Freshwater systems are one of the most important natural resources for life. Despite their value, these ecosystems have suffered great impacts caused by human activities, which directly affect the aquatic biota and the quality of water sources. Considering the value of aquatic macroinvertebrates as bioindicators of water quality, the richness, composition, and water quality of La Gallega-Morropón stream, Piura-Peru, were compared. Two field trips were conducted between November 2018 and May 2019 (contemplated wet and dry periods, respectively), performing 4 sampling stations. A total of 1772 individuals of macroinvertebrates were recorded, distributed in 22 families. Psychodidae had an abundance of 670 individuals, followed by morphospecies (Gasteropoda) with 379 individuals, Chironomidae with 275 individuals, and Elmidae with 136 individuals (all indicators of water quality). Finally, the water quality index method: 1) BMWP/Col, presented one station with good (HB1), acceptable (HB2), and critical (HB3 and HB4) quality, while 2) EPT exhibited two stations with good quality (HB3 and HB4), HB1 regular quality and HB2 poor (HB3 and HB4), HB1 regular quality and HB2 poor quality.

Drinking water contamination by microplastic particles is a global concern that is becoming increasingly common due to consumer abuse, and we use laser fractionation spectroscopy to examine what microplastic particles in water packaging can do. Several types of bottled water were sampled at several manufacturing facilities in Baghdad. The presence of the measured micropolymer species in water was immediately classified and detected using a laser production resolution spectrometer as well as signal and plasma scattering spectra, various MP polymers “polyethylene terephthalate, polystyrene, polypropylene, polyethylene, and polyvinyl chloride” are five polymers that were successfully detected in drinking water to validate the ability to identify health risk factors based on potential environmental risk index (RI) and potential environmental risk factors (Tin), the results are calculated to show that risk predicates have evolved over a decade depending on the risk factors. To do. The smallest particle was 20 microns and the largest particle was 63.4 microns. Microplastics were detected in 5 out of 10 samples, PET in 4 samples, PS and PP in 2 samples, and PVC in sample 1, the most common polymer in bottled water is polyethylene. The average C/H ratios of the five samples were PE (1.76), PET (1.21), PS (1.52), PP (1.23), and PVC (0.99), on average, the measured trends of C/H values were [PE greater than PS], [PP greater than PET], and [PVC greater than PET]. According to our results, the integration of LIBS technology provides a fast and efficient way to detect microplastics. It has a high resolution of fine particles, allowing the detection of very small particles associated with various adverse effects on human health. The feasibility study for water bottling was approved, and the WHO water quality criteria were confirmed. As a result, we will undertake a thorough analysis of the best water bottling quality. In this study, the initial LIBS signals of several samples were used to completely detect microplastics. Microplastics in bottled water samples have been detected and quantified using LIBS spectroscopy techniques with Ecological Potential Ecological Risk. Analytical technology is used to investigate sources, perform research, and collect relevant data, worldwide reports, and permitted statistics to deliver crucial insights and recommendations.Water samples were obtained from several locations throughout Baghdad. At the source, 2 liters of water were obtained in plastic bottles for each sample, for a total of 10 samples. Each sample is owned by the factories that supplied it.

This research investigates the migration of Bisphenol A (BPA) from packaging containers into take-out vegetable soups and premixed tomato soups through three replicate studies. The samples underwent extraction using solid-phase extraction (SPE) cartridges, followed by separation on a C18 column. BPA concentrations in the soups were assessed at 15, 30, and 45-minute intervals, consistently revealing undetectable levels (<LOQ). Plastic packaging samples, known for BPA utilization in production, remained below the Specific Migration Limit (SML) set at 0.5 mg.kg-1, irrespective of material type or contact conditions. These results, conforming to EC regulations, suggest that food-contact materials (FCMs) in the Indian market pose no apparent health hazards during initial use. The absence of detectable BPA levels is attributed to the limited time-temperature relationship during the study. However, caution is warranted as BPA migration can occur with repeated use, emphasizing the importance of considering material quality and intended use of FCMs. The study underscores the significance of understanding BPA leaching under varied conditions, necessitating further research to explore long-term implications. Overall, the findings provide valuable insights for regulators, manufacturers, and consumers, contributing to the ongoing discourse on food safety and using plastic materials in food packaging.

Biodiesel production from Pongamia pinnata, a tree-based oil using healthcare industrial waste dolomite as a catalyst, was studied. The studies aimed to establish the ideal parameters for producing biodiesel, such as temperature, the ratio of methanol to oil, and the weight percentage of the catalyst. The healthcare industrial waste was procured and characterized. With the operating conditions, temperature maintained at 75°C, methanol to oil molar ratio of about 20:1, and a catalyst weight of 5%, the optimum yield of 92.3% was obtained. The tree-based nonedible oil source for biodiesel production was suggested widely due to its ability to achieve sustainable development goals (SDGs). The Pongamia Pinnata cultivation on barren land supports the afforestation projects with economic and environmental values; further biodiesel from renewable bioresources reduces emissions, and livelihood development to eradicate unemployment are the primary objectives for achieving the SDGs. The tree-based biodiesel production and adaptation of dolomite as a heterogeneous catalyst have proven to be a recent attraction among scientists. The present study is the first report on Pongamia pinnata for biodiesel production catalyzed by dolomite.

The rapid global plastic production of 348 million tonnes in 2018 has led to widespread environmental pollution, especially in terrestrial ecosystems. This study examines microplastics in agricultural soils, coming alarmingly. Particles ≤5 mm, which are defined as microplastics, have detrimental effects on the earth’s environment. Because of its ecological importance, soil acts as an important microplastic sink, affecting soil and plant health and microbial activity. A variety of factors contribute to microplastic pollution in agricultural soils, including plastic mulching, manure, agricultural products (silage nets, twine), sewage sludge, weathering, and other indirect processes. These microplastics migrate, threatening soil integrity and biodiversity. Soil microplastics are analyzed for size, volume fraction, and polymer. Common materials include polyethylene, polypropylene, polyamide, polystyrene, polyvinyl chloride, and polyesters. Techniques, including optical microscopy and spectroscopy, extract and analyze microplastics. This comprehensive review calls for increased concern about the ecological effects of microplastics in agricultural soils. It emphasizes the importance of managing plastics to solve environmental challenges. The integrated environmental assessment highlights the complex relationship between microplastics and soil ecosystems, providing insights into potential risks and suggesting strategies to combat this looming environmental threat.

The indigenous knowledge of the Dayak Paramasan in Indonesia holds the potential for environmental sustainability. This study aims to assess an environmental education framework grounded in the local wisdom of the Paramasan Dayak tribe. A survey was conducted among 300 individuals, including traditional leaders and members of indigenous communities residing in the Paramasan Subdistrict, Indonesia. Data collection occurred from May 2023 to July 2023 and was analyzed using Structural Equation Modelling (SEM). The findings indicate a significant association between indigenous values, local expertise, and community cohesion concerning environmental education. Local wisdom includes local skills, values, and community solidarity, which are crucial for environmental education. Local skills, like farming and hunting, have a significant impact on environmental protection. Passing down knowledge to younger generations needs improvement. Limited local resources create a gap between generations, but some believe traditional leaders can safeguard nature without formal education. Further exploration of implementing environmental education models within school settings will offer valuable insights for Indigenous communities and society, fostering environmentally conscious behaviors.

In this study, we synthesized cobalt-doped molybdenum supported on silica (Co/MS) nanocomposites with varying concentrations of cobalt (1, 5, 10, 15, and 20 wt%) using the sol-gel method. We investigated their physico-chemical properties, photocatalytic activity, and antimicrobial efficacy. The synthesized nanocomposites were characterized using a range of techniques, including X-ray powder diffraction (XRD) to determine crystal structure, UV-vis spectroscopy for optical properties, Fourier transform infrared spectroscopy (FT-IR) for functional group analysis, and scanning electron microscopy coupled with energy-dispersive X-ray microanalysis (SEM-EDX) for morphological and elemental composition analysis. The photocatalytic performance of these catalysts was assessed by their ability to degrade organic dyes, specifically methyl orange and methylene blue, under visible light irradiation. Our results demonstrated that the photocatalytic efficiency increased with higher cobalt content, with the 20 wt% Co/MS nanocomposite showing the highest degradation rates. Additionally, we evaluated the antibacterial activity of the nanocomposites against a range of microorganisms, including Gram-positive and Gram-negative bacteria, as well as fungal species. The 20 wt% Co/MS nanocomposite exhibited superior antimicrobial activity compared to the other samples, indicating its potential for applications in environmental remediation and antimicrobial treatments.

