Cleaner Water最新文献

Many factories use a variety of colours to enhance product aesthetics, leading to untreated wastewater being discharged into natural water bodies. This wastewater not only poses a threat to aquatic life but also endangers human health, causing issues like skin diseases, as some dyes are carcinogenic. Rhodamine B dye (RhB) is commonly used in industries such as textiles, paper, etc. This study focuses on synthesizing, characterizing, and applying Zeolite/Bi₂O₃ nanocomposites to efficiently remove RhB dye. Nanocomposites were synthesized using the sol-gel method and characterized using techniques including FTIR, SEM-EDS, XRD, DLS, point of zero charge determination, and surface resonance analysis. The removal process in an aqueous solution achieved its maximum efficiency of 100% under the following optimal conditions: initial concentration of RhB dye (0.5 mg/L), time (10 min), adsorbent dose (0.55 g), pH (4), and temperature (298 K). Real wastewater testing confirmed the nanocomposite's efficiency, removing a significant 98.12% of RhB dye. Reusability tests showed stability, with removal efficiencies of 100%, 97.08%, and 88.9% over three cycles. Isotherm analysis adhered to the Freundlich Isotherm Model (R² = 0.9953), signifying favourable adsorption behaviour. Kinetic analysis supported the pseudo-second-order model, indicating a chemisorption mechanism. Thermodynamic analysis suggested spontaneous (negative ΔG°) and endothermic (positive ΔH°) adsorption, with reduced randomness (negative ΔS°) at the solid-liquid interface. In conclusion, wastewater dye removal, especially Rhodamine B, is vital for environmental and public health protection. The Zeolite/Bi₂O₃ nanocomposite emerges as an efficient, sustainable, and eco-friendly adsorbent for Rhodamine B dye removal in both synthetic solutions and real wastewater.

The demand for water resources has increased due to rapid increase of metropolitan areas brought on by growth in population and industrialisation. In addition, the groundwater recharge is being afftected by shifting land use pattern caused by urban development. Using precise and trustworthy estimates of groundwater level is vital for the sustainable groundwater resources management in the face of changing climatic circumstances. In this context, machine learning (ML) methods offer a new and promising approach for accurately forecasting long-term changes in the groundwater level (GWL) without computational effort of developing a comprehensive flow model. In order to simulate GWL, five data-driven (DD) models, including the hybridization of support vector regression (SVR) with two optimisation algorithms i.e., firefly algorithm and particle swarm optimisation (FFAPSO), SVR-FFA, SVR-PSO, SVR and Multilayer perception (MLP), have been examined in the present study. Spatial clustering was utilised to choose four observation wells within Cuttack district in order to study and assess the water levels. Six scenarios were created by incorporating numerous variables, such as GWL in the previous months, evapotranspiration, temperature, precipitation, and river discharge. The goal was to identify the variables that were most efficient in predicting GWL. The SVR-FFAPSO model performs best in GWL forecasting for Khuntuni station, according to the quantitative analysis with correlation coefficient (R) = 0.9978, Nash–Sutcliffe efficiency (NSE) = 0.9933, mean absolute error (MAE) = 0.00025 (m), root mean squared error (RMSE) = 0.00775 (m) during the training phase. It is advised that groundwater monitoring network and data collecting system are strengthen in India for ensuring effective modelling of long-term management of groundwater resources.

This study quantified the volatile organic compounds (VOCs) in the Omi-Asoro Stream located in Ilesa town, Nigeria, to understand their sources and health risks to humans. The VOCs were measured in 2023 according to the US EPA equilibrium headspace method using a gas chromatograph (GC) and detected by a flame ionization detector (FID). Their human health risk assessments via ingestion and dermal contact were also estimated. The results showed that dissolved oxygen (DO) ranged 0.5–4.8 mg/L. Chemical oxygen demand (COD) was exceptionally high (March: 181.3 ± 45.5 mg/L; July: 180.7 ± 25.7 mg/L) in the industrial waste discharge area. Twenty-two and eighteen sets of VOCs were detected in March and July, respectively. 1,2-dibromo-3-chloropropane (DBCP) was the predominant VOC in the stream accounting for 18% (March) and 19% (July). DBCP, 1,2-dichlorobenzene+nbutylbenzene (oDCB+bBZ) and hexachlorobutadiene+1,2,4-trichlorobenzene (HCBD+TCB) were ubiquitous in the stream with 100% detection frequency. Disinfectants/fumigants, cleaning agents, industrial solvents, agrochemicals and plastic materials were the main sources of the VOCs. No individual VOC posed a non-carcinogenic risk (HI) in both months of the study. However, the total HI via ingestion route in March posed a non-carcinogenic health risk to children (HI_sum = 1.03). BDCM, TeCA, TCP and pDCB posed a high carcinogenic risk to humans via ingestion with values in the range of (0.00219–5.07) × 10⁻² for both months. TCP also posed a high carcinogenic risk (range of 10⁻⁴) via dermal contact to humans. The highly impaired water quality of the stream was due to industrial, agricultural and other anthropogenic activities.

Environmental sustainability has gained greater acceptance as an approach to achieving the objective of a secure ecosystem with a reliable management system. The best strategy for maintaining a healthy ecosystem is waste management. In this present study, chromium (Cr) adsorption capacity from real tannery wastewater on thermally activated adsorbent, equipped from Cucurbita moschata (pumpkin) peel is described. The adsorbent features were investigated by implementing Fourier transform infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX), and pHpzc (point of zero charges) analysis. The Cr adsorption was identified by EDX analysis. SEM images were analyzed to record surface morphological modifications. The adsorbent has a pHpzc of 8.7. The thermally activated adsorbent is used to treat the wastewater, in a batch experiment with varying parameters including contact time, adsorbent dose, and pH. Under optimal circumstances, 50 mL of wastewater was mixed with 2.5 g of adsorbent, agitated for 10 min, allowed to settle, and then the Cr concentration was evaluated. The Cr level in untreated effluent and in filtrate was 3178.6 mg/L, and 12.1 mg/L, respectively. The capability of Cr adsorption and Cr removal efficiency was 3164.46 mg/g and 99.32%, correspondingly, at a pH of 7.2. The biochemical oxygen demand (BOD), chloride (Cl^-), and chemical oxygen demand (COD) showed a decreasing percentage of 96.58%, 55.62%, and 95.01%. The Cr adsorption fitting for pumpkin peel adsorbent follows the Pseudo second-order (PSO) kinetic and Freundlich isotherm model. Thus, this investigation established the efficiency of using pumpkin peel as an adsorbent for Cr tanning effluent treatment.