Journal of Research in Environmental Health
Year:2023 | Volume:9 | Issue:1|Papers Count:8

Background and purpose: Industrial development, on one hand, creates harmful chemical products and industrial waste, including heavy metals. On the other hand, it increases energy consumption and leads to the release of atmospheric pollutants, causing environmental pollution. Bandar Abbas, compared to other areas of Hormozgan province, has a high concentration of industries. Therefore, it is necessary to study the pollution caused by these industries in the region's environment. The general purpose of this study is to investigate the amount of heavy metals associated with industrial activity. mirzahosseini@gmail. com. Nabiulah Mansouri Professor, Department of Environmental Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran. Received: 2022/11/11 Accepted: 2023/02/04 Document Type: Research article Materials and Methods: Ambient air sampling was conducted at seven locations in the region during winter and spring (2020). The sampling and preparation methods were based on EPA and NIOSH Standards. Sampling was performed using a High-Volume pump with a flow rate of 1. 7 cubic meters per minute for a duration of 24 hours. The sampling device was installed at a height of 3 meters above the ground. The heavy metals in the collected samples were measured using the Varian Z220 atomic absorption spectrometer with the furnace technique. Circular fiberglass filters with a diameter of 47 mm were used for environmental sampling. Results: Based on the analysis of air particles, the concentration of heavy metals showed a decreasing trend as follows: V < Cd < Fe < Pb. The average concentrations of these elements were 0. 0006, 0. 0060, 0. 0061, and 0. 339 micrograms per cubic meter, respectively. With the exception of lead, the average concentration of these metals exceeded the limit value. Conclusion: The amount of suspended particles at all sampling locations exceeded the environmental standards. Additionally, except for vanadium, the average concentration of metals in the samples from residential areas was below the limit value.

Background and purpose: Removing pharmaceutical substances from wastewater is essential due to their high stability and toxic effects on humans and other living organisms before they enter the environment. Green-synthesized nanocomposites possess significant abilities to degrade pharmaceutical compounds and exhibit antibacterial effects. Therefore, this study aimed to investigate the photocatalytic and antibacterial effects of a green-synthesized magnetic nanocomposite. Materials and Methods: In this experimental study, the photocatalytic process was conducted on a solution containing tetracycline to examine the photocatalytic capabilities of the synthesized nanocomposite. The antibacterial effect of the nanocomposite was also assessed on Gram-negative and Gram-positive bacteria using the broth dilution method. Results: The results of the tetracycline antibiotic photocatalytic degradation test showed a removal rate of 87. 95% under the following conditions: pH = 7, nanocomposite dose = 0. 26 g/L, contact time = 54 min, and initial TC concentration of 10 mg/L. The minimum inhibitory concentration (MIC) of the synthesized nanocomposite was determined to be 1. 25 mg/mL for Staphylococcus aureus bacteria and 5 mg/mL for Escherichia coli and Klebsiella bacteria. The minimum bactericidal concentration (MBC) against Escherichia coli and Staphylococcus aureus bacteria was found to be 5 mg/mL. Conclusion: In addition to the inhibitory and bactericidal capabilities of the manganese-ferrite-based nanocomposite, it can be utilized as a powerful catalyst for the degradation of tetracycline antibiotics in aqueous solutions.

Background and purpose: Considering the role of hydrocarbon pollution in cancer, this research aims to investigate the degradation rate of benzene and toluene using bacteria extracted from soil, as well as to examine the compounds resulting from this decomposition. Materials and Methods: Thirty soil samples, including agricultural soil and soil contaminated with hydrocarbons, were collected from the northwestern provinces of Iran. Bacteria were cultured in agar medium and subsequently extracted. To assess the decomposition of benzene and toluene, bacteria were separately cultured in a mineral culture medium containing a specific amount of benzene or toluene, and the percentage of decomposition was determined. Additionally, GC-Mass analysis was conducted to identify the compounds resulting from the decomposition of benzene and toluene. The type of bacteria responsible for the degradation was determined using biochemical methods and PCR. Results: All the extracted bacteria exhibited the ability to decompose benzene and toluene, with the highest decomposition rates observed in bacteria extracted from refinery soil, averaging 55. 85% for benzene and 49. 39% for toluene. Agricultural and refinery soil bacteria displayed a higher decomposition rate for benzene compared to toluene. The majority of the compounds obtained from the decomposition had lower toxicity than benzene and toluene. Furthermore, the presence of the Streptomyces strain was confirmed in environments with the highest decomposition rates for benzene and toluene. Conclusion: Streptomyces strains indigenous to soils contaminated with hydrocarbons demonstrated a high efficiency in converting benzene and toluene into organic compounds, reducing the associated risks.

