This study examined the concentrations of 40K, 238U, and 232Th radionuclides and evaluated the possible radiological health risks to medicinal plants found in Ewu, Edo State, Nigeria, using a NaI(Tl) gamma spectrometer. The six selected medicinal plants were Mangifera indica, Dacryodes edulis, Terminalia catappa, Cymbopogon citratus, Anacardium occidentale, and Persea Americana. The results showed that the activity concentrations for 40K ranged from 146.59 ± 4.81 in Persea americana to 296.08 3.42 Bq/kg in Cymbopogon citratus, with a mean of 209.43 ± 5.14 Bq/kg; 238U ranged from 2.25 ± 0.06 to 5.57 ± 0.15 Bq/kg, with a mean of 4.73 ± 0.15 Bq/kg; and 232Th varied from 4.50 ± 0.35 to 12.07 ± 0.57 Bq/kg, with a mean of 8.00 ± 0.40 Bq/kg. The maximum and minimum activity concentrations of both 238U and 232Th were found in Mangifera indica and Cymbopogon citratus, respectively. The calculated average committed effective dose ECED was 0.130 μSv/yr and the excess lifetime cancer risk (ELCR) has a mean of 0.00913 (×〖10〗^(-3)). The radiological hazard assessment of the investigated medicinal plants was well within the internationally recommended safe limits of 0.3 mSv/yr and >〖10〗^(-4) for ECED and ELCR respectively. 232Th contributes 54.91% of the total ECED, while 238U contributes the least to 6.35%. 232Th exhibits a very strong, positive, and significant relationship with ECED and the ELCR, and it contributes largely to the ECED and ELCR due to ingestion of the examined herbal plant. Therefore, these medicinal plants are radiologically safe for human consumption.

Given the widespread use of mercuric oxide NPs (HgO-NPs), they have become increasingly prevalent in the soil ecosystem. Consequently, it is important to promptly evaluate their phytotoxic impacts. To this end, we have investigated the effects of HgO-NPs (0-200 mg/L) on germination and early growth of maize. Moreover, we have evaluated the interactive influences of HgO-NPs toxicity on the elongation and anatomical structures of primary roots. Relative to control, HgO-NPs decreased the germination percentage, speed and rate, but increased the mean germination time, mean daily germination time and time to 50% germination. The length and biomass of root and shoot and seedling vigour indices have significantly deteriorated. The inhibitory impacts of HgO-NPs on growth parameters were more pronounced in root than in shoot. The response of root was concomitant with dose and time-dependent inhibitions in root elongation and significant drops in root diameter, stele size, cortex size, and cortical cells count. The consequences of HgO-NPs were dose-dependent. For instance, the decrease of maize germination, growth, root elongation, and anatomy were more evident at 200 mg/L HgO-NPs compared to other doses and control. Overall, this study suggests that the presence of HgO-NPs leads to phytotoxic effects on germination and growth of young seedlings, highlighting a noteworthy challenge and environmental concern.

Wastewater treatment plants are an important pathway for microplastics (MPs) to enter the environment. In recent decades, hybrid treatment technologies such as sono-electrocoagulation have been used to treat various types of wastewater. This study aimed to remove polypropylene microplastics from synthetic wastewater by sono-electrocoagulation process using central composite design. The central composite design was utilized to investigate the relationship among four independent variables including the number of MPs (0.003-0.03 MPs/L), sodium sulfate concentration (180-9000 mol/L), voltage (1-15 V) and reaction time (20-180 min) on the efficiency of polypropylene microplastic. Design Expert 13 software and central composite design method were used to design and analyze the experiments and results. The optimum number of concentration of MPs, sodium sulfate concentration, voltage, and reaction time were found to be 6343.36 MPs/L, 0.0181924 mol/L, 10.0356 V, and 62.21 min, respectively. In optimal conditions, polypropylene removal was found to be %90.34. Central composite design proposed a quadratic model for this process. Adequacy of the model using lack of fit statistical tests values, p-values, and F-values was checked, yielding the values of were 1.76, 0.0001 ˂, 19.51, respectively. The R2, R2 adjusted, R2 predicted values which were 0.9367, 0.8776, 0.6959, respectively. Considering the proper removal efficiency, the sono-electrocoagulation process can be used to remove microplastics.

