Water, Air, & Soil Pollution最新文献

Mangrove soil is crucial for maintaining the health and nutrient balance of coastal ecosystems. It often serves as the final sink for commercial, aquaculture, and agricultural contaminants. This necessitates developing and understanding precise insights into mangrove health and sustainability through tailor-made evaluation indices. Currently, there are few studies regarding the assessment of mangrove ecosystem sustainability. The Thai Binh Mangrove is the third-largest province in terms of mangrove coverage in northern Vietnam. This mangrove has not undergone a direct assessment of soil quality using ground-level data. Therefore, this study focuses on evaluating the current state of the Thai Binh Mangrove in Vietnam, identifying key factors contributing to its degradation. Soil samples were collected from 38 stations across the mangrove and analyzed for pH, heavy metals, and nutrients over two years, from 2022 to 2023. The mangrove soil quality is assessed using Principal Component Analysis (PCA) and Cluster Analysis (CA). The Pollution Load Index (PLI) is used to characterize soil pollution, and it ranges from 0.29 to 1.09. Additionally, the Ecological Risk Index (ERI) is used to assess the ecological impact of soil pollution, revealing that the area falls within the low-risk category. The study also proposes measures like aquaculture, ecotourism, and increased awareness and education regarding the sustainability of mangroves and soil quality. The study underscores the significance of international cooperation, treaties, and legislative reform in assisting decision-makers with sustainable mangrove management.

In this investigation, the purifying power of a biodegradable coagulant extracted from banana peel waste was studied and compared with that of a synthesized coagulant, hydroxyapatite. The biocoagulant of banana peel powder was prepared and characterized using different techniques, such as Fourier-transform infrared spectroscopy, scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, X-ray diffraction, and X-ray fluorescence spectrometry. The coagulation-flocculation process was adopted to treat water loaded with copper, zinc, and suspended matter. The experimental design methodology was employed for the optimization of the experimental conditions. The Box Behnken design with three factors (dose, granulation, and initial pH) defined in 15 experiments was chosen. Within the pH range of 6 to 8, there was a noticeable increase in the rate of elimination, and this noteworthy trend was confirmed by the observable changes in the point of zero charge. The biocoagulant shows a very good coagulation capacity comparable to that of hydroxyapatite in Zn removal. The obtained values for the removal of Zn, Cu, and turbidity using banana peel powder and hydroxyapatite were 86 %, 96 %, and 97 %, and 68 %, 99 %, and 97 %, respectively. Banana peel powder has the potential to serve as a cost-effective and eco-friendly option for wastewater treatment in the context of waste valorization and environmental protection.

Rainfall prediction, based on meteorological data and models, forecasts the possible rainfall conditions for a period in the future. It is one of the important issues in meteorology and hydrology, and holds significant scientific and social value for enhancing human society's adaptive capacity, reducing the risk of natural disasters, promoting sustainable development, and protecting the environment. This study proposes a rainfall prediction model based on CEEMDAN-VMD-BiLSTM, which couples CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise), VMD (Variational Mode Decomposition), and BiLSTM (Bidirectional Long Short-Term Memory). The model first employs CEEMDAN and VMD, two decomposition algorithms, for a secondary decomposition of the original data, followed by prediction using the BiLSTM network. The study integrates the characteristics of CEEMDAN, which include adaptability, completeness, denoising capability, and high precision, the characteristic of VMD in extracting trend information, and the ability of the BiLSTM model to better capture contextual information in sequence data and solve long-term dependency issues, thereby increasing the accuracy of rainfall prediction. The research selected Zhongwei City in the Ningxia Hui Autonomous Region as the study object and used 20 years of monthly rainfall data from 2001 to 2020 as the research data. The model was compared with standalone BiLSTM models, CEEMDAN-BiLSTM coupled models, and VMD-BiLSTM coupled models. The model was validated using four indicators: RMSE, MARE, MAE, and NSE. The results showed that the maximum relative error of the CEEMDAN-VMD-BiLSTM neural network rainfall prediction coupled model was 7.22%, and the minimum relative error was -7.03%. The prediction qualification rate was 100%. The overall NSE value of the model ranged from 0.63 to 0.97, with most values between 0.86 and 0.97. The excellent rate was about 84.6%, and the good and above rate was 92.3%. In the rainfall prediction for Zhongwei City, the prediction accuracy of this coupled model was better than the other three models. In summary, the CEEMDAN-VMD-BiLSTM rainfall prediction model proposed in this paper combines the advantages of various methods and has shown good predictive effects in experiments, providing an effective prediction method for rainfall.

