Adsorption of Per- and Polyfluoroalkyl Substances (PFASs) and Other Polar Organic Contaminants on Pristine and Organic-Coated Clay Mineral Surfaces

全氟烷基物质和多氟烷基物质 (PFAS) 以及其他极性有机污染物在原始和有机涂层粘土矿物表面上的吸附

基本信息

批准号：
1931611
负责人：
Ian Bourg
金额：
$ 33万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931611&HistoricalAwards=false
关键词：
Adsorption Per Polyfluoroalkyl Substances PFASs

项目摘要

Per- and Polyfluoroalkyl Substances (PFAS) are a class of synthetic compounds that have been widely dispersed in the environment. Recent evidence indicates that PFAS can lead to adverse health outcomes in humans. These compounds are being found increasingly in drinking water and soils. These developments have led to numerous legal and regulatory actions regarding their use. Despite numerous studies over the past few decades, there remain significant gaps in our knowledge of the environmental persistence of PFAS. This project aims to gain deep insight into the molecular-scale attachment of PFAS and other organic contaminants to solid surfaces using molecular dynamics simulations on supercomputers. Generalizable knowledge of the affinity of PFAS for solid surfaces has the potential to transform our understanding of the environmental fate of these compounds. Successful completion of the research will lead to better models of environmental persistence of PFAS, and the potential development of novel water treatment and soil remediation technologies to protect human and ecological health. A web-based science gateway will produce visualizations of results for the K-12 and broader educational community, thus increasing the scientific literacy of the Nation.The goal of this project is to understand the adsorption of organic contaminants on pristine and organic-coated smectite clay surfaces. The research focuses on polar or anionic organic contaminants, including many compounds of emerging concern such as per- and polyfluoroalkyl substances (PFAS). These compounds exhibit a more diverse range of functional groups and more complex adsorption behaviors than legacy pollutants such a polychlorinated biphenyls or polycyclic aromatic hydrocarbons. The focus on PFAS is timely and relevant given the acute challenges these compounds pose for site remediation and water treatment. The research will develop a novel computational chemistry methodology that can accurately predict the affinity of polar or anionic organic contaminants for pristine and organic-coated smectite clay surfaces at the molecular scale. Variables include the influence on adsorption of compound structure for a diverse range of 53 compounds, aqueous chemistry, and organic clay surface coatings. This methodology will be validated using laboratory sorption experiments to develop new geochemical modeling tools. The project team will develop a web-based interface that will enable the broader educational community of high school students and teachers to visualize and explore simulation results stored on the high-performance data storage systems at the National Energy Research Scientific Computing Center (NERSC).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

全氟烷基物质和多氟烷基物质 (PFAS) 是一类广泛分散在环境中的合成化合物。最近的证据表明，PFAS 可能导致人类健康不良。这些化合物越来越多地存在于饮用水和土壤中。这些发展导致了许多有关其使用的法律和监管行动。尽管过去几十年进行了大量研究，但我们对 PFAS 环境持久性的了解仍然存在很大差距。该项目旨在利用超级计算机上的分子动力学模拟，深入了解 PFAS 和其他有机污染物在固体表面的分子尺度附着情况。关于 PFAS 对固体表面亲和力的普遍了解有可能改变我们对这些化合物的环境命运的理解。该研究的成功完成将带来更好的 PFAS 环境持久性模型，并有可能开发新型水处理和土壤修复技术，以保护人类和生态健康。基于网络的科学网关将为 K-12 和更广泛的教育界提供可视化结果，从而提高国家的科学素养。该项目的目标是了解有机污染物在原始和有机涂层蒙皂石上的吸附情况粘土表面。该研究重点关注极性或阴离子有机污染物，包括许多新出现的化合物，例如全氟烷基物质和多氟烷基物质（PFAS）。与多氯联苯或多环芳烃等传统污染物相比，这些化合物表现出更多样化的官能团和更复杂的吸附行为。鉴于这些化合物给现场修复和水处理带来的严峻挑战，对 PFAS 的关注是及时且相关的。该研究将开发一种新颖的计算化学方法，可以在分子尺度上准确预测极性或阴离子有机污染物对原始和有机涂层蒙脱石粘土表面的亲和力。变量包括对 53 种不同化合物结构吸附的影响、水化学和有机粘土表面涂层。该方法将通过实验室吸附实验进行验证，以开发新的地球化学建模工具。该项目团队将开发一个基于网络的界面，使更广泛的高中生和教师教育界能够可视化和探索存储在国家能源研究科学计算中心（NERSC）高性能数据存储系统中的模拟结果。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。