Applied Water Science最新文献

{"title":"Human health risk assessment for fluoride and nitrate contamination in drinking water of municipal and rural areas of Zahedan, Iran","authors":"Hossein Abdipour,&nbsp;Ali Azari,&nbsp;Hossein Kamani,&nbsp;Khadijeh Pirasteh,&nbsp;Ferdos Kord Mostafapour,&nbsp;Shahla Rayegnnakhost","doi":"10.1007/s13201-025-02375-8","DOIUrl":"10.1007/s13201-025-02375-8","url":null,"abstract":"<div><p>Increased fluoride and nitrate concentration in water resources can affect consumers' health adversely. The objective of this study is to health risk assessment of fluoride and nitrate in the drinking water of municipal and rural areas of Zahedan using probabilistic approaches. For this purpose, 347 water samples were collected from both urban and rural areas of this province. After the chemical analysis of the samples, a health risk assessment was conducted using the USEPA model, and a sensitivity analysis was performed by Monte Carlo software. The average concentration of nitrate in rural and municipal areas drinking water was 31.89 mg/L and 40.87 mg/L, respectively. Fluoride concentration in rural samples was 2.13 mg/L while municipal samples had 1.28 mg/L. 14.53% and 24.12% of rural and urban areas exceeded NO₃⁻ limits, respectively. Rural samples had higher F- concentrations than WHO standards. CDI values for fluoride and nitrate in municipal areas were 0.04 and 1.15 mg/kg/day, for adults and 0.09 and 2.82 mg/kg/day, for children. The corresponding values for rural areas were 0.06, 0.9, 0.15, and 2.2 mg/kg/day. The HQ for nitrate in children was between 0 and 5.2 in children, with an average of 1.71. These values were registered to be 0–3.85 and 1.26, respectively, in the adult group. Also, the average value of HQ fluoride in children is much higher than that of adults, with values of 2.45 and 1.47 in rural and urban areas, respectively, both exceeding 1. The results indicate a possibility non-carcinogenic risk of nitrate and fluoride, particularly for children in these areas, is significant. Therefore, it is necessary to pay special attention to improving the quality of drinking water in this province.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02375-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of positive matrix factorization and water quality models for pollution source identification and water quality enhancement in rivers","authors":"Semin Kim","doi":"10.1007/s13201-025-02393-6","DOIUrl":"10.1007/s13201-025-02393-6","url":null,"abstract":"<div><p>Identifying the primary pollution source poses a challenge in river watersheds characterized by diverse land-cover types and mixed pollution sources. We addressed this challenge by focusing on the major tributaries influencing the water quality of the Mankyung River’s mainstream, successfully identifying the primary pollution source. Additionally, it identified the limiting nutrient for algal growth in the Mankyung River, proposing an alternative strategy to enhance water quality and mitigate algal growth. Positive matrix factorization (PMF) was employed to discern pollution sources in major tributaries, namely Jeonju-cheon and Iksan-cheon, impacting mainstream water quality. For Jeonju-cheon, pollution from urban and agricultural areas, including wastewater treatment plants, emerged as the primary source. For Iksan-cheon, pollution from urban and agricultural areas predominated. The nitrogen-to-phosphorus ratio and correlation analysis revealed that total phosphorus is the limiting factor for algal growth. Furthermore, scenarios to improve water quality and reduce algal growth were developed, and the Environmental Fluid Dynamic Code (EFDC) was used in the simulation, while the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) was used in water quality assessment. The findings demonstrated improved water quality and decreased algal blooms in the downstream Mankyung River region. This research provides a foundation for applying PMF, the EFDC, and the WQI in tracking pollution sources and enhancing water quality in rivers.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02393-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of land-use and climate change on future extreme flows: a study for three dam watersheds in Alborz and Tehran provinces of Iran","authors":"Mostafa Naderi,&nbsp;Fereshteh Talebi Ardeh,&nbsp;Farzaneh Abedi,&nbsp;Zohreh Masoumi","doi":"10.1007/s13201-025-02396-3","DOIUrl":"10.1007/s13201-025-02396-3","url":null,"abstract":"<div><p>This study assesses the impact of land-use and climate change on hydrological regime of three dam watersheds (Karaj, Latian and Mamlu) in Alborz and Tehran Provinces of Iran. Daily precipitation and temperature data from CMIP6 are transiently downscaled to ten climatic stations using the LARS-WG under global warming scenarios SSP1-1.9, SSP2-4.5, and SSP5-8.5. The Cellular Automata-Markov-chain machine learning is used to simulate future land-use maps (2021–2080) by training and testing its multilayer perceptron neural network with observed land-use change during the period 1995–2015. The study area will experience warming by 0.78, 2.1, and 2.4 °C under SSP1-1.9, SSP2-4.5, and