The objective of the research was to determine the water quality index of Lake Chinchaycocha, which has faced pollution problems for several years. To do this, we worked with data from ten water quality monitoring points collected by the National Water Authority (ANA) during the period 2019-2023, after which the water quality index (ICA-PE) was calculated by analyzing a total of 12 parameters, using the Water Quality Standard (ECA) for water category 4 E1 (lagoons and lakes). The results of the physicochemical parameters indicated that the values of total nitrogen exceed the limits established in the ECA in 82% of the data obtained, pH in 13%, and phosphorus in 1%. In the evaluation of inorganic parameters, data from the LChin1S monitoring point showed that lead and zinc levels exceeded the values established in the ECA by 8% and 3%, respectively. Regarding the ICA-PE of the dry and wet seasons, it was determined that both present a good quality according to their averages and with the results obtained from the ICA-PE in a general way, it is concluded that Lake Chinchaycocha has a good water quality having total nitrogen as the main pollutant.

This study focuses on assessing the toxicity levels in fruits and vegetables based on the presence of polycyclic aromatic hydrocarbons (PAHs), particularly in regions affected by industrial and vehicular pollution where the particulate matter deposits on the plant surfaces. Traditional methods, including Gas Chromatography/Mass Spectrometry (GC/MS) and HighPerformance Liquid Chromatography (HPLC), are used to measure PAH levels in fruits and vegetables, which are found to be valuable but expensive and time-consuming. However, the detection of toxicity relies on either expert knowledge or experimental analysis when compared with the limitations set by EFSA (European Food Safety Authority). Therefore, in this study, artificial intelligence techniques have been employed to evaluate the toxicity levels based on 16 PAHs. The PAH concentrations in fruits and vegetables were collected from different articles corresponding to safe and unsafe datasets and then validated through statistical analysis. The validated dataset is classified using different machine learning algorithms. Based on the output from the neural network, the level of toxicity is also scaled and compared with the targeted outputs. The promising results of the classification of toxicity using artificial intelligence methods are substantiated by an experimental study and validated through statistical methods. From the results, it can be observed that the machine learning algorithm has given classification accuracy of more than 90% along with their degree of harmfulness. This research holds implications for food safety and public health, offering a novel approach to the interdisciplinary understanding of climate change by addressing the impact of environmental contaminants on the edibility of fruits and vegetables.

The presence of anthropogenic activities in the coastal areas of the South Central Timor (SCT) Regency has weakened coastal resilience, which may exacerbate the impact of rising sea levels. One important factor that needs to be analyzed is the vulnerability assessment. This study, conducted from July to September 2024, aimed to determine the spatial distribution and variables that can influence the vulnerability in the coastal areas. The methods used were the Coastal Vulnerability Index (CVI) and the Social Vulnerability Index (SoVI), which then used Multi Criteria Analysis (MCA) to perform the standardization value. The integrated index values were then integrated into the Geographic Information System (GIS) for comprehensive spatial information. The results showed that, in general, the coastal areas of the SCT Regency were in the low (35%), medium (48%), and high (66%) risk categories. Areas of high physical vulnerability were alluvial lowland areas and those near hills. The karst hills that are characteristic of the coastal areas of the SCT regency have become a threat to the lives of coastal communities. Communities living in coastal hill areas, including the Kolbano and Oetuke coasts, and in the alluvial lowlands like the Tuafanu, Kualin, and Oni coasts, need to be the focus and priority areas for recovery efforts. This is due to the high level of vulnerability, both physically and socio-economically. Geomorphology is the primary contributor to physical vulnerability because these coastal hills and lowlands are prone to erosion and land degradation caused by waves, tides, and human activities. On the socio-economic side, land use, particularly mining activities, increases vulnerability by degrading the environment and threatening the livelihood of coastal communities. Key recovery efforts should focus on revegetation, which can help stabilize the soil, reduce erosion, and restore ecological balance while offering sustainable economic benefits to the local population.