Background and purpose: The Zayandeh-Rud River is the sole permanent river in the central plateau of Iran. This river has been extensively exposed to sewage and effluent discharge from various point and non-point sources of pollution. Consequently, the sediment quality of the Zayandeh-Rud River was investigated. Materials and Methods: Sediment sampling was conducted in triplicates at six stations along the Zayandeh-Rud River during the spring, summer, autumn, and winter of 2019-2020. The concentrations of lead and cadmium were then determined. Subsequently, the bioaccumulation factor, Mü, ller's geochemical index, contamination factor, contamination degree, modified contamination degree, potential ecological risk index, and pollution load index were calculated. Results: The results indicated that the mean concentrations of cadmium in spring, summer, autumn, and winter were 1. 18, 1. 13, 1. 08, and 0. 54 mg/kg, respectively. Additionally, the mean concentration of lead was 26. 13, 23. 04, 23. 96, and 11. 17 mg/kg, respectively. The ecological risk assessment index revealed that the region was at a moderate ecological risk during spring, summer, and autumn, while during winter, it was at a low ecological risk. Conclusion: A comparison between the mean metal concentrations and the Canadian sediment quality standard values for fresh waters demonstrated that the lead concentration in sediments is lower than the standard value, whereas cadmium exceeds the standard value. These results highlight the pollution status of the river, which is the primary source of freshwater in the central plateau of Iran. Moreover, this study can serve as a basis for implementing policies to mitigate the accumulation of heavy metals in aquatic ecosystems.

Background and purpose: Diazinon is an organophosphorus insecticide that is widely used in paddy fields and gardens. The entry of resistant pollutants into drinking water sources, soil, and agricultural products can be harmful to human health and the environment. This study aimed to identify and isolate diazinondegrading bacteria and measure the amount of poison decomposed by superior bacteria in liquid and soil environments. Materials and Methods: Sampling was conducted from Tonekabon gardens. The strains were identified and sequenced using polymerase chain reaction based on 16S rRNA. The rate of diazinon degradation by the isolated bacteria was measured by gas chromatography. Results: Two strains of diazinon-degrading bacteria, Serratia and Enterobacter cloacae, were identified. Bacteria with diazinon concentrations of 10 and 20 ppm were cultured in broth and soil for 10 days, and the amount of poison decomposition was measured. The results indicated that Serratia bacteria in the broth medium, with initial concentrations of 10 and 20 ppm, consumed 64. 3% and 78. 4% of diazinon, respectively, while in the soil with the same concentration, it decomposed 90. 2% and 98. 25% of diazinon. Enterobacter cloacae bacteria consumed and decomposed diazinon in the broth and soil environments, with percentages of 23. 1, 17. 95, 31. 19, and 88. 05%, respectively. According to the results, Serratia has a higher decomposition ability compared to Enterobacter. Conclusion: The results of this research showed that some microorganisms in the soil have the ability to decompose diazinon. Utilizing these microorganisms and other biological methods to clean contaminated soils can be a suitable approach.

