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      Facile fabrication of dolomite-doped biochar/bentonite for effective removal of phosphate from complex wastewaters

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          Most cited references37

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          Reporting physisorption data for gas/solid systems with special reference to the determination of surface area and porosity (Provisional)

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            Enhancing phosphate adsorption by Mg/Al layered double hydroxide functionalized biochar with different Mg/Al ratios

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              Selective Phosphate Removal from Water and Wastewater using Sorption: Process Fundamentals and Removal Mechanisms

              Eutrophication of water bodies is a serious and widespread environmental problem. Achieving low levels of phosphate concentration to prevent eutrophication is one of the important goals of the wastewater engineering and surface water management. Meeting the increasingly stringent standards is feasible in using a phosphate-selective sorption system. This critical review discusses the most fundamental aspects of selective phosphate removal processes and highlights gains from the latest developments of phosphate-selective sorbents. Selective sorption of phosphate over other competing anions can be achieved based on their differences in acid-base properties, geometric shapes, and metal complexing abilities. Correspondingly, interaction mechanisms between the phosphate and sorbent are categorized as hydrogen bonding, shape complementarity, and inner-sphere complexation, and their representative sorbents are organic-functionalized materials, molecularly imprinted polymers, and metal-based materials, respectively. Dominating factors affecting the phosphate sorption performance of these sorbents are critically examined, along with a discussion of some overlooked facts regarding the development of high-performance sorbents for selective phosphate removal from water and wastewater.
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                Author and article information

                Journal
                Frontiers of Environmental Science & Engineering
                Front. Environ. Sci. Eng.
                Springer Science and Business Media LLC
                2095-2201
                2095-221X
                June 2023
                December 20 2022
                June 2023
                : 17
                : 6
                Article
                10.1007/s11783-023-1671-7
                a915bf28-0488-474d-962d-ea6f8cf3954b
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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