SENSORS FOR WATER CONTAMINANT DETECTION AND MONITORING

用于水污染物检测和监测的传感器

• 批准号: 10361888
• 负责人: Menachem Elimelech
• 金额: $ 20.74万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-07 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10361888
• 关键词: Affinity; Air; Antibody Affinity; Binding; Biological Assay; Biosensor; Charge; Chemicals; Cities; Collaborations; Communities; Computers; Consumption; Crystallization; DNA; Data; Data Analyses; Detection; Development; Devices; Diagnostic; Dioxanes; Effectiveness; Elements; Encapsulated; Epitopes; Ethylene Dichlorides; Event; Exposure to; Extravasation; Gas Chromatography; Gases; Goals; Hazardous Chemicals; Health; Human; Hydrophobicity; Immunoglobulin Fragments; In Situ; Individual; Infrastructure; Interruption; Laboratories; Libraries; Lipids; Liposomes; Measurable; Measurement; Measures; Methods; Modeling; Molecular Weight; Monitor; Oligonucleotides; Oxidation-Reduction; Phase; Plants; Prevalence; Process; Property; Proxy; Public Health; Quartz; Reagent; Research; Risk; Safety; Signal Transduction; Site; Solubility; Solvents; Source; Specificity; System; Techniques; Time; Toxic Environmental Substances; Trichloroethanes; Trichloroethylene; Vacuum; Vesicle; Water; Water Pollutants; Water Supply; Yeasts; analytical method; anthropogenesis; aptamer; base; chemical reaction; combinatorial; community engagement; contaminant transport; contaminated drinking water; copolymer; cost; data management; detection limit; drinking water; exposed human population; field study; ground water; improved; innovation; nanobodies; photoionization; portability; purge; real time monitoring; receptor; remediation; response; sensor; sensor technology; spatiotemporal; superfund site; water sampling; water testing; water treatment; waterborne; well water; wireless network; wireless sensor

ABSTRACT Groundwater in Superfund sites is contaminated with a wide range of hazardous chemicals originating from anthropogenic and natural sources. Individuals exposed to these chemicals through contaminated drinking water can be subjected to adverse health effects. The YSRTP will focus on 1,4-dioxane (1,4-DX) and its co-occurring contaminants: trichloroethylene (TCE), 1,1,1-trichloroethane (TCA), and 1,1-dichloroethane (DCA). To protect drinking water supplies and human health, rapid approaches for the detection and monitoring of these contaminants are crucial. The overall goal of this project is to develop sensors for 1,4-DX and its co-contaminants with real-time monitoring via a wireless network. The project includes four specific aims: (1) developing and characterizing biosensors for 1,4-DX detection and quantification, (2) developing and characterizing chemical sensors for 1,4-DX co-occurring contaminants (TCE, TCA, and DCA), (3) 1,4-DX and co-contaminant detection via portable vacuum gas chromatography, and (4) demonstrating detection in a distributed wireless sensor network for contaminant monitoring. The main innovative aspects of the research include the following: (i) developing the first sensor for detecting low, health relevant concentrations of 1,4-DX, by employing an evolutionary selection process, an artificially antibody affinity maturation technique, and organometallic pre- binding molecules; (ii) developing a chemical sensor that exploits the unique solubility-based selectivity of lipid and block-copolymer bilayer vesicles for detecting TCE, DCA, and TCA as a proxy for 1,4-DX contamination; and (iii) demonstrating the use of 1,4-DX sensors and adapted portable vacuum gas chromatographers in a wireless sensor network (WSN) to enable responses to dynamic contamination and exposure events. The project is well integrated with the overall YSRTP. The real time data of contaminant concentrations provided by the WSN will be integrated Project 4 to improve remediation strategies and measure remediation effectiveness and help inform the biomedical projects (Projects 1,2) on exposures for communities in the vicinity of the Superfund sites, and inform the community—through the Community Engagement Core—on real-time concentrations of the target contaminants in drinking water sources. The project will also be engaged with the Data Management & Analysis Core (DMAC) to appropriately store and analyze all contaminant occurrence and concentration data pursuant to the above project interactions and for assistance in the WSN to meet the stated measurement goals.

摘要