic compounds widely distributed in the environment by bacteria, is a cheap and safe cleaning up method. The present study attempts to isolate and characterize dioxygenase-producing bacteria which are able to degrade phenanthrene and pyrene from refinery soils. It also aims to assess in vitro biodegradation. To do so, two contaminated soil samples were collected from Isfahan-Iran refinery. The population of phenanthrene and pyrene degrading bacteria were 2.17 × 103 and 1.19 × 103 CFU/g in sample 1 and  21.50 × 103 and 19.40 × 103 CFU/g in sample 2. A sum of 18 phenanthrene and pyrene degrading bacteria were isolated using enrichment culture technique, three of them getting selected which had dioxygenase activity and produced biosurfactant. Identified as Pseudomonas plecoglossicida ATAI18, Pseudomonas aeruginosa ATAI19, and Pseudomonas stutzeri ATAI21, they were submitted to GenBank under the accession number of KF113842, KF113843, and KF113845 respectively. The degradation rate of pyrene (50 mg/L) by strains ATAI18 and ATAI19 was 45.32% and 31.23%, respectively. The strain ATAI21 degraded 39.38% of phenanthrene (50 mg/L) after 9 days. These isolated bacteria can be used to improve microbial population of other hydrocarbon-polluted soils for faster bioremediation of such areas.

The present study has been conducted on Caspian Roach (Rutilus rutilus) so that the impact of different concentrations lead on blood hematological, biochemical, and immunological indicators could be investigated. The roach (Rutilus rutilus), used in this study, was 3.3±0.3 g heavy and 4±0.80 cm long in average. The fish were exposed to a low concentration of 10% LC50 and high concentration of 50% LC50 lead for a period of 0, 24, 48, and 96 h. The experiment was done in a static toxicity condition, within tanks of 400L, each including 14 fish. In the 96-hour period (10% LC50 Lead), the parameters of WBC and RBC dropped significantly in comparison to the control group (0 h) (P<0.05). MCV and MCH elevated as the exposure time ascended up to 96 h (P<0.05), but the cortisol decreased in the meantime. In the 96-hour period (50% LC50 Lead) RBC, Hb and Hct parameters plummeted towards the control group (P<0.05). Heavy metals can change physiological and biochemical parameters in fish blood. The results show that lead (10% LC50 and 50% LC50 concentration Lead) may poison the fish, causing their death. The major toxicity belongs to the 50% LC50 concentration Lead.

The present paper measures natural radioactivity in different areas of Wassit governorate, using (HPGe) detector. Gamma spectrum analysis for each sample along with caululated specific activity show that the average concentrations of U-238, Th-232, and K-40 have been 19.420±4.7 Bq/kg, 18.487±5.05 Bq/kg, and 204.266±46.9 Bq/kg respectively, which is lower than the worldwide average value. While the average value of Radium equivalent, absorbed dose, indoor and outdoor annual effective dose, activity index, and internal and external hazard index for each sample have been found to be 85.182 Bq/kg, 39.962 nGy/h, 0.196 mSv/y, 0.049 mSv/y, 0.374, 0.313, 0.309, and 0.230 respectively, all of them are lower than the permissibility limit value.

Nitrate pollutants increase the growth of algal bloom, resulting in fresh water eutrophication. The high nitrogen level in wastewater has become a growing concern, which has risen the necessity to develop efficient nitrogen removal techniques. Biological denitrification, which is the reduction of oxidized nitrogen compounds like nitrate or nitrite to gaseous nitrogen compounds, is the most important and widely used method to treat nitrate wastes as it enables the transformation of nitrogen compounds into harmless nitrogen gas. As such, this study collected samples from Eutrophic Lake, picking isolates of bacterial strain with good growth rates in the nitrate medium. The selected bacterial strains were cultured on media 1and 2 and by means of UV-visible spectrophotometer, the nitrate removal efficiency and growth were detected at 410 nm and 600 nm OD respectively. After comparing three bacterial strains, it was found that RN1 had a higher efficiency in nitrate removal at 1000ppm nitrate concentration. At an optimum temperature of 37°C, pH of 7, and agitation of 121 rpm, after 432 hrs of the treatment, RN1 showed an optimum growth, equal to 0.1859 OD in 1000ppm nitrate solution with dextrose. Also the spectral analysis of RN1 strain showed 85% removal efficiency, thus making this strain the best one. Confirmed and identified as Bacillus species, it can be recommended for the bioremoval process of nitrate from wastewater.

Kumasi, Sekondi-Takoradi, and Accra are the major recipients of agricultural commodities or productions in Ghana, primarily due to their population and ready markets. To ensure food security, meet food demands, and mitigate the threats posed by pests and diseases, pesticides are used when cultivating vegetables and fruits in Ghana. The present study has been conducted to assess the concentration of various pesticide residues in tomatoes, obtained from three market centers (namely Bantama, Central, and Ayigya Markets) in Kumasi, dealing with potential health risks for the consumers. Analyzed samples have revealed high percentage of organophosphorous pesticide residues (45%) in Ayigya market with Bantama market recording high percentage of organochlorines and pyrethroid. Laboratory analysis of tomato samples for various pesticides residues has indicated that all the pesticide residues pose no threat to human’s health with all estimated hazard indices being below 1; however, heptachlor (HI=0.85) and dieldrin (HI=0.74) have shown the highest risk levels in children. The study reveals that there is some need for strict monitoring of heptachlor and dieldrin in tomato, especially in case of children.