SSP5-8.5, respectively, and precipitation anomalies by +129.3, −95.6, and −54.2 mm, respectively, compared to the baseline period 1991–2014. Extreme precipitation depth will increase at all stations under SSP1-1.9. However, precipitation change depends on the storm’s return period, station, and scenario under warmer scenarios. The SWAT-predicted river flow over three watersheds will increase, compared to the baseline period, under SSP1-1.9 but decrease under SSP2-4.5 and SSP5-8.5. Among combinations of land-use and climate change scenarios, land-use scenario High under SSP1-1.9 leads to greatest annual streamflow, while no change in land-use under SSP2-4.5 results in maximum reduction in streamflow over three watersheds. Extreme flows over Karaj and Latian watersheds show no sensitivity to different land-use scenarios due to negligible land-use development in future but they still are sensitive to climate change scenarios. Meanwhile, extreme flows over Mamlu watershed show significant sensitivity to both land-use and climate change scenarios due to significant land-use change in future.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02396-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous electro-Fenton process using a novel catalytic electrode for the degradation of direct dye from aqueous solutions: modeling, optimization, degradation pathway and toxicity evaluation","authors":"Seyedeh Mahtab Pormazar,&nbsp;Arash Dalvand","doi":"10.1007/s13201-025-02394-5","DOIUrl":"10.1007/s13201-025-02394-5","url":null,"abstract":"<div><p>In this study, Fe₃O₄ magnetite nanoparticles were coated on the granular activated carbon (GAC) surface and packed in stainless steel (SS) mesh, which was named MGACSS. It was developed as a novel three-dimensional cathode in the heterogeneous electro-Fenton (HEF) process for direct dye removal from colored wastewater. According to the Box–Behnken design, the Direct Blue 80 (DB80) dye removal efficiency and chemical oxygen demand (COD) degradation under the optimal conditions of initial dye concentration of 35 mg/L, current of 0.09 A and reaction time of 18  min reached 98.97% and 66.66%, respectively. Furthermore, scavenger studies confirmed that the surface-bounded ·OH was the major oxidant responsible for the degradation of DB80 dye. The MGACSS electrode exhibited a dye removal efficiency of 98.56% even after six consecutive operations, indicating excellent stability and reusability. The efficiency of the MGACSS cathode demonstrated an excellent treatment performance in removing other direct dyes of Direct Brown 103 (DB 103), Direct Red 23 (DR23) and a real sample with 97.34%, 98.15% and 93.1% efficiency, respectively. This study suggested a highly efficient and stable novel electrode for removing direct dye from wastewater through the HEF process, over a wide pH range.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02394-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Removal of chromium from synthetic wastewater by electrocoagulation and using natural coagulant (blend of hen eggshell powder with lime): optimization of response surface methodology","authors":"Werkne Sorsa Muleta,&nbsp;Firomsa Bidira Abdi,&nbsp;Endrias Adane Bekele","doi":"10.1007/s13201-025-02384-7","DOIUrl":"10.1007/s13201-025-02384-7","url":null,"abstract":"<div><p>Water is a limited natural resource that is essential for both the survival of the environment and all forms of life. Nowadays, heavy metal pollution containing Cr has put serious threat to our environment. It can enter into soil, water, and even particulate matter in air, and can be harmful to human health and wild life. In this work, the removal of Cr from synthetic wastewater by electrocoagulation supported by natural coagulant (eggshell powder) with aluminum electrodes was investigated. The central composite design of the response surface methodology was employed to estimate and optimize process variables, such as initial Cr concentration (225–475 mg/L), solution pH (5–9), and current density (0.35–045 A/m²), and treatment time (30–40 min) with an electrode distance (ED) of 0.5 and 1 cm, respectively. 99.90% and 99.74% of removal efficiencies were observed at initial Cr concentration of 456.11 mg/L, a solution pH of 5.45, with current density of 0.47 A/m², and treatment time of 36.84 min. The analysis of variance (ANOVA) was performed, and the multiple correlation coefficients (<i>R</i>²) of both ED were found to be 0.9996 and 0.9955, which confirms the significance of the predicted model. Furthermore, X-ray diffraction, Fourier transform infrared spectroscopy, Brunauer–Emmett–Teller analysis, and thermogravimetric analysis were used to characterize the crystal structure, functional groups, specific surface area, and thermal stability of the coagulants (eggshell powder). The findings of this study suggest that using this natural coagulant, synthetic wastewater can be treated in a more cost-effective and simple way than other existing method.