Applied Water Science最新文献

This study describes a novel adsorbent with a multidentate ligand that was facilely fabricated by covalently bonding 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole on graphene oxide (AHMT-PRGO). The AHMT-PRGO nano-adsorbent was used for the effective removal of Hg(II), Pb(II), and Cr(VI) from wastewater. The AHMT-PRGO nano-adsorbent was synthesized by a nucleophilic substitution reaction between GO acyl chloride and AHMT chelating ligand in the presence of tetrabutyl-ammonium bromide as a catalyst. The successful modifications were confirmed via several spectroscopic and electron microscopy instrumentations including UV–Vis, FTIR, Raman, XRD, XPS, SEM, and TEM. The maximum adsorption capacities of Hg(II), Cr(VI), and Pb(II) on the AHMT-PRGO nano-adsorbent were 370.0, 136.2, and 109.6 mg/g, respectively, exceeding those of most previously reported adsorbents. Additionally, the equilibrium contact times for Hg(II), Pb(II), and Cr(VI) were 60, 30, and 400 min, respectively. In a mixture of nine heavy metal ions containing 250 ppm of each ion, the AHMT-PRGO nano-adsorbent exhibited high selectivity for Hg(II) ions. Furthermore, the AHMT-PRGO nano-adsorbent showed high stability over five adsorption–desorption cycles. Additionally, the AHMT-PRGO nano-adsorbent was successfully applied to remove heavy metal ions from real water samples. The novelty of AHMT-PRGO lies in the combination of a multidentate ligand for strong and selective binding with the high surface area and stability offered by covalently bonded graphene oxide. This combination offers potential advantages over traditional adsorbents in terms of adsorption capacity, selectivity, and reusability.

A magnetic pomegranate peels activated carbon (MG-PPAC) nanocomposite (23.46–26.75 nm) was prepared as an effective adsorbent for Acid Orange 7 (AO7) dye removal from wastewater. The effects of impregnation ratio and activation temperatures (600–900 °C) on the specific surface area and pore morphology were studied. BET, SEM, EDX, FT-IR, XRD and VSM are considered the synthesized composite MG-PPAC. The prepared magnetic composite at 700 °C activation temperature and impregnation ratio 1/2 (peels/ZnCl₂) exhibited 513.34 m²/g surface area, 0.4025 cm³/g volume of the total pores, and 3.1364 nm mean diameter of the pores. The magnetization saturation, remanence and coercivity of the MG-PPA composite were 14.116 emu/g, 0.50685 emu/g, and 19.705 G, respectively. Also, the composite MG-PPAC was in a super-paramagnetic state at room temperature and could be gathered within 5 S (less than 5 S) with an external magnetic field. The impact of pH, adsorbent dose, initial concentration of adsorbate (AO7 dye), and time of contact have been studied to optimize the removal process. Langmuir, Freundlich and Temkin isotherm models were used to investigate MG-PPAC adsorption behavior for AO7 dye. Applicability of the Langmuir isotherm model demonstrates a monolayer adsorption AO7 dye removal process, and the maximum monolayer capacity (Q_m) attained from linear solvation of LIM is 322.58 mg/g. Furthermore, the highest removal was 99.53% at pH 2.25. Also, the adsorption process was tested using like pseudo-first-order, pseudo-second-order, intraparticle diffusion, film diffusion, and Elovich models. The pseudo-second-order model is well-fitted to the operational data of AO7 dye removal.

This study aimed to investigate the simultaneous effects of drought and salinity on irrigation management coefficients in maize farms. A three-year field research was conducted in the form of a 3 × 3 factorial experiment with a randomized complete block design and three replications from 2020 to 2022 in a maize farm, in Aliabad Fashafoye, Qom province, Iran. The applied treatments included three levels of salinity (S₀ = 1.8, S₁ = 5.2, and S₂ = 8.6 dS/m) and three levels of irrigation (W₀ = 100%, W₁ = 75%, and W₂ = 50% of field capacity). Evapotranspiration stress coefficient (K_S) due to W₀S₁ and W₀S₂ treatments was (0.975 and 0.934), (0.974 and 0.932), and (0.962 and 0.935) in 2020, 2021, and 2022, respectively. According to the results, K_S decreased by increasing the salinity level of irrigation water, so a 1-unit increase in salinity level above the tolerance threshold of the crop to salinity decreased K_S by 0.78 and 1.76% for S₁ and S₂, respectively. Moreover, each percent of volumetric moisture decrease from field capacity decreased K_S by 5.9 and 13.3% in W₁ and W₂, respectively. Also, with the increase in the intensity of the stresses, the readily available water (RAW) of treatments decreased. The sole application of salinity stress decreased the decreasing slope of RAW by 3.2%, while the application of both stresses resulted in the decreasing slopes of 4.9, 5.7, and 7.8% at the salinity levels of S₀, S₁, and S₂, respectively, compared to the control. The findings of this study show that the accurate estimation of crop evapotranspiration and RAW can help to improve the irrigation schedule, and the amount of irrigation water used is less than in non-stress conditions due to the reduction of total evapotranspiration and less water uptake in environmental stresses in maize farms.

This study aimed to derive major pollutants for standard watersheds with relatively high pollution levels and identify their trends. Hence, the water quality index (WQI) and multivariate statistical techniques were used to analyze the water quality evaluation of standard watershed during the total maximum daily load (TMDL) policy period implemented since 2004. The WQI was calculated for 41 standard watersheds, divided into 14 main streams and 27 tributaries. Consequently, in the main stream, WQI decreased as it moved downstream after the MS5 site. In the tributary, WQI values were found to be low at TS11, TS15, TS16, and TS17 sites. However, the Mann–Kendall test results indicated that the overall WQI value was increasing, suggesting that the water quality of the study basin was improving as the TMDL policy phase progressed. Principal component analysis of the group with relatively low WQI among the standard watersheds revealed that water temperature, dissolved oxygen, total phosphorus, chemical oxygen demand, biochemical oxygen demand, and electrical conductivity were the main variables in the main stream cluster. In the tributary stream cluster, total phosphorus, dissolved oxygen, total suspended solids, total nitrogen, and electrical conductivity showed high loading values. This study proposed a series of methods to provide the basic data required for watershed management through detailed water quality assessment methods, statistical techniques for deriving major pollutants, and trend analysis of water quality evaluation.

The Yamuna River, a vital water source in India, poses a profound challenge concerning water purity across its entire stretch. The comprehensive review aims to thoroughly examine the river's water quality, shedding light on the sources of pollution and their consequences for both ecological systems and public health. The primary objective of this review is to examine the published research papers concerning the Yamuna River water quality stretching from Yamunotri to Prayagraj and its resulting impact on human health. This paper also comprises a wide range of pollutants mainly caused by human activity; during the strange period of COVID-19 lockdown, when all industries were closed, resulting in changes in water quality, signifies the destructive effects of human activity on the river. Studies uncover that the most contaminated areas are Nizamuddin of Delhi region and D/S of Agra in Uttar Pradesh, which includes the foremost level of faecal coliforms to be around 210000–11000000 and 450–6100000, respectively. The total coliforms were found to be between 700000–28000000 and 2200–32000000, respectively. Biochemical oxygen demands, industrial discharge, urban waste and agriculture are identified as the most responsible factors for this contamination. After the COVID-19 lockdown, all industries were open, and now, the conditions are the same as before COVID-19. The primary insight to be assembled is that the ecological balance of the Yamuna River and public health depend on the immediate requirement for effective wastewater treatment solutions. Besides offering valuable data by compiling findings from multiple studies, this review underscores the importance of implementing stringent regulations on industrial emissions, upgrading sewage treatment plants, and promoting eco-friendly farming methods to tackle pollution in the Yamuna River and also manage the rural and urban areas of the sewage pipeline plan. It stresses the importance of safeguarding the Yamuna River ecosystem's inherent socioeconomic benefits while alleviating the environmental harm caused by pervasive pollution. Essentially, the study calls for prompt and comprehensive measures to ensure the sustainable health of this crucial water resource in India.

Groundwater is considered the most important natural resource to mankind. Groundwater constitutes an important part of the hydrological cycle and is more prone to pollution. Dumpsite located in close proximity to groundwater resources is highly susceptible to leachates pollution. Predicting the susceptibility of groundwater pollution is crucial to address industry-standard codes for groundwater flow, contaminant transport, local to regional-scale water quality, and source water protection issues. Therefore, predicting heavy metal transport in groundwater around Lemna dumpsite in Cross River State, Nigeria, was examined. Soil samples were purposively collected with a soil Auger, along a straight line at (5 m, 25 m and 50 m) in the dumpsite. Water samples were purposively collected from five (5) boreholes close to Lemna dumpsite. The study utilized pumping test method to obtain data for the analysis of heavy metal transport in groundwater. Data analysis of the laboratory results of soil and borehole water quality focuses on arsenic, lead, cadmium, chromium, nickel, and mercury. Paired sample t test was used to analyse the soil and borehole water quality. Visual Modflow was also used to analyse the solute transport of heavy metals in groundwater around Lemna dumpsite. The paired sample t test of the analysis of heavy metals in soil exhibited a significant difference (p < 0.05) compared to National Environmental Standard Regulation and Enforcement Agency limits. The paired sample t test of the analysis of heavy metals in borehole water exhibited a significant difference (p < 0.05) compared to World Health Organization limits. The significant level indicates contamination of the soil and borehole water. The findings revealed a spatial spread of 259.2000 m²/day, with the contaminant travelling up to 94,608 m²/year. The extent of heavy metals concentration exhibited a maximum of 0.991 mg/l to a minimum of (− 6.72 × 10^–18 mg/l), with concentrations decreasing as the plume extend. The study recommends the need for remediation and stringent monitoring to mitigate heavy metal contamination of boreholes near Lemna dumpsite.

The Artocarpus heterophyllus (AH) seed was used as a coagulant in this study to explore the effects of pH, settling time, and coagulant doses on the removal of colour, turbidity, and heavy metals from paint industrial wastewater. The AH coagulant was instrumentally characterized by SEM, FTIR, and XRD. The maximum colour and turbidity removal efficiencies were 94.33% and 99.94% at the dosage of 0.2 g/L, pH 2. The mercury removal efficiency of 99.29% was achieved at the optimal conditions of 0.8 g/L coagulant dosage and pH 8. At a dose of 1.0 g/L and a pH of 10, the highest lead removal efficiency was 99.76%. The best removal efficiency for arsenic was 75.24% at a 0.8 g/L coagulant dosage and pH of 8. All at a time of 50 and 40 min, respectively. XRD diffraction results before treatment depict that the AH coagulant was crystalline and changed to amorphous after treatment. The SEM and FTIR results of the coagulant revealed changes in the surface morphology and functional groups before and after treatment. The reaction kinetics were best modelled in second order.

This study is the first attempt to characterize the quality status of El Fahs aquifer by combining graphical tools, multivariate statistical techniques and traditional geostatistical methods. Water samples are collected from thirty-six observation wells during April 2016 to characterize the physicochemical properties of the aquifer. Subsequently, these samples are partitioned into three hydrochemically distinct water classes (i.e., C1, C2, and C3) using the K-means clustering method. Principal Component Analysis is used to reduce the dimensionality of the dataset prior performing the clustering computations, resulting in clusters of higher quality than the non-reduced case in terms of Silhouette coefficient. Piper diagram is used to display the chemical composition of the samples, revealing the dominant role of Mg–Ca–Cl water type for all three classes, whereas Sodium and Sulfate were found to be the second most important cations and anions respectively. Indicator kriging (IK) is used to identify the probability of occurrence of the hydrochemical classes beyond the sampling locations. It is found that Class 1, associated with fresh groundwater component, is most probable to occur at the central part of the plain, mainly due to the presence of a dense hydrological network, whereas Classes 2 (agricultural activities) and 3 (dissolution of evaporate geological formations) are expected to occur at the southern and northern regions respectively. IK also identified the regions associated with high levels of uncertainty, mostly occurring in a large portion of the northern area due to the absence of available hydrochemical information. The results showed that integration of graphical methods, multivariate statistical techniques and geostatistical modeling, is an efficient approach for characterizing the hydrochemical status of the aquifer system, to spatially optimize the groundwater monitoring well networks and quantify the uncertainty levels of the water classes in a systematic way.

Water quality in arid regions is a crucial determinant of sustainable social and economic development. Combining traditional hydrogeochemical methods with ordinary least squares (OLS) and geographically weighted regression modeling (GWR), the suitability of surface water irrigation in the summer irrigation period was investigated in the Tarim Basin. The results indicated that all water samples belonged to three types of water: SO₄ Cl–Ca•Mg, SO₄ Cl–Na, and HCO₃–Ca Mg. A convergence phenomenon occurred under long-term irrigation conditions, showing a similarity between the salt composition of soils and surface irrigation waters. Although the current quality of surface water is generally suitable for irrigation, the process of reverse ion exchange has a more important effect on surface water bodies and soil salinity, thereby resulting in an increase in the Na-ion content of the soil and subsequently enhancing alkaline hazards. Both the OLS and GWR models unequivocally indicate that nitrate nitrogen primarily originates from natural weathering processes and that the sources of this material exhibit spatial heterogeneity across distinct regions. The construction of irrigation reservoirs to effectively deal with agricultural water shortages will lead to a deterioration in the quality of irrigation. The overall findings suggest that the water quality can meet the irrigation needs at present, but to ensure the sustainable use of water resources in arid regions, the increasing nitrogen concentration caused by human activities and the decline in water quality caused by reservoir construction need to be addressed in future irrigation management.

It observers that an object is submerged in a liquid, more pressure is applied to its bottom surface than its top surface, as a result pressure rises within depth of fluids. A buoyancy force is generated due to the pressure difference. In the current investigation, the mathematical formulation of bio-convective stagnation point flow of a radiative Maxwell fluid with multiple slip effect on an exponentially porous stretching surface is analyzed thoroughly. The buoyancy assisting and opposing conditions with magnetic field are discussed in the current investigation. Moreover, the energy and concertation equations are formulated by the utilization of Cattaneo–Christov theory and non-uniform heat source/sink. The flow model is developed in the form of partial derivatives, then use the similarity variables to convert the physical system into nonlinear ordinary derivative. The nonlinear system is tackled numerically with the help of Bvp4c approach on the MATLAB. The graphical upshots for various emerging parameter are observed with two aspects: buoyancy assisting (left( {lambda > 0} right)) and buoyancy opposing (left( {lambda < 0} right)). The observation shows that the greater values of mixed convection parameter improves the fluid velocity for assisting flow (left( {lambda > 0} right)), while declining trend is noticing for opposing flow situation (left( {lambda > 0} right)). Further, it is worth noticing that stronger inputs of thermal and concentration relaxation parameter yield lesser thermal and concentration diffusivity, which reduces the temperature and nanoparticles concentration.