The role of particle size on the reduction of granular activated carbon (GAC) adsorption capacity for trace organic contaminants by dissolved organic matter (DOM) is examined and applied to performance scale-up. The adsorption capacity reduction, termed fouling, must be scalable in order to use bench scale tests, such as the rapid small-scale column test (RSSCT) to predict full-scale breakthrough. Equilibrium adsorption capacity tests with GAC preloaded with DOM and RSSCT breakthrough curves at three different GAC particle sizes indicate that GAC adsorption capacity is dependent on GAC particle size when DOM is present. Thus, the RSSCT cannot be expected to match full-scale results regardless of which RSSCT design approach is used (constant or proportional diffusivity), unless a scaling factor is applied to the results. Proportional diffusivity RSSCT breakthrough curves demonstrate that surface concentration of DOM is not a good measure of fouling. It is hypothesized that pore blockage is the mechanism responsible for the dependence on particle size. As GAC particle size increases, the microporous surface area behind a constricted pore also increases. The result is lower adsorption capacity per mass of adsorbent in the larger GAC particles. A scaling methodology for equilibrium and breakthrough data is presented that accounts for the dependence of NOM preloading effects on GAC particle diameter.
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Sci Rep
December 2024
College of Resources and Environment, Gansu Agricultural University, Lanzhou, 730070, China.
Cadmium pollution in water is becoming increasingly serious. Thus, the effective removal of Cd(II) from water has garnered attention. Aluminum hydroxide-modified attapulgite (ATP-AC) was prepared from basic aluminum acetate through a coprecipitation method that could efficiently adsorb Cd(II) in aqueous solution.
View Article and Find Full Text PDFEnviron Res
December 2024
College of Materials Science and Engineering, Fuzhou University, Fuzhou 350116, PR China. Electronic address:
This work developed a novel oxidized hierarchical porous carbon (OHPC) with vesicule-like ultrathin graphitic walls via a method of air oxidation and used as an efficient adsorbent for Congo red (CR) and Malachite green (MG) removal. Results show that the OHPC2 oxidized at 400 °C possesses three-dimensional hierarchical pores with vesicule-like ultrathin graphitic walls. The prepared OHPC2 not only has a large specific surface area of 1020 m g with a high pore volume, but also has abundant oxygen-containing functional groups.
View Article and Find Full Text PDFEnviron Res
December 2024
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China; State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil& Water Pollution, College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China.
To develop an efficient and cost-effective adsorbent for phosphate removal from water bodies, this study utilized natural red clay (RC) as a carrier. The modified red clay (MRC) was prepared through three methods: acid modification, high-temperature calcination, and metal loading. The preparation conditions were optimized, and the adsorption effects on phosphate were compared across these different modifications.
View Article and Find Full Text PDFChemosphere
December 2024
College of Land Science and Technology, China Agricultural University, Beijing 100193, PR China. Electronic address:
Heavy metals released from metallic sulfidic tailings pose significant environmental threats by contaminating surface and groundwater in mining areas. Sustainable rehabilitation methods are essential to remove or stabilize these metals, improving the quality of acid mine drainage and minimizing pollution. This study examines the adsorption capacity of zinc ions (Zn) by different iron-silicate mineral groups under natural weathering and bacteria-regulated weathered conditions.
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December 2024
Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, USA. Electronic address:
Phosphate (PO(III)) contamination in water bodies poses significant environmental challenges, necessitating efficient and accurate methods to predict and optimize its removal. The current study addresses this issue by predicting the adsorption capacity of PO(III) ions onto biochar-based materials using five probabilistic machine learning models: eXtreme Gradient Boosting LSS (XGBoostLSS), Natural Gradient Boosting, Bayesian Neural Networks (NN), Probabilistic NN, and Monte-Carlo Dropout NN. Utilizing a dataset of 2952 data points with 16 inputs, XGBoostLSS demonstrated the highest R (0.
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