Clean-soil Air Water最新文献

{"title":"Artificial neural network model for extracting knowledge from the electro-Fenton process for acid mine wastewater treatment","authors":"Anoop Kumar Maurya,&nbsp;Pasupuleti Lakshmi Narayana,&nbsp;Uma Maheshwera Reddy Paturi,&nbsp;Subba Reddy Nagireddy Gari","doi":"10.1002/clen.202400029","DOIUrl":"10.1002/clen.202400029","url":null,"abstract":"<p>In this study, artificial neural networks (ANNs) were employed to analyze the complex interactions between electro-Fenton (EF) process variables (plate spacing, current intensity [CI], initial pH, aeration rate) and the Fe(II) and Mn(II) removal efficiency from wastewater. After experimenting with 69 different ANN architectures, the 4-8-8-2 architecture was identified as more efficient, achieving higher accuracy (adj. <i>R</i>² of 0.93 for Fe(II) and 0.96 for Mn(II)) than the published model. The research provides valuable insights into the correlation between EF process parameters and removal efficiency, guiding the optimization of wastewater treatment processes. Sensitivity analysis revealed that CI significantly affects Mn(II) and Fe(II) removal efficiency. A user-friendly graphical interface was created based on the synaptic weights of the best model to enable practical predictions. It is designed to be accessible even to users without programing experience.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of using a specially designed sludge draw-off pipe for circular secondary clarifiers to mitigate underflow short-circuiting","authors":"Emre Koken,&nbsp;Nurdan Buyukkamaci","doi":"10.1002/clen.202300151","DOIUrl":"10.1002/clen.202300151","url":null,"abstract":"<p>Short-circuiting in secondary clarifiers is a well-known problem that can occur through up-flow or underflow routes. The underflow short-circuiting is not as visible as up-flow short-circuiting but can affect clarifier performance. The energy-dissipating inlet (EDI) is a type of inlet structure that is used in secondary clarifiers to dissipate the energy of larger influent volumes, allowing clarifiers to operate at higher treatment capacities. The underflow short-circuiting is encountered particularly in clarifiers equipped with EDIs. As influent volume increases, conventional draw-off pipes cannot handle high sludge capacities, deforming the sludge blanket and leading to lower concentration of solids being withdrawn. Retrofitting the design of draw-off pipes is an effective way to mitigate underflow short-circuiting and enhance treatment performance. In this study, a snail-shaped sludge draw-off pipe was designed and tested in two types of EDIs using computational fluid dynamics tools, showing a 20% increase in withdrawn sludge concentration and mitigating underflow short-circuiting potential. The optimal retrofit option was identified as equipping the clarifier with a snail-shaped draw-off pipe and an innovative EDI, known as multilayer EDI column, which would save almost half of the energy and operational costs of the biological processes while meeting discharge limits.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clen.202300151","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 stage‐discharge and sediment‐discharge relationships in data‐scarce Himalayan River Basin Dhauliganga, Central Himalaya, using neural networks","authors":"Kuldeep Singh Rautela, Vivek Gupta, Juna Probha Devi, Lone Rafiya Majeed, Jagdish Chandra Kuniyal","doi":"10.1002/clen.202300388","DOIUrl":"https://doi.org/10.1002/clen.202300388","url":null,"abstract":"This study focuses on the hydro‐sedimentological characterization and modeling of the Dhauliganga River in Uttarakhand, India. Field data collected from 2018–2020, including stage, velocity, and suspended sediment concentration (SSC), showed notable variations influenced by melting snow, glaciers, and precipitation. Challenges in accurately modeling rivers with a topography and sparse gauging stations were addressed using artificial neural networks (ANN). The calibrated models precisely predicted stage‐discharge and sediment‐discharge relationships, demonstrating the effectiveness of machine learning, particularly ANN‐based modeling, in such challenging terrains. The model's performance was assessed using coefficient of determination (<jats:italic>R</jats:italic><jats:sup>2</jats:sup>), root mean square error (RMSE), and mean square error (MSE). During the calibration phase, the model exhibited notable performance with <jats:italic>R</jats:italic><jats:sup>2</jats:sup> values of 0.96 for discharge and 0.63 for SSC, accompanied by low RMSE values of 5.29 cu m s<jats:sup>–1</jats:sup> for discharge and 0.61 g for SSC. Subsequently, in the prediction phase, the model maintained its robustness, achieving <jats:italic>R</jats:italic><jats:sup>2</jats:sup> values of 0.97 for discharge and 0.63 for SSC, along with RMSE values of 5.67 cu m s<jats:sup>–1</jats:sup> for discharge and 0.68 g for SSC. The study also found a strong agreement between water flow estimates derived from traditional methods, ANN, and actual measurements. The suspended sediment load, influenced by both water flow and SSC, varied annually, potentially modifying aquatic habitats through sediment deposition, and altering aquatic communities. These findings offer crucial insights into the hydro‐sedimentological dynamics of the studied river, providing valuable applications for sustainable water‐resource management in challenging terrains and addressing environmental concerns related to sedimentation, water quality, and aquatic ecosystem.","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"41 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"C, N, and P contributions to sediments of