Applied Water Science最新文献

Runoff from glaciated catchments is an integrated process that includes glacier melt, snowmelt, rainfall and surface and subsurface runoff of meltwater from glacierized and non-glacierized areas. Monitoring and quantifying the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Himalayan basins is essential for decision-making in the water sector, particularly in water resources management and flood risk reduction in the region. An attempt has been made to characterize and hydrologically model streamflow (Bhagirathi River) for the Gangotri Glacier (Central Himalaya, India). A semi-distributed conceptual hydrological model is used for the streamflow modelling and assessing the major streamflow components (snow melt, glacier melt and rainfall runoff). Initially, the model was calibrated using the available in situ hydro-meteorological records for the ablation seasons of 2013–14 to 2015–16 (3 years), and further validated for the ablation seasons of 2016–17 to 2018–19 (3 years). The model performed well for all the studied years except for some months, where abrupt changes in the contrasting weather parameters (precipitation and temperature) were recorded. In the Gangotri Glacier Valley (upper Bhagirathi River catchment), snowmelt contributed the largest portion (55.5%) to total streamflow followed by glacier melt (29.7%) and rainfall runoff components (14.7%).

This comprehensive study explored the removal of methylene blue (MB) from aqueous solutions as a model pollutant, utilizing solar-driven photocatalysis with nano-sized titanium dioxide (TiO₂) and composites with activated carbon (AC) and reduced graphene oxide (RGO). This research introduces continuous solar reactor instead of conventional batch experiments investigating its design configuration. Utilizing response surface methodology (RSM), the study determined the optimal process conditions (MB concentration at 30 mg/L, pH 8.82, irradiation time 138 min), under which TiO₂ achieved a 93.13% MB removal efficiency. The study further revealed that the integration of TiO₂ with AC and RGO (5% wt.) significantly enhanced the MB photocatalytic degradation. The TiO₂/AC composite achieved 98.3% MB degradation in 138 min of solar exposure, related to its large specific surface area of 146 m²/g and a pore volume of 0.439 cm³/g. Likewise, the TiO₂/RGO composite demonstrated 97% removal with a surface area of 102 m²/g and a pore volume of 0.476 cm³/g, significantly better than nano-TiO₂. Additionally, the research investigated the role of the solar reactor configuration on MB removal. Using 26 mm Pyrex tube diameter with 15 cm long on parabolic aluminum concentrator inclined at 30° optimally achieved the peak MB degradation efficiency. Recyclability tests shown a noticeable decrease in nano-TiO₂ efficiency to 56.03% without regeneration; however, after regeneration following the third cycle, the efficiency significantly recovered to 70.07%. Thereby, this paper introduces an innovative, continuous, and well-designed solar reactor system for dye removal, employing nano-TiO₂ and its composites with AC and RGO for improved photocatalytic efficiency under statistically optimized process conditions.

Bottlenecks inherent in batch and column adsorption configurations have impeded the implementation of the adsorption technique in large-scale wastewater treatment systems. This study mainly aimed to develop an innovative wastewater treatment prototype that integrates inclined plate settlers (IPS) and composite adsorbent coating (CAC). The objective is to enable the removal of Cd²⁺ from aqueous solutions in a continuous setup, thereby enhancing its practicality for large-scale applications. The combined IPS-CAC system was optimized at various angle of inclination (θ), influent flow rate (Q) and adsorbate initial concentration (C_o) using the Box–Behnken Design (BBD) of the Response Surface Methodology (RSM). At optimized operating parameters (θ = 45°, Q = 5 ml/min and C_i = 1.87 mg/L) the IPS-CAC Cd²⁺ predicted (R² = 0.9926) and experimental removal efficiencies were 75.8% and 69.7 ± 4.67%, respectively. The IPS-CAC breakthrough adsorption capacity was 9.6 mg/g. Comparing IPS-CAC performance with a tank without plates and IPS with plain plates, the Cd²⁺ removal efficiencies were 2.4 ± 0.1% and 4.6 ± 1.1%, respectively, confirming the synergistic effect of IPS and CAC. Additionally, breakthrough curves were acquired for various flow rates, cadmium influent concentrations, and plate inclination angles. Only a 10% decline in the removal effectiveness (from 69.7 to 59.7%) of the CAC after three adsorption–regeneration cycles was observed, indicating its stability for heavy metal removal. The results underpin the potential of using IPS-CAC for industrial wastewater treatment and enhancing the use of adsorption on a larger scale.

This research aimed to synthesize polyvinyl fluoride membranes and coat them with tannic acid (TA) nanoparticles and polyethylene glycol (PEG) additives so that the membrane’s removal efficacy for humic acid (HA) pollutant from agricultural wastewater was investigated. Thus, six membranes with PEG:TA ratios of 0:0, 1:0, 0:1, 1:1, 4:1, and 1:4 were synthesized. Then, the membranes’ characteristics were identified by FTIR-ATR, FESEM, and AFM analysis, and HA’s particle size and zeta potential were also investigated. Based on optimizing effective parameters, the operating pressure of 1.5 bar and HA concentration of 80 ppm were selected as optimal values. The membrane with PEG:TA = 4:1, as the optimally modified membrane, had a pure water flux of 446.03 L/m².h, effluent flux of 72.43 L/m².h, and pollutant removal rate of 86.62% at pH = 7 after 60 min had passed. These values for the pristine membrane (PEG:TA = 0:0) were 265.64 L/m².h, 89.39 L/m².h, and 75.59%, respectively. The results showed that although the effluent flux was lower in the optimized modified membrane than in the pristine membrane, HA removal percentage was increased.