This study investigated the radioactivity of groundwater and bottom silt from wells in southern Sinai, Egypt. Eight well sites were chosen (Abu Redis, Abu Zenima, and Al-Tor) and composite samples of water and silt were created from each. Southern Sinai well water (Egypt) was safe for drinking based on tested elements (²²⁶Ra < 300 Bq/L, ²³²Th < 100 Bq/L). However, some bottom silt samples showed elevated ²²⁶Ra, ²³²Th, and ²²²Rn-, potentially posing health risks through inhalation or ingestion. Further investigation is needed on these specific silt samples due to potential internal and external radiation exposure.

The quality of water is significantly impacted by the presence of Cr⁶⁺ and Ni²⁺ ions. This study investigates the effectiveness of a flow-by porous graphite electrode cell in removing these contaminants from simulated industrial wastewater. We explore the impact of various factors on the removal process, demonstrating the method's potential for efficient removal. The initial concentration of nickel and chromium ions (20 to 80 mg/l and 20 to 100 mg/l, respectively), the feed flow rate (0.28 to 1.11 ml/s), current density (0.2 to 2.25 mA/cm²) and pH all influence the removal rate and efficiency. A higher feed flow rate negatively affects the removal efficiency of both Ni²⁺ and Cr⁶⁺ ions. Nickel removal efficiency decreased by 34.9% at 20 ppm and 26% at 80 ppm, representing the highest and lowest reductions in efficiency, respectively. Chromium removal efficiency decreased by 19% at 100 ppm and 6.5% at 50 ppm, indicating the highest and lowest reductions in efficiency, respectively, under the same flow rate change. Under optimal conditions, the removal efficiency for Ni²⁺ was 99.47% after 15 min of operation at a current density of 1.96 mA/cm², a flow rate of 0.28 ml/s, and a pH of 8 and the removal efficiency for Cr⁶⁺ was 99.97% after 10 min of operation at a current density of 2.25 mA/cm², a flow rate of 0.28 ml/s, and a pH of 2. The flow-through porous electrode system achieves efficient heavy metal removal with operating costs of 0.24 USD/m³ for nickel and 0.38 USD/m³ for chromium at optimal conditions.

Manganese oxide (MnO_x) on the surface of the filter material can be used to effectively remove ammonium (NH₄⁺) and manganese ions (Mn²⁺) from water, but overgrow oxide film gradually shortens backwashing interval after several years of long-term filtration system operation. Different influent pollutant loading result in different durations for chemical peeling film. A growth kinetics model for MnO_x was established by adjusting the different initial concentrations of Mn²⁺ in the influent, which provided a theoretical basis for determining a specific time point for film peeling and recovered the shortened backwashing intervals in the filter columns. The variation in film thickness demonstrated a linear dependence on time, confirming the high accuracy of the kinetics model for film growth. The pseudo-first-order kinetic model better fits among adsorption and oxidation kinetic models of Mn²⁺. Hydrogen peroxide (H₂O₂) was identified as an effective agent in the chemical peeling film process. Hydroxyl radicals, generated by H₂O₂, destroy coordination bonds, producing extremely low solubility (≡MnO₂), which was then removed during the backwashing process.

Graphical Abstract

Antibiotics are intensively used in various sectors, such as human and animal husbandry, and in the current scenario, they are considered global contaminants in different environmental compartments. Constant antibiotic exposure leads to antimicrobial resistance in environmental microorganisms. However, the correlation between antibiotic exposure and resistance is still indistinct and unproven in environmental microbiota. The release of antibiotic-resistant bacteria from municipal wastewater into rivers poses a public health concern. This study aimed to explore the antibiotic resistance profiling of bacterial pathogens isolated from wastewater, sludge, water, and sediment samples of the Ganges River of three North Indian cities (Kanpur, Prayagraj and Varanasi) for summer and winter seasons. Antibiotic resistance profiles were done for 12 antibiotics through the disc diffusion method. PCR analysis of genomic and plasmid DNA, the prevalence of six Antibiotic Resistance Genes was evaluated in 103 bacterial isolates isolated from wastewater, sludge, river water and sediment samples of North Indian cities. This study gives insight into the role of wastewater treatment plants in the abundance and spread of antibiotic-resistant bacteria and genes through effluent in the receiving river environment. The consumption of antibiotics is very high in India, and Antibiotic Resistance Genes are mostly abundant in wastewater treatment plants and river water and sediment, which indicates that the river has the potential and probable reservoir of Antibiotic Resistance Genes.