two Venezuelan coastal lagoons and their relationships with the adsorption of P","authors":"Danilo López-Hernández,&nbsp;Leidy Morales,&nbsp;Karelys Umbría-Salinas,&nbsp;Astolfo Valero,&nbsp;Williams Melendez,&nbsp;Ana López-Contreras","doi":"10.1002/clen.202300266","DOIUrl":"10.1002/clen.202300266","url":null,"abstract":"<p>In Unare and Píritu Coastal Lagoons, a study was carried out to assess the effect of C, N, and P load contributions on the capability of the sediments to immobilize phosphates. To achieve the later, the geochemical data of the sediments were coupled to the P-sorption index of Bache and Williams (IBW). In both lagoons, the sediments showed a pH &gt; 7 because of calcareous sedimentation. The inorganic carbon values in the lagoons displayed a spatial distribution with higher concentrations toward the shores, that is defined by the carbonate lithology. On the contrary, the inner part of the lagoons was characterized by the presence of organic materials associated to the clay. The phosphorus content in the Unare Lagoon ranged from 290 to 625 mg kg⁻¹, whereas in the Píritu Lagoon the values fluctuated between 213 and 1013 mg kg⁻¹. The highest concentrations of phosphorus in both lagoons could be linked to sewage and runoff input from agricultural and livestock activities around the lagoon systems. The IBW displayed adsorption average values of 21.97 and 27.42 for Unare and Píritu Lagoon, respectively, corresponding to a rather low P sorption. In Unare Lagoon, the IBW showed positive correlations with C, N and Fe_labile but negative with P. However, in the Píritu Lagoon, despite the analogous lithology of the lagoons, a slightly positive non-significative correlation between IBW and IC was only found. Although the sediments adsorb P with a rather low capacity, they can mitigate the eutrophication process in the studied lagoons.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Information: Clean Soil Air Water. 8/2024","authors":"","doi":"10.1002/clen.202470081","DOIUrl":"https://doi.org/10.1002/clen.202470081","url":null,"abstract":"","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 8","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clen.202470081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Exposure assessment of severe acute respiratory syndrome coronavirus 2 and norovirus genogroup I/genogroup II in aerosols generated by a municipal wastewater treatment plant","authors":"José Gonçalves,&nbsp;Andrés Felipe Franco,&nbsp;Priscilla Gomes da Silva,&nbsp;Elisa Rodriguez,&nbsp;Israel Diaz,&nbsp;Maria José González Peña,&nbsp;João R. Mesquita,&nbsp;Raul Muñoz,&nbsp;Pedro Garcia-Encina","doi":"10.1002/clen.202300267","DOIUrl":"https://doi.org/10.1002/clen.202300267","url":null,"abstract":"<p>The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater and its potential as an airborne transmission source require extensive investigation, particularly in wastewater treatment plants (WWTPs), where few studies have been conducted. The aim of this study was to investigate the presence of SARS-CoV-2 and norovirus (NoV) RNA in wastewater and air samples collected from a municipal WWTP. In addition, the study assessed the potential risk of viral exposure among WWTP employees. In both the summer and winter campaigns of this study, SARS-CoV-2 and NoV RNA were quantified in wastewater/sludge samples other than effluent. Viral RNA was not detected in any of the air samples collected. The exposure risk assessment with the SARS-CoV-2 RNA concentrations in the influent pumping station of this study shows a lower risk than the calculation with the historical data provided by AquaVall, but both show a low-to-medium exposure risk for the WWTP workers. The sensitivity analysis shows that the result of the model is strongly influenced by the SARS-CoV-2 RNA quantification in the wastewater. This study underscores the need for extensive investigations into the presence and viability of SARS-CoV-2 in wastewater, especially as a potential airborne transmission source within WWTPs.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 9","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clen.202300267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Concentrations and health risk assessment of selected cations and anions in drinking water in Antalya, Türkiye","authors":"Murat Kilic","doi":"10.1002/clen.202300451","DOIUrl":"10.1002/clen.202300451","url":null,"abstract":"<p>This study investigates the potential health risks associated with ion concentrations in fountains used for drinking water in the Antalya/Konyaaltı tourism center region. A total of 32 fountain samples commonly used during the summer were analyzed to determine the anion and cation concentrations using ion chromatography equipped with a conductivity detector. The results showed high accuracy and reliability, with <i>R</i>² values ranging between 0.998 and 0.999 and recovery values between 97% and 110% at low and high concentrations. The method detection limit and method quantification limit were determined as 0.004 and 0.276, respectively, whereas the pH values ranged from 6.71 to 7.69. When examining the average fluoride and nitrate levels in different age groups, the nitrate daily acceptable intake (total hardness index) values were found to be 0.175, 0.091, and 0.076 µg kg⁻¹ body weight per day for children, adolescents, and adults, respectively. Overall, the study suggests that children have the highest exposure levels due to their lower body weight, and exposure levels decrease with increasing age.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 9","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Arsenic and zinc concentrations in wheat grains under soil zinc application and arsenic-contaminated irrigation","authors":"Ammara Basit,&nbsp;Shahid Hussain","doi":"10.1002/clen.202300106","DOIUrl":"10.1002/clen.202300106","url":null,"abstract":"<p>Above-permissible levels of arsenic (As) in irrigation water lead to toxic levels in wheat grains, increasing health risks for humans. In this study, two zinc (Zn)-biofortified wheat (<i>Triticum aestivum</i> L.) cultivars (Akbar-2019 and Zincol-2016) were grown in pots with two Zn application rates (0 and 8 mg Zn kg⁻¹) and three levels of As in irrigation water (distilled-water control, 100 and 1000 µg As L⁻¹). Irrigation with As-contaminated water decreased dry matter yields, concentrations of grain phosphorus (P) and Zn, and estimated daily intake (EDI) of Zn. Conversely, it increased grain As concentration and As EDI. Soil Zn application mitigated the negative effects of As on dry matter yields of both cultivars while simultaneously enhancing grain Zn concentration and Zn EDI. On average, Zn application increased grain Zn concentration by 114% compared to no Zn application. Additionally, Zn application decreased grain As concentration at all As levels. In conclusion, this study suggests that applying Zn to Zn-biofortified wheat irrigated with As-contaminated water can mitigate the toxic effects of As on wheat. It increase Zn concentration and decrease As concentration in wheat grains, which is vital for enhancing grain quality for human consumption.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 9","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141932480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of temporal and spatial variations of water quality parameters in the Zarafshan River basin","authors":"Shobegim Shoergashova,&nbsp;Tie Liu,&nbsp;Nigora Ibrokhimova,&nbsp;Liliya Latisheva,&nbsp;Bakhtiyor Karimov","doi":"10.1002/clen.202300454","DOIUrl":"10.1002/clen.202300454","url":null,"abstract":"<p>River ecosystems in Central Asia face significant stress from environmental changes and pollution. This study assesses temporal and spatial variations in water quality parameters within the Zarafshan River Basin using retrospective data and field measurements. Water quality indicators, including electrical conductivity (EC), total suspended solids (TSS), ammonium nitrogen (N-NH₄), nitrite nitrogen (N-NO₂), nitrate nitrogen (N-NO₃), temperature (<i>T</i>), chemical oxygen demand (COD), dissolved oxygen (DO), and discharge, were analyzed using the Pearson's correlation coefficient and ANOVA, with the Mann–Kendall (MK) test detecting trends over time. Obtained results indicate significant seasonal effects with elevated TSS during summer, increasing sediment load and changing aquatic habitats. The strong inverse correlation (–0.89) between DO and N-NH₄ signifies ecological challenges particularly in low DO concentrations during summer (3.25 mg L^–1). Long-term analysis identifies Navoiazot chemical factory as a major pollution hotspot. Spatial analyses based on extended sampling have revealed the Siab and Dargom canals and Samarkand City as major pollution sources of elevated N-NO₂ and COD, respectively. Trends at various gauging stations (MK-test) show increasing EC (<i>τ</i> = 0.72) and N-NH₄ (<i>τ</i> = 0.46) levels, with decreasing TSS, N-NO₃, <i>T</i>, and COD levels over time. Recommendations include targeted measures to reduce pollution at the Navoiazot factory and downstream, introducing sustainable agriculture practices, increasing public awareness for environmental conservation, and improving urban wastewater treatment to meet water quality requirements for different users.</p>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"52 8","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141867813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of different machine learning algorithms for prediction of nitrate in groundwater in Thiruvannamalai District","authors":"Christina Jacob, Uma Shankar Masilamani","doi":"10.1002/clen.202400060","DOIUrl":"https://doi.org/10.1002/clen.202400060","url":null,"abstract":"The prevalence of nitrates (NO<jats:sub>3</jats:sub><jats:sup>−</jats:sup>) in groundwater due to the extensive application of fertilizers and anthropogenic sources pollutes the groundwater. Machine learning (ML) techniques are now being increasingly deployed to achieve high precision in predicting water quality. This study assesses the efficacy of nine distinct ML algorithms, namely, linear regression, polynomial regression, decision tree, random forest (RF), support vector machine, multilayer perceptron regressor, eXtreme gradient boosting (XGB), light gradient boosting (LGB), and K‐nearest neighbors to predict nitrate concentration in the groundwater in Thiruvannamalai District, Tamil Nadu. Overall, 360 water samples for 1 year and 14 groundwater variables were determined to predict nitrate. Performance evaluation metrics such as root mean square error (RMSE), moving average error (MAE), and correlation coefficient (<jats:italic>R</jats:italic><jats:sup>2</jats:sup>) were evaluated for pre‐monsoon, monsoon, and post‐monsoon seasons. For all three seasons, RF predicted the nitrate concentration with low values of RMSE, MAE, and higher values of <jats:italic>R</jats:italic><jats:sup>2</jats:sup>. The results show values for RF with: RSME: 0.49, MAE: 1.30, and <jats:italic>R</jats:italic><jats:sup>2</jats:sup>: 0.94, which has a higher prediction tailed by LGB and XGB and is true for all the seasons. The results from the study will aid the policymakers in planning the strategy for remediation.","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"8 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}