Constructed wetland coupled microbial fuel cell (CW-MFC) encompasses both aerobic and anaerobic zones to produce electrical energy while facilitating the oxidative breakdown of pollutants. In this study, we ascertained the effective setup of CW-MFC in order to assess the pollutant removal efficiency and electricity generation. The CW-MFC system was initially filled with textile wastewater. Stainless steel mesh with granular activated carbon as the anode and graphite rods as the cathode were used. Soil and gravel were used as substrates and Canna indica as macrophyte. Over the course of 4 weeks, regular assessments were conducted every 3rd day to monitor the alternations in the wastewater properties. Throughout the treatment phase, the planted CW-MFC system achieved a significant reduction in phosphate, nitrate, BOD, COD, and chloride as compared to the unplanted CW-MFC system. From this study, the results also show that planted CW-MFC produce maximum peak voltage (0.112V) and current (1.12 mA) in comparison to CW-MFC without plants. Consequently, the finding suggests that Canna indica possesses the capacity to treat textile wastewater.

This study investigated the potential impact of a fertilizer factory in Upper Egypt on the surrounding soil's radioactivity levels. Gamma-ray spectrometry was used to measure the concentrations of naturally occurring radionuclides (226Ra, 232Th, and 40K) in soil samples collected near the factory. Additionally, radon gas concentrations were measured, and various radiological hazard indices were calculated. Activity concentrations of 238U, 226Ra, 232Th, and 40K varied in the soil samples, ranging from 110.63 to 326.12 Bq/kg for 238U, 172.72 to 582.37 Bq/kg for 226Ra, 25.63 to 189.15 Bq/kg for 232Th, and 252.20 to 713.24 Bq/kg for 40K. Radium equivalent activity, absorbed gamma dose, and external and internal hazard indices exceeded permissible levels. Radon gas concentrations varied from 20.89 to 192.30 Bq/m3, with an average of 104.43 Bq/m3. The calculated effective dose from radon inhalation exceeded the recommended limit. The elevated levels of radioactivity in soil and the high radon gas concentrations suggest a potential health risk for farmers and residents near the fertilizer factory. Further investigations and mitigation strategies may be necessary to ensure the safety of the surrounding population.

In this research, successive electro-oxidation (EO) process was utilized to eliminate some of the primary organic contaminants in effluent wastewater, specifically phenol and chemical oxygen demand (COD). The performance of the electro-oxidation (EO) process was studied by using two graphite electrodes as anodes and three stainless steel electrodes as cathodes, which is a new strategy in this field. Taguchi method has been used to design experiments to approach the best experimental conditions for phenol and COD removal as significant responses. The best operating conditions that resulted in the maximum reduction of phenol and COD were current density (CD = 25 mA/cm2), pH = 4, support electrolyte (NaCl=2g/l), the distance between electrodes (Dist.=5mm), and time of 60 minutes. At these operating conditions, phenol and COD removal were 99.27% and 99.96%, respectively. This work provides important insights into a novel water and wastewater treatment method with a detailed analysis of the results.

Water is vital for human survival and has been instrumental in the development of ancient civilizations worldwide. However, in the modern era, humanity grapples with the pressing issues of environmental crisis and the depletion of natural resources. To address these challenges, it is crucial to embrace sustainable practices in land and resource management, ensuring the responsible use of natural resources while safeguarding the needs of future generations. The Finsk Dam, situated on the Sefidroud River, fulfills the vital purpose of providing potable water to the cities of Semnan, Mahdishahr, Sorkheh, and Shahmirzad. Moreover, it also caters to the requirements of downstream aquifers and environmental needs concerning drinking water development. As the Finsk Dam exceeds a height of 15 meters, it qualifies as a large dam according to the International Committee on Large Dams (ICOLD). Consequently, a comprehensive evaluation of its diverse environmental aspects assumes paramount importance. Despite the projections of regional development, the construction of the dam possesses the potential to yield adverse environmental effects within the region. To address this concern, the evaluation matrix method, as endorsed by ICOLD, was employed to scrutinize the various stages of the dam's construction and operation while assessing its environmental aspects. Following technical reviews, the third option emerged as the most suitable location for the dam's construction among the four available alternatives. Additionally, three distinct pipeline routes were identified and evaluated for the transportation of water from the dam to the Semnan province, with the second option being deemed the most appropriate choice.

