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REMOVAL OF BACTERIA IN LABORATORY FILTERS - MODELS AND EXPERIMENTS

WATER RESEARCH 1993年第6期27卷 955-962页

作者： LOGAN, BE HILBERT, TA ARNOLD, RG Environmental Engineering Program Department of Civil Engineering and Engineering Mechanics University of Arizona Tucson AZ 85721 U.S.A.

Five filtration models were used to predict the effect of particle size on removal in several types of laboratory filters (nylon, cellulose and glass fiber). All, models predicted similar trends in removal with particle size, although the capillary-pore model predicted substantially lower removals than the other four fibrous filtration models. These models indicated that bacterium-size (approximately 1 mum) particles are removed in filters primarily through the filtration mechanism of particle interception. Based on advertised pore sizes, removal of bacterium-size particles was a function of filter material in the order cellulose > nylon > glass fiber. The percent of bacteria removed in a nylon filter (5 mum pore diameter) was similar to removal in GF/C filters (1.2 mum pore diameter) as a result of a higher sticking coefficient of bacteria with nylon than with glass. The average sticking coefficients of three bacteria, Pseudomonas sp. JS6, Pseudomonas fluorescens P17 and Bacillus pumilus, in glass fiber (GF/C) filters, were 0.01, 0.24 and 0.20, respectively. These results indicate that filtration models can be used to describe particle removal during laboratory filtration of water and wastewater samples, and that bacteria have relatively high sticking coefficients for filter materials.

关键词： BACTERIA FILTERS FILTRATION WATERS WASTEWATERS

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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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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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Correction to: environmental consequences of interacting effects of changes in stratospheric ozone, ultraviolet radiation, and climate: UNEP environmental Effects Assessment Panel, Update 2024 (Photochemical & Photobiological Sciences, (2025), 24, 3, (357-392), 10.1007/s43630-025-00687-x)

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Photochemical and Photobiological Sciences 2025年第5期24卷 863-865页

作者： Neale, Patrick J. Hylander, Samuel Banaszak, Anastazia T. Häder, Donat-P. Rose, Kevin C. Vione, Davide Wängberg, Sten-Åke Jansen, Marcel A. K. Busquets, Rosa Andersen, Mads P. Sulbæk Madronich, Sasha Hanson, Mark L. Schikowski, Tamara Solomon, Keith R. Sulzberger, Barbara Wallington, Timothy J. Heikkilä, Anu M. Pandey, Krishna K. Andrady, Anthony L. Bruckman, Laura S. White, Christopher C. Zhu, Liping Bernhard, Germar H. Bais, Alkiviadis Aucamp, Pieter J. Chiodo, Gabriel Cordero, Raúl R. Petropavlovskikh, Irina Neale, Rachel E. Olsen, Catherine M. Hales, Simon Lal, Aparna Lingham, Gareth Rhodes, Lesley E. Young, Antony R. Robson, T. Matthew Robinson, Sharon A. Barnes, Paul W. Bornman, Janet F. Harper, Anna B. Lee, Hanna Calderón, Roy Mackenzie Ossola, Rachele Paul, Nigel D. Revell, Laura E. Wang, Qing-Wei Zepp, Richard G. Environmental Research Center Smithsonian Institution EdgewaterMD United States Centre for Ecology and Evolution in Microbial Model Systems Linnaeus University Kalmar Sweden Unidad Académica de Sistemas Arrecifales Universidad Nacional Autónoma de México Puerto Morelos Mexico Erlangen Germany Department of Biological Sciences and Department of Civil and Environmental Engineering Rensselaer Polytechnic Institute TroyNY United States Department of Chemistry University of Turin Turin Italy Department of Marine Sciences University of Gothenburg Gotheburg Sweden School of Biological Earth and Environmental Sciences Environmental Research Institute University College Cork Cork Ireland Chemical and Pharmaceutical Sciences Kingston University London Kingston Upon Thames United Kingdom Civil Environmental & Geomatic Engineering University College London London United Kingdom Department of Chemistry and Biochemistry California State University NorthridgeCA United States Atmospheric Chemistry Observations and Modeling National Center for Atmospheric Research BoulderCO United States USDA UV-B Monitoring and Research Program Colorado State University Fort. CollinsCO United States Department of Environment and Geography University of Manitoba WinnipegMB Canada Working Group Environmental Epidemiology IUF-Leibniz Research Institute for Environmental Medicine Düsseldorf Germany Department of Environment and Health School of Public Health University of Bielefeld Bielefeld Germany School of Environmental Sciences University of Guelph GuelphON Canada Retired From Eawag Swiss Federal Institute of Aquatic Science and Technology Dübendorf Switzerland Center for Sustainable Systems School for Environment and Sustainability University of Michigan Ann ArborMI United States Climate Research Finnish Meteorological Institute Helsinki Finland Indian Academy of Wood Science Bengaluru India Chemical and Biomolecular Engineering North Carolina State University RaleighN