The most significant air pollutant is particulate matter of less than 10 microns (PM10), followed by ozone (O3) during the monitoring period from 2006 to 2022 in Chiangmai. The association between ambient pollutants and climate conditions in Chiangmai was assessed using regression analysis and analysis of variance (ANOVA). The ANOVA analysis indicated that the average temperature was associated significantly with the nitrogen dioxide (NO2) concentration in the ambient, but the average rainfall volume was associated significantly with most pollutants except only sulfur dioxide (SO2). From the prediction models, the rise in average temperature affected to increase in the concentrations of PM10 and O3. Interestingly, the increase in rainfall will be advantageous to compromise the severity of all pollutants. Meanwhile, on hotter days should be careful of the rise of PM10 and O3 concentrations. Therefore, the vital meteorological variables associated with air pollution are very useful for forecasting the harmful and severity level of each air pollutant.

The mountainous region of the Hunza River watershed basin, especially along the Karakorum highway, and also known as a third pole for the high accumulation of glaciers, which leads to huge devastating landslides occurring every year. Landslide susceptibility mapping was carried out using two deep machine learning techniques (DeeplabV3+ & universal network U-Net) and two statistical models (Intuitionistic Fuzzy divergence IF-D & Frequency ratio FR). The landslide susceptibility mapping is conducted using landslide inventory data and twelve conditional factors. The landslide susceptibility maps obtained from the two statistical models were compared with those generated by two deep machine learning models based on prediction accuracy measures, such as the Area Under the Curve (AUC) and Seed Cell Area Index (SCAI). The Success Rate Curve (SRC) was obtained using the training dataset, and the AUC values for the four models were as follows: 76.9% for IF-D, 76.9% for FR, 80.4% for DeeplabV3+, and 76.3% for U-Net. In terms of the Prediction Rate Curve (PRC) obtained from the validation dataset, the AUC values were found to be 80.8% for IF-D, 80.8% for FR, 81% for DeeplabV3+, and 77.8% for U-Net. To assess the classification ability of the models, the Seed Cell Area Index (SCAI) test was conducted. The results indicated that the SCAI (D-value) was 7.3 for U-Net, 10 for DeeplabV3+, 7.6 for IF-D, and 9.1 for FR. Overall, the findings revealed that DeeplabV3+ exhibited the highest prediction accuracy and classification ability, making it the most suitable choice for landslide susceptibility mapping in the relevant study area.

Invasive weed plants are unwanted and hazardous waste biomass; and have extraordinary potential to serve as raw materials for biochar production. To evaluate the potentiality of invasive weed for bioenergy production in the form of biochar, Crotolaria burhia was investigated. The response surface modeling and optimization of the biochar parameters were conducted using the experimental design expert 13.0. The optimum value of the desirability function was obtained at a pyrolysis temperature of 450°C and a particle size of 50-100 mm. The model represents a p-value less than 0.0500 and a high F value, which denotes its reliable and accurate prediction of experimental data. A strong correlation was observed between actual and predicted values for biochar composites fixed carbon, carbon, surface area, pore size, and pore volume. In the present study, C. burhia biochar production was carried out by slow pyrolysis at 450°C under vacuum conditions. Biochar was found to be alkaline, with a 33.23% yield. Proximate analysis of C. burhia revealed 3.35% moisture content, 8.48% volatile matter, 81.24% fixed carbon and 6.94% ash content. The elemental analysis shows major concentrations of carbon, hydrogen, and oxygen as 57.77%, 6.123%, and 27.60%, respectively. Low H/C and O/C molar ratios were quantified as 0.10% and 0.47%, respectively. It possesses a honeycomb structure having mesoporous surface porosity with a surface area of 155.19m²/g and the presence of a remarkable concentration of mineral elements calcium and potassium. Biochar rich in hydroxyl, carboxylic, and alkene functional groups enhances its applicability areas. These findings make C. burhia a potential feedstock for the production of good-quality biochar.