Environmental pollution has posed a major threat to terrestrial, aquatic, and marine ecosystems, thereby affecting microflora and micro-fauna populations. This study assessed the growth attributes of maize plants on crude oil-polluted soils amended with agro-wastes. Six kilograms each of composite soil sample was weighed and transferred into one hundred and fifty labeled plastic buckets with drainage holes for soil aeration and spiked with 300mls each of crude oil, allowing for 14 days of soil acclimatization. Soil amendments such as groundnut husks, cassava peels, empty fruit bunch of oil palm, and maize cob powder were applied and allowed for 90 days. Maize seeds were sowed, while periodic data were collected and subjected to a three-way ANOVA. The result obtained revealed that maize seeds grown on agro-wastes treated and pristine control soils show early seed germination than the crude oil-polluted control soil. The plant height obtained for GnH14P + MaC14P at 10% was the highest with a mean (of 152.81cm2), and the leaf area of the maize from soil treated with GnH14P + EFBOP14P at 10% had the highest mean (756cm2), the leaf length of maize from soil treated with GnH14P + CasP14P at 3%, 6%, and 10% was the highest with mean ranging (54-97 cm2) with no significant difference in mean values obtained. The stem girth, number of leaves, and leaf width were generally improved in the bio-remediated soils. The result for the yield performance of maize shows that the days to flowering were shortened in the bio-remediated soil compared to the prolonged flowering days observed in the crude-oil polluted control. The number of seeds per cob was high in the bio-remediated soils while no seed was obtained in the crude-oil-polluted control soils. It can be concluded that the ameliorated treatment with the agro-wastes improves the performance of maize plants in crude oil-polluted soils.

Computational toxicology is a rapidly growing field that utilizes artificial intelligence (AI) and machine learning (ML) to predict the toxicity of chemical compounds. Computational toxicology is an important tool for assessing the risks associated with the exposure of finfish and shellfish to environmental contaminants. By providing insights into the behavior and effects of these compounds, computational models can help to inform management decisions and protect the health of aquatic ecosystems and the humans who depend on them for food and recreation. In aqua-toxicology research, Quantitative Structure-Activity Relationship (QSAR) models are commonly used to establish the relationship between chemical structures and their aquatic toxicity. Various ML algorithms have been developed to construct QSAR models, including Random Forest (RF), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Bayesian networks (BNs), k-Nearest Neighbor (kNN), Probabilistic Neural Networks (PNNs), Naïve Bayes, and Decision Trees. Deep learning techniques, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), have also been applied in computational toxicology to improve the accuracy of QSAR predictions. Moreover, data mining graphs, networks and graph kernels have been utilized to extract relevant features from chemical structures and improve predictive capabilities. In conclusion, the application of artificial intelligence and machine learning in the field of computational toxicology has immense potential to revolutionize aquatic toxicology research. Through the utilization of advanced algorithms and data analysis techniques, scientists can now better understand and predict the effects of various toxicants on aquatic organisms.

Radioactive pollution is caused when radioactive materials are deposited in the environment or atmosphere, particularly when their presence is inadvertent, and poses harm to the environment owing to the radioactive decay of the radioactive elements. Exposure to uranium in the workplace or environment can damage cells and increase cancer risk. Uranium, a heavy metal of the actinide family, has negative consequences due to its chemical and radioactive toxicity. The fission-track method with CR-39 evaluated the uranium content in blood samples collected from healthy persons and cancer patients. This method counted the fission tracks in a detector after the nuclear reaction. The data reveal that the lowest value in the group of people with cancer is 1.84±0.36 ppb, while the highest is 2.95±0.32 ppb. This population has an average uranium content of 2.52± 0.32 ppb. The highest result was 1.88± 0.22 ppb, while the lowest was 0.39±0.15 ppb in the healthy group. This population has a mean uranium content of 1.09±0.27 ppb. The statistics show that the uranium content in cancer patients' blood is much higher than that in the blood of healthy individuals.