POLLUTANT BIOAVAILABILITY LEADING TO STRUCTURED MODELS FOR CONTAMINANT FATE

本项目旨在评估微尺度方法在研究中的应用 污染物在土壤和沉积物中的生物有效性。总体目标是 更好地从机理上理解微生物和 微环境有利于控制分布、生物降解 以及污染物的传输，如单环芳烃和多环芳烃 碳氢化合物(多环芳烃)(如甲苯、萘和菲)和 多孔介质中的重金属(如Cd和Pb)。方法是发展 并应用微观检测和鉴定方法，如 荧光抗体(FAB)染色、显微放射自显影(MARG)和 寡核苷酸荧光原位杂交(FISH)检测 特定物种的微尺度分布和不同的活动模式 与非生物有关的细菌(和基因)和污染化学品 土壤和沉积物的成分。常规光和电子 显微镜方法也将用于区分染色和 非生物成分的鉴定。这些原则的应用 微尺度方法将有助于更好地理解污染物 相对于非生物成分的分布和可用性以及 能够参与其生物降解的细菌细胞或 运输。 在延续项目中，新开发的FAB-MARG程序将 在甲苯的宏观和微观相结合的研究中得到提炼 恶臭假单胞菌F1在有机底泥中的生物降解 随后可应用于多环芳烃的类似研究。新鱼--Marg 将开发鉴定非可培养细菌的方法，使用 一种荧光标记的核糖体RNA靶向寡核苷酸 Fab-Marg程序的杂交变异。FAB检测方法 将进行测试，以识别污染物化学物质和腐殖质成分 在土壤或沉积物基质中。其他差分光和电子 显微方法，包括STEM-MAG和STEM-EDX，自体荧光 以及土壤基质成分的荧光染色，以及胶体金- 标记抗体染色，也将测试其在 估算污染物分布与其微观结构的关系 土壤和沉积物颗粒。 从微观模型出发，建立了宏观模型结构 嵌入其中的组件，允许直接应用微尺度 从数据到宏观性能。生物降解动力学与污染物 此结构化模型中使用的分布参数将为 使用微尺度方法进行评估，因为它们可用于 确认物理和化学之间的相互关系 土壤中污染物的有效性及其矿化速率 和沉淀物。在建议中获得的机械性理解 研究将为更稳健的持续发展提供基础 污染物生物利用度、降解和迁移的模型 以前就已经有了。这类模型的开发有望有助于 风险评估和风险管理活动，并降低成本 通过允许更准确地预测污染物来实现生物修复 比当前型号可能的性能更好。

This project aims to evaluate microscale methods for use in studies of pollutant bioavailability in soil and sediment. The overall goal is to provide a better mechanistic understanding of microbiological and microenvironmental favors controlling the distribution, biodegradation and transport of pollutants such as mono- and polycyclic aromatic hydrocarbons (PAHs) (e.g. toluene, naphthalene and phenanthrene) and heavy metals (e.g. Cd and Pb) in porous media. The approach is to develop and apply microscopic detection and identification methods such as fluorescent antibody (Fab) staining, microautoradiography (MARG), and oligonucleotide fluorescent in situ hybridization (FISH) to determine the microscale distribution and differential activity patterns of specific bacteria (and genes) and pollutant chemicals relative to non-living components of soil and sediment. Conventional light and electron microscopic methods will also be used for differential staining and identification of the non-living components. Application of these microscale methods will result in a better understanding of pollutant distribution and availability relative to the non-living components and the bacterial cells capable that participate in their biodegradation or transport. In the continuation project, a newly developed Fab-MARG procedure will be refined in combined macro- and microscale studies of toluene biodegradation by Pseudomonas putida Fl in organic sediment and subsequently be applied in similar studies with PAHs. New FISH-MARG methods will be developed for identifying non-culturable bacteria using a fluorescently labeled ribosomal RNA-targeted oligonucleotide hybridization variation of the Fab-MARG procedure. Fab detection methods will be tested for identifying pollutant chemicals and humic components in soil or sediment matrix. Other differential light and electron microscopic methods, including STEM-MARG and STEM-EDX, autofluorescence and fluorochrome staining of soil matrix components, and colloidal gold- labeled antibody staining, will also be tested for their efficacy in estimating pollutant distribution in relation to the microstructure of soil and sediment particles. A macroscale model structure was developed with microscale model components embedded in it that allow for direct application of microscale data to macroscale performance. Biodegradation kinetic and pollutant distribution parameters for use in this structured model will be evaluated using the microscale methodologies as they become available to confirm the interrelationships between the physical and chemical availability of the contaminants and their mineralization rates in soils and sediments. The mechanistic understanding obtained in the proposed research will provide the basis for continued development of more robust models for pollutant bioavailability, degradation, and transport than have been available before. Development of such models is expected to aid exposure assessment and risk management activities and reduce the costs of bioremediation by allowing for more accurate predictions of pollutant behavior than is possible with current models.