Throughout history, many scientists considered time as the result of changing the world and believed that time is not true. Among those who say that time is not true, Einstein is the only one who was able to mathematically explain the relativity of time in the field of geometry (space time) and present his equations in relativistic physics. Although Einstein, like other scientists, did not provide a clear definition of time, he presented the relativity of time well. He showed that time is not independent of space and bends along with space. Also, Einstein used the speed of light to convert mass into energy to introduce the law of mass–energy equivalence. Currently, basic laws such as conservation of mass, conservation of energy and equivalence of mass and energy have been presented. Recently, due to the importance of time in the development of science, especially in the field of water and chemistry, “timemass equivalence law” has also been presented (by the author). In this research, with the aim of expanding the relativity of time in the flows of mass and energy (not the field of motion and geometry), while presenting new definitions of “phenomenon”, “time” and “specific speed of transformation”, in addition to the theory of “mass equivalence law” “Time” was completed, the general equations of equivalence of energy time—and timemass were introduced. Then, to check the results more accurately, the general masstime equation (in this study, absorption kinetics) by performing surface absorption experiments of heavy metals (Fe + 2, Pb + 2, Zn + 2, Ni + 2, Cd + 2, Cu + 2)) was investigated by the adsorbents of green walnut shell (GWH) and its biochar (GWHB), and the results are tested in different ways.

A study was conducted at Punjab Agricultural University, Ludhiana, Punjab, with the aim of monitoring soil loss and infiltration rate in loamy sand soil. The study focused on the effects of applying polyvinyl alcohol (PVA) and mulch under simulated rainfall conditions. The experimental setup involved testing three levels of PVA (0.5%, 0.75%, and 1.0%), one level of wheat-straw mulch (600 g/m²), and a Control treatment (untreated soil). Each of these treatments was replicated four times. The lowest soil loss (20.9 g/m²) was recorded under the 1.0% PVA treatment, while the highest (120.1 g/m²) was seen under the 0.5% PVA treatment. The 1.0% PVA treatment showed a significant reduction in soil loss compared to the 0.5% PVA, 0.75% PVA, mulch, and Control treatments, with reductions of approximately 82.6%, 45.1%, 81.2%, and 89.6%, respectively. Regarding infiltration rates, the Control treatment exhibited the lowest rate (2.4 cm/h), while the 1.0% PVA treatment displayed the highest rate (9.6 cm/h). Additionally, the use of mulch led to a 44.7% reduction in soil loss compared to the treatment without mulch, likely due to the mitigated impact of raindrops. The infiltration rate was significantly higher (4.8 cm/h) under the mulched treatment compared to the unmulched treatment (2.4 cm/h). Overall, the application of PVA and mulch resulted in a drastic reduction in soil loss, likely attributable to the enhanced stability of soil aggregates, improved infiltration rate, and reduced runoff.

Palm oil mill effluent (POME), wastewater generated from palm oil production, is known for its extremely high chemical oxygen demand and brownish color. Anaerobic digestion is the primary treatment method for POME in the palm oil industry; however, anaerobically treated POME has high concentrations of residual contaminants and color intensity. This study proposes an approach to treat anaerobically-treated POME in recycled water for industrial applications by integrating preliminary organic precipitation, electrocoagulation, and electrooxidation (EO). The EO process was optimized in terms of the current density, electrolysis time, electrode arrangement, and feed flow rate. At a current density of 60 mA/cm² and an electrolysis time of 9 min, the EO process with a graphite anode and stainless-steel cathode in the monopolar electrode configuration reduced the phenolic concentration and color in the preliminary-treated POME from 8.95 mg/L and 317.19 ADMI to 0.25 mg/L and 26.10 ADMI, respectively. Additionally, the EO process exhibited a 92.26% efficiency in lowering the ammonium-nitrogen content.

The ubiquitous presence of MPs in water bodies presents an escalating concern, as these minuscule plastic particles could ultimately reach humans via the drinking water supply. This study explores the efficacy and underlying mechanisms of removing PE and PVC MPs using Abelmoschus esculentus seeds (commonly known as okra), a natural and environmentally benign coagulant. Through experiments conducted under varying conditions—such as pH level, coagulant dosage, MP concentration, and EC—using the standard method and a Jar test apparatus, the sedimentation rate was assessed. ZP analysis revealed that charge neutralization and bridging cause pivotal in enhancing the removal efficiency of MPs. FESEM and FTIR analyses corroborated the formation of new bonds during the interaction between the MPs and the okra seed-based coagulant. The findings indicate that the optimal parameters for PVC removal were a coagulant dosage of 70 mg/L, a pH of 10, and an MP concentration of 20 mg/L, achieving a removal efficiency of 80.11%. Conversely, for PE, the maximum removal efficiency of 64.76% was realized at a coagulant dosage of 70 mg/L, a pH of 3, and an MP concentration of 20 mg/L. Abelmoschus esculentus seeds offer a practical and eco-friendly option, potentially substituting chemical coagulants, to efficiently eliminate MPs from aquatic environments.

After precipitation, reference evapotranspiration (ET_O) plays a crucial role in the hydrological cycle as it quantifies water loss. ET_O significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ET_O and its predictive variables. This study aimed to model and forecast annual ET_O in Iran’s basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ET_O values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO₂), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ET_O. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics.