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Advanced landfill leachate treatment: Sequential electrocoagulation and electrooxidation system for efficient remediation

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Journal of Water Process engineering 2025年 74卷

作者： Justen, Nicóli Borba, Fernando H. Mayer, Ildemar Seibert, Daiana Inticher, Jonas J. Ferreira Piazzi Fuhr, Ana C. Carissimi, Elvis Leichtweis, Jandira Postgraduate Program of Environment and Sustainable Technologies Federal University of Fronteira Sul Av. Jacob Reinaldo Haupenthal 1580 RS Cerro Largo 97900-000 Brazil Postgraduate Program of Chemical Engineering West Paraná State University Rua da Faculdade 645 Jd. Santa Maria PR Toledo 85903-000 Brazil Materials Science and Engineering Graduate Program Federal University of Pelotas 1 Gomes Carneiro St. RS Pelotas 96010-610 Brazil Department of Sanitation and Environmental Engineering Federal University of Santa Maria Av. Roraima 1000 RS Santa Maria 97105-000 Brazil

The treatment of concentrated landfill leachate generated by nanofiltration and reverse osmosis processes represents a significant challenge. This concentrate is characterized by high concentrations of heavy metals, contaminants of emerging concern, dissolved salts, and organic compounds. In this study, a novel advanced treatment system integrating an Electrocoagulation Reactor with a subsequent electrooxidation process was proposed. Two anode/cathode arrangements were evaluated: electrocoagulation followed by electrooxidation with “boron-doped diamond” and steel electrodes, and electrocoagulation followed by electrooxidation with “boron-doped diamond” and aluminum electrodes, focusing on their effectiveness in degrading contaminants and improving the quality of the treated concentrated landfill leachate. In order to monitor the efficiency of the electrocoagulation process and integrated systems, the degradation of the physicochemical parameters of absorbance at 254 nm, total organic carbon, and turbidity were investigated. Within the best performance, acute toxicity indices (Artemia salina - LC50) were determined and possible degradation and/or formation of contaminants of emerging concern were identified by gas chromatography–mass spectrometry (GC–MS). The results indicated the mineralization of 73 % of total organic carbon and 25 % of total nitrogen, an increase in the biodegradability fraction (BOD5/COD) of the concentrated landfill leachate from 0.18 to 0.35, as well as a significant reduction in toxicity (LC50 of 54.4 %), demonstrated by Artemia salina bioassays. The reduction in toxic potential was also observed in the by-product analysis by GC–MS, which indicated the removal of emerging contaminants such as benzene, 2-(2-methoxy-1-propenyl)-1,3,5-trimethylbenzene, benzothiazole, 2-(methylthio) and phenol, 2,2′-methylenebis[6-(1,1-dimethylethyl)-4-methyl-. These findings highlight that the integration of the electrocoagulation process with electrooxidation us

关键词： Concentrated landfill leachate Contaminants of emerging concern Electrocoagulation Electrooxidation

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Carbon dioxide, global boiling, and climate carnage, from generation to assimilation, photocatalytic conversion to renewable fuels, and mechanism

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Science of the Total Environment 2025年 965卷 178629页

作者： Khan, Muhammad Sun, Xiaohui Zada, Amir Azizi, Shohreh Shah, Muhammad Ishaq Ali Khan, Javed Ali Ragab, Ahmed H. Taher, Mostafa A. Abbas, Qumber Han, Changseok College of Civil and Transportation Engineering Shenzhen University 3688 Nanhai Avenue Guangdong Province Shenzhen518060 China Department of Chemistry Abdul Wali Khan University Mardan Mardan23200 Pakistan UNESCO-UNISA Africa Chair in Nanosciences and Nanotechnology College of Graduate Studies University of South Africa Muckleneuk Ridge PO Box 392 Pretoria0002 South Africa Chemistry Department Faculty of Science King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia Biology Department Faculty of Science and Arts King Khalid University Mohail Assir 61321 Saudi Arabia Department of Technologies and Installations for Waste Management Faculty of Energy and Environmental Engineering Silesian University of Technology Gliwice44-100 Poland Program in Environmental and Polymer Engineering of INHA University 100 Inha-ro Michuhol-gu Incheon22212 Korea Republic of Department of Environmental Engineering INHA University 100 Inha-ro Michuhol-gu Incheon22212 Korea Republic of

The increasing CO2 concentration in the atmosphere has substantial impacts on the global temperature. For energy sustainability and minimization of the effects of global warming, an approach to understand CO2 capturing and a carbon neutral culture is extremely essential in the present circumstances. The CO2 emission from vehicles and industries can be minimized using energy cost-effective techniques and can be converted more selectively into reusable fuels via thermochemical, electrochemical, photochemical, photocatalytic, electrocatalytic, biological and inorganic carbonate-based approaches. In this review article, we have discussed the effects of increased global temperature on human beings, economy and climate change. Further, we have discussed the photocatalytic conversion of CO2 (PC-CO2) into gaseous and liquid fuels under solar light driven photocatalysis. The adsorption and activation of CO2, its conversion into various intermediates, their stability and selectivity of the final products have been elaborated comprehensively. The conversion mechanisms of CO2 into CO, CH4, alcohol, aldehyde and carboxylic acid have been discussed in detail. The role of defects and exposed facets of photocatalysts, effect of metal and non-metal dopants, and the additive role of co-catalyst on the mechanisms and selectivity of the conversion products have been discussed comprehensively. Finally, future perspective is discussed to highlight the research gap in the PC-CO2. We hope that this article will help to understand the mechanisms of PC-CO2 and will direct researchers to add their role in the reduction of CO2 to control global warming and make life easier on earth in the coming years. © 2025 Elsevier B.V.

关键词： Kyoto Protocol

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PHYSIO-CHEMICAL AND ECOLOGICAL MODELING THE FATE OF TOXIC-SUBSTANCES IN NATURAL-WATER SYSTEMS

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ECOLOGICAL MODELLING 1984年第1-4期22卷 145-170页

作者： THOMANN, RV Environmental Engineering and Science Graduate Program Manhattan College Bronx NY 10471 U.S.A.

A basic framework for the modeling of the fate of chemicals in natural water systems is presented. Both the physical/chemical and ecological fate of the substance are considered. The fully time variable equations do not present any significant insight into the general behavior of chemical fate. However, under a steady state assumption and including bottom sediment interactions, relatively simple formulations result that permit rapid calculation of the maximum concentrations that might be expected. It is shown that for a completely mixed lake the ratio of the areal loading rate of the toxicant to the water column concentration is determined by the hydraulic overflow rate and the net loss rate of the toxicant from the water column. Thus, c T = W Ta /q + w T for c T as the total toxicant concentration, W Ta as the areal loading rate of the chemical, q as the hydraulic overflow rate, and w T the net loss of the chemical. The net loss rate w T is a function of all water column and sediment decay rates and interactions. The steady state food chain model of the accumulation of a toxic chemical from both water and food sources is shown to be a means for estimating the parameters of loss and sediment interaction for a lake. The steady state case of the discharge of a chemical into a stream provides a simple means for estimating net loss rates under some reasonable assumptions. Also coupling the food chain model to the physio-chemical model permits the use of chemical concentrations in the fish to estimate the net loss of toxicant in a stream. Application is made to metals concentrations in Lakes Ontario and Michigan and to 1,4 dichlorobenzene in Lake Zurich. The theory indicates that under zero decay of the chemical in the sediment and equal partition coefficients in the sediment and the water column that the chemical in particulates form in the sediment should equal that in the water column. Metals data for Lake Ontario appears to confirm this result at least to order of ma

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By-products of Baru and Monguba: A review of their potential

Food and Humanity

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Food and Humanity 2025年 4卷

作者： Miranda, Bruna Melo Tovar, Beatriz Carolina Alvez Otero, Deborah Murowaniecki da Silva, Flávio Alves Scalize, Paulo Sergio de Oliveira, Tatianne Ferreira Department of Food Science Nutrition School Federal University of Bahia Canela Campus Bahia Salvador Brazil Department of Food Engineering Agronomy School Federal University of Goiás Goiás Goiânia Brazil Institute of Experimental Biology Faculty of Sciences Central University of Venezuela Caracas Venezuela Graduate Program in Food Science Faculty of Pharmacy Federal University of Bahia Campus Ondina Bahia Salvador Brazil Graduate Program in Food Nutrition and Health Nutrition School Federal University of Bahia Campus Canela Bahia Salvador Brazil School of Civil and Environmental Engineering Federal University of Goiás Goiás Goiânia Brazil

During food processing, large amounts of waste are generated, which compromise the environment and society. The valorization of agri-food by-products has been investigated as a solution to obtain clean energy and value-added materials, improving food security and production profitability. This research focuses on the by-products of baru (Dipteryx alata Vog.) and monguba (Pachira aquatica Aubl.), discussing their applications and biotechnological perspectives. A critical review of the parameters related to the valorization of these by-products was conducted, using publications from 2013 to 2023, prioritizing studies that presented new knowledge. An increase in publications on the topic was observed starting in 2020, with Brazil leading, followed by India, Portugal, and Singapore. Although still underexplored, eight areas of knowledge were identified, with emphasis on food science and chemistry. Monguba lacks technological exploitation and economic value, while baru, despite being more documented, remains underutilized. Both fruits have fractions (epicarp, mesocarp, and endocarp) that are often considered waste but are of scientific interest. The mesocarp of baru is rich in proteins, lipids, carbohydrates, and phenolic compounds with high antioxidant capacity. The by-products of baru and monguba can be used in the extraction of nutraceutical compounds, in the transformation into biomaterials for water impurity removal, in renewable energy production, in food enrichment, and as ingredients in animal feed, improving the quality of eggs and meat. The use of these by-products offers economic and environmental advantages, reducing contamination caused by the improper disposal of agro-industrial waste. It is essential to promote their commercial exploitation and potential applications. © 2024 Elsevier B.V.

关键词： Bioactive compounds Biomaterials By-products application Functional foods Residues recovery Sustainable agriculture

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Application of machine learning technique for predicting and evaluating chloride ingress in concrete

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Frontiers of Structural and Civil engineering 2022年第9期16卷 1153-1169页

作者： Van Quan TRAN Van Loi GIAP Dinh Phien VU Riya Catherine GEORGE Lanh Si HO Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

The degradation of concrete structure in the marine environment is often related to chloride-induced corrosion of reinforcement ***,the chloride concentration in concrete is a vital parameter for estimating the corrosion level of reinforcement *** research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting(GB),artificial neural network(ANN),and random forest(RF)in combination with particle swarm optimization(PSO).The input variables for modeling include exposure condition,water/binder ratio(W/B),cement content,silica fume,time exposure,and depth of *** results indicate that three models performed well with high accuracy of prediction(R2⩾0.90).Among three hybrid models,the model using GB_PSO achieved the highest prediction accuracy(R2=0.9551,RMSE=0.0327,and MAE=0.0181).Based on the results of sensitivity analysis using SHapley Additive exPlanation(SHAP)and partial dependence plots 1D(PDP-1D),it was found that the exposure condition and depth of measurement were the two most vital variables affecting the prediction of chloride *** the number of different exposure conditions is larger than two,the exposure significantly impacted the chloride content of concrete because the chloride ion ingress is affected by both chemical and physical *** study provides an insight into the evaluation and prediction of the chloride content of concrete in the marine environment.

关键词： gradient boosting random forest chloride content concrete sensitivity analysis

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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Frontiers of Structural and Civil engineering 2023年第2期17卷 284-305页

作者： Hai-Van Thi MAI May Huu NGUYEN Son Hoang TRINH Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

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Frontiers of Structural and Civil engineering 2022年第8期16卷 990-1002页

作者： Hai-Bang LY Thuy-Anh NGUYEN Binh Thai PHAM May Huu NGUYEN Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

This study examined the feasibility of using the grey wolf optimizer(GWO)and artificial neural network(ANN)to predict the compressive strength(CS)of self-compacting concrete(SCC).The ANN-GWO model was created using 115 samples from different sources,taking into account nine key SCC *** validation of the proposed model was evaluated via six indices,including correlation coefficient(R),mean squared error,mean absolute error(MAE),IA,Slope,and mean absolute percentage *** addition,the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence *** results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s *** that,an examination of the parameters impacting the CS of SCC was provided.

关键词： artificial neural network grey wolf optimize algorithm compressive strength self-compacting concrete

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Implications of technological improvement and circular agriculture on environmental sustainability of sugarcane production

Cleaner Environmental Systems

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Cleaner environmental Systems 2025年 18卷

作者： Aakriti Deuja Min Hein Khant Thapat Silalertruksa Shabbir H. Gheewala Trakarn Prapaspongsa Graduate Program in Environmental and Water Resources Engineering Department of Civil and Environmental Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand Department of Environmental Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand The Joint Graduate School of Energy and Environment King Mongkut's University of Technology Thonburi Bangkok Thailand Centre of Excellence on Energy Technology and Environment Ministry of Higher Education Science Research and Innovation Bangkok Thailand

The spatially differentiated environmental impacts and associated costs of technological improvement and circular agricultural practices in sugarcane production were assessed. Analysis of the cause-effect relationship between the key processes and substances each helped develop alternative scenarios for impact reduction. PM 2.5 emissions contributed to 92 % of the total human health impacts from open burning of field residues. Freshwater ecotoxicity, mainly due to ametryn emissions from pesticide application, contributed to 47 % of the total damage to the ecosystem. The environmental costs were 116 % higher than the value of sugarcane production, signifying the critical importance of adopting alternative pathways that provide economic benefits from environmental cost reduction compared to the production value. Scenarios considering green cane harvesting and waste management approaches demonstrated high potential for total impact reduction of 99 % and 97 %, respectively, and economic gains of 202 and 225 billion THB, respectively (5.76 and 6.42 billion USD, respectively). The economic benefits of waste utilization were 137 % higher than the value of sugarcane production, demonstrating the potential benefits of product substitution to help mitigate impacts. The core findings highlight the significance of the PM 2.5 impact-related external costs and underscore the benefits of adopting green cane harvesting in conjunction with on-field waste utilization to mitigate the impact of open burning and produce value-added products. Technological improvement and circular agricultural practices coupled with valuation of spatially differentiated impacts can provide useful and more accurate information to policymakers, to prioritize the implementation of mitigation strategies for enhancing the environmental sustainability of sugarcane production.

关键词： Life cycle assessment On-site and supply chain emissions Human health Ecosystem environmental cost environmental sustainability

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Machine learning-based analysis on factors influencing blood heavy metal concentrations in the Korean CHildren's environmental health Study (Ko-CHENS)

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Science of the Total Environment 2025年 978卷