The removal of pollutants from water bodies has emerged as a pressing global concern. Discharging untreated wastewater into the environment poses a significant threat due to the presence of hazardous substances like nitrate and phosphate, contributing to the widespread issue of eutrophication. This study focused on investigating the adsorption of phosphate from a synthetic solution using fly ash, an industrial by-product. To enhance the efficiency of coal fly ash, acid treatment was employed. Batch experiments were conducted to examine the influence of different factors, including pH, adsorbent dosage, initial phosphate ion concentration, contact time, and temperature. Surface electron microscopy (SEM) explained the morphology of the adsorbent, and Fourier Transform Infrared Spectroscopy (FTIR) analysis was performed to analyze the adsorbent pre and post-adsorption, allowing for the identification of functional groups tangled in the adsorption process. The major functional groups observed were hydroxyl, carboxylic acid, amines, and nitrile groups, all contributing to the adsorption process. Acid-modified fly ash (AMFA) demonstrated favorable results in terms of phosphate removal, particularly at a pH of 5.0 and an initial phosphate concentration of 50 ppm. Equilibrium in adsorption was achieved within 30 min at a temperature of 15°C with constant stirring of 100 rpm, resulting in a high phosphate removal rate of 91%. Freundlich isotherm was found to contribute a better fit for the adsorption data compared to the Langmuir isotherm. Pseudo-second-order kinetic model, with a high R2 value of 0.998, exhibited excellent agreement with the adsorption data for acid-modified fly ash. Thermodynamic study indicated that the adsorption process was heat absorbing (endothermic) and non-spontaneous at low temperatures. Overall, the results of the experimental study highlighted the promising adsorption potential of acid-modified fly ash as an effective adsorbent for phosphate removal in water treatment applications.

There is growing evidence of negative impacts of antidepressants on behavior of aquatic non-target organisms. Accurate environmental risk assessment requires an understanding of whether antidepressants with similar modes of action have consistent negative impacts. Here, we tested the effect of acute exposure to two antidepressants, fluoxetine and venlafaxine (0–50 µg/L), on the behavior of non-target organism, i.e., freshwater pond snail, Lymnaea stagnalis. As compounds interact with chemical cues in the aquatic ecosystems, we also tested whether the effects altered in the presence of bile extract containing 5α-cyprinol sulfate (5α-CPS), a characterized kairomone of a natural predator, common carp (Cyprinus carpio). Behavior was studied using automated tracking and analysis of various locomotion parameters of L. stagnalis. Our results suggest that there are differences in the effects on locomotion upon exposure to venlafaxine and fluoxetine. We found strong evidence for a non-monotonic dose response on venlafaxine exposure, whereas fluoxetine only showed weak evidence of altered locomotion for a specific concentration. Combined exposure to compounds and 5α-CPS reduced the intensity of effects observed in the absence of 5α-CPS, possibly due to reduced bioavailability of the compounds. The results highlight the need for acknowledging different mechanisms of action among antidepressants while investigating their environmental risks. In addition, our results underline the importance of reporting non-significant effects and acknowledging individual variation in behavior for environmental risk assessment.

This study was conducted in Hezhang County, Bijie City, Guizhou Province. The soil in the zinc smelting area has been contaminated with cadmium, lead, and zinc. Therefore, these elements are the focus of this research. Rice husk biochar was used as the passivation material. The Fourier infrared spectrum was utilized to study the biochar’s morphology, element content, mineral composition, structure, and surface functional groups. Moreover, the physical and chemical properties of the biochar were analyzed to explore its passivation effect. Biochar is beneficial in the cleaning of cadmium, lead, and zinc minerals and can be used for the passivation of heavy metals in contaminated soil. This study aims to understand the detailed mechanism behind this process and provide experimental data and ideas for pollution control. The results indicate that the biochar contains many functional groups, including -OH, C-H, C-O, C=O, C=C, and C-O-C. It also consists of a significant quantity of potassium salt, calcite, and quartz. Biochar has a noticeable pore structure, and as the pyrolysis temperature increases, the pore structure becomes more developed and thinner, with a smooth surface. The main minerals in the soil are quartz, mica, zeolite, illite, and chlorite. The aromatic degree of biochar increased with pyrolysis temperature. In contrast, the aromatic degree and polarity first increased and then decreased. The 0.2-0.45 mm biochar exhibited the best passivation effect on cadmium, lead, and zinc.

