Emma F. Shapiro , Zhi-Wei Lin , Edwin Saavedra Cifuentes , Francisco J. Barajas-Rodriguez , Rosa Gwinn , William R. Dichtel , Aaron I. Packman
{"title":"Removal of PFAS and pharmaceuticals from municipal wastewater using a novel β-cyclodextrin adsorbent over distinct contact times","authors":"Emma F. Shapiro , Zhi-Wei Lin , Edwin Saavedra Cifuentes , Francisco J. Barajas-Rodriguez , Rosa Gwinn , William R. Dichtel , Aaron I. Packman","doi":"10.1016/j.watres.2025.123631","DOIUrl":null,"url":null,"abstract":"<div><div>Conventional adsorbents applied in wastewater treatment are ineffective at removing trace organic contaminants (TrOCs), including per and poly-fluoroalkyl substances (PFAS) and pharmaceuticals. Cross-linked β-cyclodextrin (β-CD) polymer adsorbents have demonstrated efficient removal of TrOCs and exhibit rapid kinetics and high adsorption capacity in wastewater. We evaluate the removal of a mixture of contaminants from wastewater by a styrene functionalized β-CD adsorbent (StyDex) through rapid small-scale column tests (RSSCTs). We found the kinetics observed in batch adsorption tests are maintained in RSSCTs. However, batch sorption kinetic constants did not match column breakthrough kinetics, due to an inability to describe complex flow-through behaviors. We correlated both batch kinetic constants and treatable bed volumes with hydrophobicity of target compounds, where PFOA and PFHxS had the highest affinity for StyDex in batch tests and the latest breakthroughs in RSSCTs. Breakthrough curves of five of the seven TrOCs were not affected by change in contact time. Conversely, decreasing the contact time led to earlier breakthrough of contaminants with the highest sorption affinity to StyDex: longer chained and sulfonated PFAS compounds. These effects were isolated in two-component competitive sorption experiments between PFOA and PFBA, and we observed the same preferential sorption of hydrophobic compounds identified in the multi-component mixture. Additionally, competitive adsorption-desorption increased with increasing contact times. We discuss how these findings are crucial for scale-up and large-scale testing of novel sorbents.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"282 ","pages":"Article 123631"},"PeriodicalIF":11.4000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S004313542500541X","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Conventional adsorbents applied in wastewater treatment are ineffective at removing trace organic contaminants (TrOCs), including per and poly-fluoroalkyl substances (PFAS) and pharmaceuticals. Cross-linked β-cyclodextrin (β-CD) polymer adsorbents have demonstrated efficient removal of TrOCs and exhibit rapid kinetics and high adsorption capacity in wastewater. We evaluate the removal of a mixture of contaminants from wastewater by a styrene functionalized β-CD adsorbent (StyDex) through rapid small-scale column tests (RSSCTs). We found the kinetics observed in batch adsorption tests are maintained in RSSCTs. However, batch sorption kinetic constants did not match column breakthrough kinetics, due to an inability to describe complex flow-through behaviors. We correlated both batch kinetic constants and treatable bed volumes with hydrophobicity of target compounds, where PFOA and PFHxS had the highest affinity for StyDex in batch tests and the latest breakthroughs in RSSCTs. Breakthrough curves of five of the seven TrOCs were not affected by change in contact time. Conversely, decreasing the contact time led to earlier breakthrough of contaminants with the highest sorption affinity to StyDex: longer chained and sulfonated PFAS compounds. These effects were isolated in two-component competitive sorption experiments between PFOA and PFBA, and we observed the same preferential sorption of hydrophobic compounds identified in the multi-component mixture. Additionally, competitive adsorption-desorption increased with increasing contact times. We discuss how these findings are crucial for scale-up and large-scale testing of novel sorbents.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.