This work is not a product of the U.S. Government or the U.S. environmental Protection Agency, and the author is not doing this work in any governmental capacity. This research was not performed or funded by EPA and was not subject to EPA’s quality system requirements. The views expressed in this journal article are those of the author(s) and do not necessarily represent the views or the policies of the U.S. environmental Protection Agency. The original article has been corrected. © The Author(s), under exclusive licence to the European Photochemistry Association, European Society for Photobiology 2025.

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History and fundamentals of multivariate air duality receptor models

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 1997年第1期37卷 37-42页

作者： Henry, RC [a] Environmental Engineering Program Department of Civil & Environmental Engineering University of Southern California Los Angeles CA 90089-2531 USA

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Photo-oxidative dissolution of CdS(s). The effect of complexing agents

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Chemosphere 1995年第4期31卷 3093-3093页

作者： Davis, A.P. Hsieh, Y.H. Huang, C.P. Environmental Engineering Program Department of Civil Engineering University of Maryland College Park MD 20742 USA Environmental Engineering Program University of Delaware Newark DE 19716 USA

The photo-oxidative dissolution of cadmium sulfide has been investigated in the presence of several complexing organic and inorganic compounds under oxygen-saturated conditions. At pH 4 and 7, aromatic organic ligands enhance the cadmium dissolution rate by a factor of 5–6 over that without the organic present; EDTA, NTA, and citric and oxalic acids have little effect. Sulfite and hydrogen sulfide/bisulfide slightly enhance the dissolution. Conversely, at pH 10, EDTA and NTA produce a significant increase in dissolved cadmium (factor of approximately 18) while the other compounds exert little effect. These phenomena are explained by ligand surface complexation, and both surface and homogeneous ligand-enhanced dissolution.

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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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Intensifying intermittent aeration for optimizing nutrient and hormone removal in vertical-flow constructed wetlands filled with aerated concrete

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Chemosphere 2025年 370卷 143941页

作者： Donato, Mayra Alves de Oliveira Souza, Adelania Pacheco, Amanda de Carvalho Silva, Lucas Svenar, Silvana Nagalli, André Passig, Fernando Hermes Brasil Bernardelli, Jossy Karla Querne de Carvalho, Karina - Civil Engineering Graduate Program. Deputado Heitor de Alencar Furtado St. 5000 Ecoville Paraná Curitiba81280-340 Brazil – Environmental Sciences and Technology Graduate Program. Deputado Heitor de Alencar Furtado St. 5000 Ecoville Paraná Curitiba81280-340 Brazil - Civil Construction Academic Department Deputado Heitor de Alencar Furtado St. 5000 Ecoville Paraná Curitiba81280-340 Brazil - Biology and Chemistry Academic Department. Deputado Heitor de Alencar Furtado St. 5000 Ecoville Paraná Curitiba81280-340 Brazil