作者： Jung, Seowoo Shah, Surabhi Oh, Jongmin Bang, Yoorim Lee, Ji Hyen Kim, Hwan-Cheol Jeong, Kyoung Sook Park, Huibyeol Lee, Eun-Kyung Hong, Yun-Chul Ha, Eunhee Department of Statistics Ewha Womans University Seoul Korea Republic of Department of Environmental Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Department of Human Systems Medicine College of Medicine Seoul National University Seoul Korea Republic of College of Medicine Ewha Womans University Seoul Korea Republic of Institute for Development and Human Security Ewha Womans University Seoul Korea Republic of Department of Pediatrics College of Medicine Ewha Womans University Seoul Korea Republic of Department of Occupational and Environmental Medicine College of Medicine Inha University Hospital Inha University Incheon Korea Republic of Department of Occupational and Environmental Medicine Wonju College of Medicine Wonju Severance Christian Hospital Yonsei University Wonju Korea Republic of Environmental Health Research Division National Institute of Environmental Research Incheon Korea Republic of Institute of Environmental Medicine Medical Research Center Seoul National University Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Ewha Medical Research Institute College of Medicine Seoul Korea Republic of

Heavy metal concentration in pregnant women affects neurocognitive and behavioral development of their infants and children. The majority of existing research focusing on pregnant women's heavy metal concentration has considered individual environmental factor. In this study, we aim to comprehensively consider lifestyle, food, and environmental factors to determine the most influential factor affecting heavy metal concentration in pregnant women. The Ko-CHENS (Korean CHildren health and environmental Study) is a nationwide prospective birth cohort study in South Korea enrolling pregnant women from 2015 to 2020. A total of 5458 eligible pregnant women were included in this study, and 897 variables were included in questionnaire comprising: maternal general information, indoor and living environment, dietary habits, health behavior, exposure to chemicals. Lead, cadmium and mercury concentration on blood were measured in early, late pregnancy and in cord blood at birth. Variables that might be related to heavy metal concentrations were included in machine learning models. Random forest and XGBoost machine learning models were conducted for predictions. Both models had similar but better performance than multiple linear regression. Kimchi (β = 1.55), seaweed (β = 0.40), fatty fish (β = 1.55), intakes respectively affected lead, cadmium, and mercury exposure through early, late pregnancy and cord blood. © 2025

关键词： Obstetrics

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A short climatology of black and brown carbon and their sources at a suburban site impacted by smoke in Brazil

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Journal of environmental Sciences 2024年第2期136卷 498-511页

作者： Admir Creso Targino Patricia Krecl Gabriel Yoshikazu Oukawa Eva Maria Mollinedo Graduate Program in Environmental Engineering Federal University of TechnologyAv.Pioneiros 3131LondrinaPR 86036-370Brazil Department of Environmental Engineering Federal University of TechnologyAv.Pioneiros 3131LondrinaPR 86036-370Brazil

Emissions from biomass burning challenge efforts to curb air pollution in cities downwind of fire-prone regions,as they contribute large amounts of brown carbon(Br C)and black carbon(BC)*** investigated the patterns of Br C and BC concentrations using Aethalometer data(atλ=370 and 880 nm,respectively)spanning four years at a site impacted by the outflow of *** data required to be post processed for the shadowing effect since,without correction,concentrations would be between 29%and 35%*** Br C concentrations were consistently higher than the BC concentrations,indicating the prevalence of aerosols from biomass *** results were supported by the Angstrom coefficient(A_(370/880)),with values predominantly larger than 1(mean±standard deviation:1.25±0.31).A_(370/880)values below 1 were more prevalent during the wet season,which suggests a contribution from fossil fuel *** observed sharp Br C and BC seasonal signals,with mean minimum concentrations of 0.40μg/m^(3)and 0.36μg/m^(3),respectively,in the wet season,and mean maximum concentrations of 2.05μg/m^(3)and 1.53μg/m^(3)in the dry *** largest concentrations were observed when northerly air masses moved over regions with a high density of fire *** burning of residential solid waste and industrial combustion caused extreme Br C and BC concentrations under favourable wind *** neither pollutant is included in any ambient air quality standards,our results suggest that transboundary smoke may hamper efforts to meet the World Health Organization guidelines for fine particles.

关键词： Light-absorbing carbonaceous matter Black carbon Wildfires Biomass burning Aethalometer

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