The inhibitory effect of Rosemary oil on the corrosion of aluminum alloy EN AW-2011 in 1M H2SO4 solution was studied by weight loss and electrochemical methods such as open circuit potential (OCP), linear sweep voltammetry (LSV) and linear polarization resistance (LPR). The inhibition efficiency increases with increasing the concentration and shows maximum inhibition efficiency (70.7 %) at optimum concentration (0.05 g.L-1). The linear polarization resistance measurements show that the presence of Rosemary oil in 1M H2SO4 solution influences polarization resistance increasing and corrosion current decreasing. The voltammetric curve shows that Rosemary oil reduces the anodic process. Open circuit potential results confirmed that organic compounds present in Rosemary oil can form a protective layer on aluminum surfaces. The inhibitive effect was probably caused by the adsorption of organic compounds such as 1,8-cineole, α-pinene, borneol, limonene, and myrcene on aluminum surfaces which are non-toxic and environmentally friendly. This study showed that the essential oil of Rosemary could be used as an environmentally friendly inhibitor of the corrosion of alloy EN AW-2011 in an acidic medium.

Naturally derived cyanotoxins, cylindrospermopsin (CYN), and microcystin-LR (MC-LR) have shown hepatotoxic and nephrotoxic effects in several studies. The present study aimed to determine the possible nephrotoxicity of MC-LR and CYN on mammalian kidneys using male Wistar rats as an animal model. Potential nephrotoxicity was evaluated at different doses of CYN (0.175 μg.kg-1, 0.140 μg.kg-1, 0.105 μg.kg-1) and MC-LR (0.105 μg.kg-1, 0.070 μg.kg-1, 0.035 μg.kg-1) was observed. Water samples from dug wells contaminated with CYN (0.161 μg.kg-1) and MC-LR (0.091 μg.kg-1) from the Padaviya area in Anuradhapura, Sri Lanka were used as environmental samples. The control groups were treated with distilled water. The exposure time of rats to the toxin was 90 days. Evaluation of urinary creatinine, serum creatinine, and Kidney Injury Molecule-1 (KIM-1) were estimated using standard protocols. A significant increase in serum creatinine levels was observed in all CYN and MC-LR treated groups (p<0.05) after 7 and 42 days of exposure, respectively, compared to control. It was found a decrease of urine creatinine when rats were treated with different concentrations of CYN and MC-LR (p<0.05) after 7 days compared to the control. The highest KIM-1 concentrations were recorded at 0.175 μg.kg-1 of CYN and 0.105 μg.kg-1 of MC-LR. The concentrations of KIM-1 in the control groups for CYN-treated and MC-LR-treated were not detected. Luminal protein, nuclear pyknosis, mild tubular epithelial swelling, vascular congestion, and interstitial inflammation in CYN and MC-LR treated groups were common. No predominant changes were observed in the control groups treated with CYN and MC-LR. The results of the present study confirm that the consumption of CYN and MC-LR-contaminated water may lead to kidney injury in Wistar rats.

Outdoor air pollution causes a lot of health problems for humans. Particulate Matter 2.5 (PM2.5), due to its small size, can enter the human respiratory system with ease and cause significant health effects on humans. This makes PM2.5 significant among the various air pollutants. Hence, it is important to measure the value of PM2.5 accurately for better management of air quality. Algorithms for deep learning and machine learning can be used to forecast air quality data. A model that minimizes the prediction error of the PM2.5 forecast is needed. In this paper, a PM2.5 concentration estimation model using Bi-LSTM (Bidirectional Long Short-Term Memory) with meteorological data as predictor variables is proposed. For a better estimation of PM2.5 values, the hyperparameters of the Bi-LSTM model used are tuned using the Osprey Optimization Algorithm (OOA), a recent meta-heuristic algorithm. The model that works with the optimal values of hyperparameters identified by OOA performed better than the other models when they are compared based on evaluation metrics like Mean-Squared Error and R2.

There is a pressing demand for the introduction of environmentally safe technologies for the industries that supply the basic needs of industrialized societies. Advanced Oxidation Processes may become one of the answers to these uprising pollution management problems in the near future. The present investigation aimed to reduce the refractory organics present in the biologically treated (Activated Sludge Process) tannery effluent using Photocatalysis. The optimum time, pH, dosage of H2O2, and mass of NPAC required for the effective treatment using photocatalysis were found to be 60 mins, 8, 0.2 mg.L-1, and 1g. 100 mL-1, respectively. Although the efficiency of homogeneous photocatalysis was found to be higher than that of heterogeneous photocatalysis, the biodegradability was higher in the latter, with a value of 0.26. The experimental results have proved that photocatalysis could be a promising technology to reduce the refractory organics present in the tannery effluent.