Operational strategies have been applied in constructed wetlands to optimize the removal of nutrients and hormones that are still a concern in wastewater treatment. The strategy of intensifying intermittent aeration was investigated in two microcosm-scale vertical-flow constructed wetlands (VFCWs) planted with Eichhornia crassipes onto autoclaved aerated concrete (AC) in the removal of nutrients, estrone (E1), 17β-estradiol (E2) and 17α-ethinylestradiol (EE2). CW-1 (2.4 LO2 min−1) and CW-2 (1.4 LO2 min−1) were fed with synthetic wastewater in sequencing-batch mode (cycles 48-48-72 h) and intermittently aerated for 1 h, followed by 7 h without aeration for 377 days. Combined with the intensification strategy, the use of planted free-floating macrophytes and concrete-based material (emergent) as filtering media stand out as the innovation and originality aspects of this study. Despite the hormone addition, intensifying aeration enhanced the efficiencies since CW-1 achieved the highest removals with 91% COD, 77% TN, 74% TAN, 60% nitrate, and 97% TP in Stage I (no hormone addition) and 90% COD, 80% TN, 93% TAN, 63% nitrate, and 82% TP in Stage II (with hormone addition). CW-1 achieved the highest removal efficiencies of E1 (84%), E2 (95%), and EE2 (73%). Conversely, the efficiencies decreased under the lower aeration rate (in CW-2) for all parameters. Macrophyte uptake and adsorption stood out for TN (>60.25%) and TP (>27.6%) removal as the main mechanisms in the VFCWs. The characteristics of AC favored ion exchange and precipitation, reinforcing the potential of this material as filtering media in VFCWs. Intensification of intermittent aeration combined with hormone addition diverse and riched the microbial community with the presence of Thauera, Lentimicrobium (denitrification), Candidatus Accumulibacter (phosphorus removal), Pseudomonas, Fusibacter, and Azoarcus (EE2 degradation). Intensifying intermittent aeration was an important strategy to enhance the simultaneou

关键词： Wastewater treatment

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An enhanced air permeability model based on stable moisture conditions for nondestructive durability assessment

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Materials and Structures/Materiaux et Constructions 2025年第5期58卷

作者： Nguyen, May Huu Nakarai, Kenichiro Civil and Environmental Engineering Program Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8527 Japan

Concrete carbonation resistance is essential for ensuring durability and extending the service life of concrete structures, as carbonation can lead to the degradation of reinforcing steel and compromised structural integrity. Accurately assessing carbonation resistance through in situ measurements is crucial for evaluating and mitigating potential durability risks over time. Therefore, this study proposes a simple and accurate model for the nondestructive evaluation of concrete carbonation rates under natural conditions. The Torrent air permeability method was applied to measure the changes in the air permeability coefficient, kT, of concrete specimens produced using various cement types, water-to-binder ratios, and initial curing times. The permeability of the concrete, when equilibrated with external environmental conditions, kTe, was predicted based on early-age measurements of kT to determine the concrete carbonation rate, kC. The results indicated that the kTe index achieved a mean ratio between predicted and measured kC values of 1.032, with a low standard deviation of 0.264 and a CoV of 25.5%, indicating high consistency and accuracy compared to conventional air permeability indices. Thus, the proposed method can be applied to effectively predict the carbonation rate under natural exposure conditions, using only early age air permeability measurements. © The Author(s) 2025.

关键词： Damage detection

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MEASUREMENT AND MODELING OF WESTERN WASHINGTON PRECIPITATION CHEMISTRY

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WATER AIR AND SOIL POLLUTION 1985年第1期26卷 71-84页

作者： VONG, RJ LARSON, TV COVERT, DS WAGGONER, AP 1.Environmental Engineering and Science Program Department of Civil Engineering University of Washington WA Seattle 98195 USA

Precipitation was collected and chemically analyzed for a 1 yr period at four sites in western Washington. Spatial and seasonal variabilities in concentrations were identified with the highest concentrations nearest emission sources and in the summer. Multiple correlations among measured species revealed five groupings which were interpreted as the influences of seasalt, metals from a Cu smelter, an urban factor, soil, and acidic sulfate aerosol. A simple washout model predicted that the Cu smelter was the major contributor to a budget for rainwater sulfate. Measurement uncertainties were estimated for each analyte.

关键词： Acid precipitation Air pollution monitoring Copper smelter Emission Sulfate Washington (western)

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