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02384-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran","authors":"Mahnoosh Moghaddasi,&nbsp;Mansour Moradi,&nbsp;Mahdi Mohammadi Ghaleni,&nbsp;Zaher Mundher Yaseen","doi":"10.1007/s13201-025-02377-6","DOIUrl":"10.1007/s13201-025-02377-6","url":null,"abstract":"<div><p>Drought assessment is inherently complex, particularly under the influences of climate change, which complicates long-term forecasting. This study introduces a novel hybrid deep learning model, Deep Feedforward Natural Networks (DFFNN), enhanced by War Strategy Optimization (WSO), aimed at forecasting the Standardized Precipitation Evapotranspiration Index (SPEI) for lead times of one, three, six, nine, and twelve months. Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. The model’s performance was validated against two established optimizers: Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). Evaluations were conducted at two synoptic stations with distinct climatic conditions in Iran. Results demonstrated that the WSO-DFFNN model achieved superior performance for SPEI 12 (t + 1) with a correlation coefficient (r) of 0.9961 and Normalized Root Mean Square Error (NRMSE) of 0.1028; for SPEI 12 (t + 3) with r = 0.8856 and NRMSE = 0.1833; for SPEI 12 (t + 6) with r = 0.8573 and NRMSE = 0.2203; for SPEI 12 (t + 9) with r = 0.7951 and NRMSE = 0.2479; and for SPEI 12 (t + 12) with r = 0.7840 and NRMSE = 0.3279 at the Chabahar station. Additionally, the WSO-DFFNN model outperformed for SPEI 12 (t + 1) with r = 0.9118 and NRMSE = 0.1704; for SPEI 12 (t + 3) with r = 0.8386 and NRMSE = 0.2048; for SPEI 12 (t + 6) with r = 0.7602 and NRMSE = 0.2919; for SPEI 12 (t + 9) with r = 0.6379 and NRMSE = 0.2843; and for SPEI 12 (t + 12) with r = 0.6044 and NRMSE = 0.3463 at the Anzali station. The results obtained from this study have the potential to improve drought management strategies.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02377-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developed a solar still unit for saltwater desalination: numerical prediction and performance verification","authors":"Ayman Ibrahim,&nbsp;Nahed El Mahallawy,&nbsp;Islam Elsebaee,&nbsp;Hebatullah Megahed,&nbsp;Galal Aboelasaad,&nbsp;Abdelalim El-Bediwy,&nbsp;Osama Dewedar","doi":"10.1007/s13201-025-02366-9","DOIUrl":"10.1007/s13201-025-02366-9","url":null,"abstract":"<div><p>In the globe, there is a rise in water demand for agricultural, industrial, and domestic purposes. Single-basin solar stills (SBSS) have been a subject of research in various countries, particularly in regions with water scarcity or limited access to clean drinking water. In this work, SBSS for desalinating high-salinity water were developed, tested, and evaluated based on a developed numerical model using MATLAB R2021a program to predict the best productivity through the best selection of raw materials used to develop the SBSS. A four-inclined SBSS was fabricated and examined experimentally according to numerical model findings for best design parameters at Marsa Matrouh, 31° 21′ 10.44″N, 27°14′14.10″ E, Agricultural Station—Agricultural Research Center (ARC), Egypt. The hourly experimental results are compared with the numerical results. A good correlation between the numerical and the experimental results with variations in water, and glass temperatures of 9, and 18% respectively, and a variation in cumulative productivity by 11%. The results clearly showed that instantaneous productivity increases by decreasing water depth to 10 mm and using the SBSS unit partially insulated from the bottom of the basin. Adding insulation in front of the sides and back of tempered glass increases the shading area and decreases water temperature hence the cumulative productivity by 15%. The cumulative productivity reached 3 L for the SBSS unit partially insulated from the bottom of the basin with an area of 0.6 m² for only 12 h working system at a water depth of 10 mm.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02366-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling, evaluation and forecasting of suspended sediment load in Kal-e Shur River, Sabzevar Basin, in northeast of Iran","authors":"M. A. Zangeneh Asadi,&nbsp;L. Goli Mokhtari,&nbsp;R. Zandi,&nbsp;M. Naemitabar","doi":"10.1007/s13201-025-02361-0","DOIUrl":"10.1007/s13201-025-02361-0","url":null,"abstract":"<div><p>Studying sediment transport to rivers is crucial for effective river management, engineering, and environmental preservation. Neglecting this aspect can lead to significant harm to natural ecosystems. This research aims to estimate suspended sediment levels in the Kal-e Shur Sabzevar River using various machine learning algorithms, which have gained popularity in recent years due to their high accuracy and reliability. The study employs ensemble Bagging algorithms, the gradient boosting machine (GBM), genetic algorithm, Naïve Bayes algorithm, gradient boosting decision trees, and extremely randomized trees. These algorithms provide a coherent framework that can serve as a standard for evaluating and comparing models in future research. Initially, data from 354 sediment measurement stations, including flow discharge, sediment discharge, and precipitation, were collected. After validating data homogeneity using the double mass