Transportation is an important part of modern community life as well as one of the largest sources of greenhouse gas emissions in urban communities, the population growth of which can increase transportation capacity. Monorail systems are relatively new rail transportation systems which are currently being designed and constructed in different countries. We have applied the Intergovernmental Panel on Climate Change (IPCC) to deal with global warming and Center of Environmental Science of Leiden University (Centrum voor Milieukunde Leiden), CML 2001, to evaluate the potential of acid raining. In order to analyze both mentioned methods, Sima Pro7.1 has been used. Initially the research-related data have been prepared from Qom Monorail workplace. Moreover the sensitivity analysis has been performed on the results, which indicated that the potential of causing global warming in the construction phase for a period of 100 years was equal to 26875.07 kg CO2eq. /km. person. The reinforcement bar with 32%, concrete with 30%, and diesel fuel with 15% enjoyed the lion’s share in terms of global warming creation. The likelihood of acid raining formation was equal to 101.876 kg SO2eq. /km. person. Diesel fuel contributed the most portion to the formation of acid raining (31%) with reinforcement bar and concrete in the second (30%) and third (13%) places. For result validation, the BEES (Building for Environmental and Economic Sustainability) software has applied with the sensitivity analysis, indicating that the first and second effective parameters on the results were the amount of reinforcement bar and diesel fuel. Hence, reduction of reinforcement bars, concrete, and diesel (respectively) have the most influence on mitigation of global warming and acid raining effects of Qom monorail project.

Water scarcity, its necessity in food production, and environmental protection in the world have forced human beings to seek new water sources. Nowadays, application of unconventional water resources (wastewater) has been proposed in countries facing the crisis of water resources shortage; however, a few studies have dealt with this issue. The present study has evaluated the changes in the elements of the soil, irrigated with wastewater. For so doing, an experiment has been conducted on a randomized complete block design with three replications. Soil samples have been collected from the studied regions at two depths of 0-30 cm and 30-60 cm and the studied parameters have included sodium, total calcium, magnesium, some acidity, and electrical conductivity of the soil. Three regions of study (namely no irrigation, irrigation with treated wastewater, and irrigation with river waters) have been taken into consideration. Results have shown increased calcium, magnesium, and pH of the effluent from Zabol Wastewater Treatment Plant compared to the control; however, electrical conductivity and chloride have decreased in wastewater-irrigated soil. The electrical conductivity in the surface layer of wastewater samples, treated with an amount of 2.25 (ds/m), has had the most significant difference to the control and other treatments. It can be concluded that wastewater increases some soil properties, contributing to its restoration.

During the last decade, the expansion of urbanization and industrial activities caused serious environmental problems such as soil pollution. Novel technologies are required to remediate soil contamination with toxic contaminants, including heavy metals and organic pollutants. In recent years, there have been increasing attempts to improve soil remediation efficiency. Electrokinetic (EK) is an emerging remediation technology for mixed contaminants, especially in low hydraulic conductivity soils. During EK remediation process, an electric field is applied to the specimen to remove the contaminants from soil by means of electro-osmotic (EO), electro-migration (EM), and electrophoresis (EP) processes. The usual EK technique may have no suitable removal efficiency or contaminants migration. Thus, enhancement techniques or their combination with other technologies are required to overcome EK limitations, increasing its efficiency. The present study reviews seven main enhancement techniques combined with EK; they include using surfactant, chelants, complexing agents, soil pH control, bioremediation, permeable reactive barriers, and ultrasonication. It should be mentioned that, selecting the suitable combination technique highly depends on the soil type and the kind of contaminant.

Precipitation patterns are influenced by many factors, such as global atmospheric circulations to name but one. Precipitation patterns in Iran have always had great fluctuations even in a smaller scale like the Alburz Mountain Range. The present research has tried to find the relationship between global atmospheric patterns and the pervasive precipitation ones in Alburz. For doing so, 17 climate indices have been chosen with the correlation between these indices and the precipitation data calculated in different lag times, using a backward correlation method (from the present time to 3 months earlier). Based on the obtained correlation results, a regression modeling has been conducted that employs a backward method. As for each lag time, one equation has been offered to estimate the amount of precipitation for every single region. Results have shown that the Bivariate ENSO Time Series (BEST) and the East Pacific Oscillation (EPO) provide the highest correlation with the pervasive precipitation time series. Also, it has been demonstrated that in multivariate correlation, the efficient index to model the relation among these indices as well as precipitation in southern Alburz alters in each lag time. Both MBE and RMSE, employed to evaluate the modeling, show relatively acceptable values, implying that the equations are acceptably capable of predicting the amount of precipitation in both northern and southern Alburz.

One of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. In this regard, there have many models developed, proposing better management in order to maintain water quality. Most of these models require input parameters that are either hardly available or time-consuming and expensive to measure. Among them, the Artificial Neural Network (ANN) Models, inspired from human brain, are a better choice. The present study has simulated the groundwater quality parameters of Ramhormoz Plain, including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), and Total Dissolved Solids (TDS), via ANN and ANN+ Particle Swarm Optimization (PSO) Models and at the end has compared their results with the measured data. The input data for TDS quality parameter is consisted of EC, SAR, pH, SO4, Ca, Mg, and Na, while for SAR, it includes TDS, pH, Na, and Hco3, and as for EC, it involves So4, Ca, Mg, SAR, and pH; all of them, gathered from 2009 to 2015. Results indicate that the highest prediction accuracy for SAR, EC, and TDS is related to the ANN + PSO model with the tangent sigmoid activation function so that both MAE and RMSE statistics have the minimum and R2 the maximum value for the model. Also the highest prediction accuracy is respectively related to EC, TDS, and SAR parameters. Considering the high efficiency of artificial neural network model, by training the PSO algorithm, it can be used in order to make managerial decisions and ensure monitoring and cost reduction results.