Electrooxidation is commonly used in wastewater treatment but faces challenges with recalcitrant pollutants like tetrabromobisphenol A (TBBPA). Understanding the role of direct electron transfer (DET) and secondary free radicals in forming intermediate products can not only reveal halogenated phenols' electrooxidation mechanism but also aid in electrode design. Coupling triple quadrupole mass spectrometer and quadrupole time-of-flight mass spectrometer, the transformation products (TPs) and their dynamics were investigated during electrooxidation treatments of TBBPA. Furthermore, electrophilic addition and ring-opening mechanisms were simulated by density functional theory (DFT), and toxic changes of TPs were assessed by quantitative structural-activity relationship. The results demonstrate that the steady-state concentration of hydroxyl radicals (•OH) significantly influences the oxidation kinetics before reaching the mass transfer limit. In addition, DET occurs at low potentials (Ep ≈ +0.35 to +0.45 V vs SHE), accompanied with the process of film formation. Six novel intermediates of TBBPA were discovered in electrooxidation process, revealing the ring-opening mechanisms of TBBPA regulated by the steady-state density of hydroxyl radicals. The toxicity of intermediates towards fish and daphnia decreased significantly than that of TBBPA. Our findings offer valuable insights into the electrooxidation process of brominated phenols including their transformation and toxicity changes.

Increased mismanaged plastic has led to widespread microplastic (MPs) contamination in the marine environment. Our study investigates MPs across the inner, outer, and mangrove regions of the Kollidam River estuary on the east coast of India. Surface water and sediment samples at 18 locations were analysed for size, shape, colour, and polymer type. The average MP abundance in surface water and sediment was 2.42 particles. m⁻³and 1580 ± 705 particles. kg⁻¹d.w. respectively. The predominant polymer types observed were PP (40%), PE (26%), and PAc (24%). Medium-sized particles (1–2.5 mm) are more in surface water (44%), and small-sized (0.01–1 mm) particles dominate in sediment samples (50%). The most common MP shapes were fibres and fragments, with transparent MPs being the most frequently observed colour. The results highlight that the mangrove region acts as a potential sink for microplastic pollution.

Graphical Abstract

Freshwater ecosystems, especially lakes, constitute vital reservoirs of potable water, irrigation resources, and aquaculture habitats. However, there is a lack of comprehensive data regarding the prevalence of microplastics (MPs) in freshwater lakes of densely populated metropolitan regions in the Indian Subcontinent. In this study, we have investigated the qualitative and quantitative attributes of MPs in the surface waters of four important lakes in Pune, India: (i) Kasarsai, (ii) Pashan, (iii) Manas, and (iv) Mastani. Our analyses revealed prevalent contamination across all four lakes, with Kasarsai lake exhibiting the highest mean MPs abundance of 14.03 ± 5.41 particles/L. Primary morphotype of MPs detected in the water samples were fibres and the dominant size was between 100 µm to 1000 µm. Additionally, in terms of colour, transparent microplastics were prominent. Fourier Transform Infrared Spectroscopy (FTIR) revealed that polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET) were the main types of MPs present in water samples. Furthermore, we assessed the abundance of MPs ingested by commercially available edible fish Tilapia, Oreochromis niloticus, collected from these lakes. We observed maximum ingestion of MPs in the fish from Kasarsai lake, which was 2.8 ± 2.9 particles per individual fish. To evaluate the possible health risks on humans, Estimated Daily intake (EDI) and Microplastics Cancer Risk (MPCR) index were determined for adults and children. EDI of PP was highest for Kasarsai and Manas lake, while, EDI of PE was predominant for Pashan and Mastani lake. For all four lakes, the MPCR index of PE was highest in both adults and children, with the maximum reaching to 0.52 for children consuming water from Pashan lake. Our findings raise concerns about the potential negative effects of MPs on freshwater ecosystem and the health of humans consuming the water and fish from such lakes. An ambitious strategy involving the collective efforts of the general public is required to address this hazard.