method, 70% of the data were allocated for training, and 30% for testing. The algorithms were trained with this data, and their performance was evaluated using the coefficient of determination (<i>R</i>²), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE) statistics. Additionally, a partial least squares (PLS) regression model was employed to identify the most influential factors affecting suspended sediment load in the basin. The results demonstrate that the gradient boosting machine (GBM) model outperforms other algorithms, exhibiting <i>R</i>² values of 0.95, RMSE values of 0.019, and NSE values of 0.78. The PLS model identified geological factors and slope as primary determinants of suspended sediment load in the region. Lastly, the algorithms predicted sediment levels, with the GBM algorithm estimating a sediment concentration of 8955 mg/liter with a relative error of 8.54%, indicating strong alignment with the total sediment load in the region.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02361-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS-based multi-criteria decision making for identifying rainwater harvesting sites","authors":"Waqed H. Hassan,&nbsp;Karrar Mahdi,&nbsp;Zahraa K. Kadhim","doi":"10.1007/s13201-025-02378-5","DOIUrl":"10.1007/s13201-025-02378-5","url":null,"abstract":"<div><p>The Middle East region, with its arid and semi-arid climate, is one of the regions most affected by climate change and water scarcity. To address the severe issue of water scarcity in the western region of Iraq, this study identifies optimal potential rainwater harvesting (RWH) locations. Geographic Information System (GIS) and multi-criteria decision-making (MCDM) techniques were employed to generate themed layers for RWH. The nine primary criteria considered were rainfall, elevation, slope, stream order, soil texture, land use, groundwater depth, distance from the lake, and runoff depth. A weighted overlay assessment was used to identify probable RWH locations. The analytical hierarchical process was used to weight criteria depending on the study region, hydrological and socioeconomic parameters, and literature. The consistency ratio (CR = 3.16%) was calculated to validate the optimum weights of the comparison components, from which it was found that the weights assigned to each criterion were appropriate for comparative purposes. The results indicated that the optimum location (very high suitability) for RWH is mostly in middle regions of the study area, covering 286 km² (13%), while for the other categories, high suitability is at 23% (498 km²), medium suitability at 29% (636 km²), low suitability at 21% (462 km²), and very low suitability at 14% (305 km²). Sensitivity analysis was used to identify the relative importance of the parameters and determine how each of the nine criteria influences the optimal RWH sites. These findings can assist decision makers and planners in devising strategies to mitigate the effects of climate change and increase any reclaimed area for agriculture.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 3","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-025-02378-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adsorptive removal of phosphate and nitrate by layered double hydroxides through the memory effect and in situ synthesis","authors":"Sarah Mariska,&nbsp;Zhang Jin-Wei,&nbsp;Hoang Huu Chien,&nbsp;Duong Minh Ngoc,&nbsp;Nguyen Duy Hai,&nbsp;Huan-Ping Chao","doi":"10.1007/s13201-024-02332-x","DOIUrl":"10.1007/s13201-024-02332-x","url":null,"abstract":"<div><p>This research examines the efficacy of layered double hydroxides (LDHs) in removing phosphate and nitrate from wastewater, enhanced by the memory effect and <i>in situ</i>synthesis techniques. LDHs were synthesized hydrothermally, initially creating carbonate-based CO₃–LDHs, which were then converted to chloride-based Cl–LDHs through anion exchange. These LDHs underwent calcination at 300 °C, 400 °C, and 500 °C to optimize their structure for enhanced adsorption capabilities. The synthesized LDHs were thoroughly characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET) surface area analysis, and X-ray diffraction (XRD). Adsorption experiments in solutions with pH values between 5, 7, and 9 revealed the adsorption capacities of phosphate and nitrate on the CO₃–LDHs and Cl–LDH, respectively. The results indicated that LDHs calcined at 500 °C showed the highest adsorption performance, achieving maximum capacities of 184 mg/g for phosphate and 70.1 mg/g for nitrate. Kinetic studies confirmed that the adsorption process followed a pseudo-second-order model, demonstrating the effectiveness of the memory effect in enhancing ion exchange. The in situ synthesis of LDHs under controlled conditions significantly improved the removal rates of these anionic contaminants from wastewater, proving the potential of this method for the realistic wastewater treatment.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"15 2","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-024-02332-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143071394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}