Background and purpose: The biological pollution of landfill sites for urban waste is a crucial concern. This study aims to investigate the resistance of bacteria in contaminated soils at waste burial sites against heavy metals in Hamadan. Materials and Methods: The physical and chemical characteristics of soils were examined, and the total amounts of metals such as copper, lead, zinc, and cadmium were measured. Additionally, pollution load index (PLI), average pollution index (PIavg), and pollution degree (Cdeg) were estimated and analyzed. Furthermore, the percentage of stable bacteria resistant to copper, lead, cadmium, and zinc in the NA culture medium was studied by measuring the logarithm of microorganism abundance. Results: Among the mentioned sites, the soil surrounding the leachate lagoon exhibited the highest levels of organic carbon, available phosphorus, and potassium. The PLI and PIavg indices for virgin soil were below one, indicating that this soil was not polluted. However, these indices were above one for the other five sites, indicating pollution. The intensity of soil pollution in these sites exceeded the permissible limit. The logarithm of population for fungi, actinomycetes, pseudomonas, and enterobacters was highest in the new rubbish landfill, with values of 5. 35, 5. 28, 6. 13, and 5. 98, respectively. The percentage of bacteria resistant to lead was 100% in all sampled soils, but in the leachate, it was lower than 64%. Conclusion: Overall, the percentages of bacteria resistant to copper, zinc, and cadmium in the new rubbish landfill site were higher compared to other sites, which may be attributed to the landfilling of urban waste in the soil.

Background and purpose: The study aims to examine the risks associated with waste landfill projects during the operational phase, with a focus on improving performance and reducing resulting injuries. Conducting environmental risk assessment studies is essential to better comprehend the hazardous criteria and their impact on the environment, as well as to propose effective solutions for control and management. As the central city of Gilan, Rasht receives over 750 tons of waste daily at the Saravan landfill. Materials and Methods: This research utilizes Delphi techniques, network analysis process (ANP), and TOPSIS to prioritize and rank the most significant risks in the operational phase of the Rasht waste landfill. The Bow-Tie model is employed to develop control and mitigation strategies. Results: Environmental risks pose the greatest challenges in the Saravan Rasht landfill. Prioritization results, based on safety-sanitary criteria, reveal that the excessive use of repellants, such as insecticides, in the Saravan landfill is of utmost priority. Regarding the environmental criterion, seepage from the bottom of the landfill takes precedence, while the economic-social criterion emphasizes the high costs associated with controlling and developing the waste landfill's health engineering. Conclusion: Identifying and prioritizing risks in the landfill site facilitates the implementation of appropriate solutions for their reduction and control. The criteria influencing risk assessment are subject to constant change. The selection of an appropriate risk identification method enhances the efficiency of the chosen approach and ensures accurate determination of risks within the waste landfill. The bowtie method provides a more realistic understanding of the relationship between factors influencing risk occurrence, resulting consequences, and barriers that can hinder risks during the operational phase.

Background and purpose: Air quality control is an inevitable issue at the forefront of national concerns. The aim of this study was to predict the daily concentration of PM2. 5. Materials and Methods: According to the objective, the type of research can be considered practical, and the statistical population of the research includes meteorological and pollution measuring stations within the 22 districts of Tehran. However, the statistical sample (synoptic geophysical station and Tarbiat Modares measuring station) was selected using a non-random sampling method. The desired statistical year for the study included the daily data from the selected stations for one year. Eleven input variables were used, which included meteorological data from the geophysical synoptic station (maximum and minimum temperature, minimum and maximum relative humidity, rainfall, maximum wind speed, and wind direction) and pollution data of PM2. 5 concentration from the Tarbiat Modares station (daily concentrations of PM2. 5 and the previous day). The support vector machine (SVM) model was used for prediction in this step. Results: The model was able to predict the daily concentration values of the PM2. 5 pollutant for the upcoming days with a detection coefficient R²,= 0. 611 and RMSE = 10. 87. In the second method, the support vector machine (SVM) model was combined with principal component analysis (PCA) to reduce the number of variables and perform modeling. Conclusion: The results of this study show that the performance of the combined model is superior to the previous model, as the coefficient of determination R²,increased to 0. 65 and the error value decreased to 10. 37 RMSE (root mean square error). This hybrid model (PCA-SVM) can assist city managers and decision-makers in controlling and reducing the amount of PM2. 5 pollutants.