Linking Redox-Cycling to Hydrogeology: Sedimentological Controls on the Capacity of Aquifers to Reduce Nitrate and other Dissolved Electron Acceptors
Linking Redox-Cycling to Hydrogeology: Sedimentological Controls on the Capacity of Aquifers to Reduce Nitrate and other Dissolved Electron Acceptors
批准号:
497727419
负责人:
Professor Dr.-Ing. Olaf A. Cirpka
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
沉积含水层的物理和化学组成是由其形成时的寄主岩石地质和当地沉积环境决定的。后者产生了一组具有特征的结构元素,这些结构元素在粒度分布(以及导水性)和氧化还原活性矿物和有机质含量上都有所不同。这种空间变化和层次组织的分布控制着沉积含水层中的地下水流动和溶质反应性运移。反应性有机相或矿物相的存在决定了硝酸盐和其他溶解电子受体的潜在反应活性,但为了发生反应,携带电子的沉积物必须是流动的管道,也就是说,它们必须具有足够高的水力导电性,以使水性溶质达到反应性固相。对基质反应性的依赖是含水层中硝酸盐持续污染的一个关键原因,尽管反硝化是一个高能量的反应,并且地下拥有必要的微生物能力来催化它。拟议的项目旨在定量地将含水层水力和生物地球化学特性与含水层沉积物的“反应性”及其通过反硝化减少硝酸盐的能力联系起来。通过水文地质、沉积学和微生物学现场调查,现场采集岩心的流动柱实验,以及实验室和含水层尺度的反应性传输模型,我们的目标是产生一个独特的数据集,能够可靠地估计特定地点和特定相的反应性,从而为更大规模(反硝化)预测模型提供数据。该项目将在德国和奥地利的五个地点进行直接推进实地调查,包括水力导电性、硝酸盐污染、有机物质/氧化还原活性矿物含量,以进行岩心测井和沉积物样品提取。实地调查将通过监测沉积物中反硝化和反硝化微生物活动的实验,为生物地球化学流动提供信息。野外采集岩心的详细沉积学特征将有助于阐明沉积相的反应电位,并建立特定地点的沉积学概念模型。反应输运模型将有助于量化反应速率系数,最终得出沉积物总体反应性的估计值。后者将输入基于“累积相对反应性”概念的含水层尺度虚拟洪泛平原含水层模型,以解决反应性输运问题。我们希望这个项目能够促进我们对基质介导的氧化还原反应和含水层微生物活动的基本沉积学控制的理解,并建立含水层尺度模型,以预测作为含水层沉积环境函数的反硝化作用。
英文摘要
The physical and chemical make-up of sedimentary aquifers is determined by the geology of the host rock and the local depositional environment at the time of their formation. The latter yields a characteristic constellation of structural elements differing both in grain-size distribution (and thus hydraulic conductivity) and content of redox-active minerals and organic matter. This spatially variable and hierarchically organized distribution controls groundwater flow and solute reactive transport in sedimentary aquifers. The presence of reactive organic or mineral phases determines the potential reactivity for nitrate and other dissolved electron acceptors, but for the reactions to occur the electron bearing sediments must be conduits for flow, that is, that they must have a sufficiently high hydraulic conductivity to allow water borne solutes to reach the reactive solid phases. The dependence on matrix-reactivity is a key reason for sustained nitrate contamination in aquifers, despite denitrification being a high-energy-yielding reaction, and the subsurface harboring the necessary microbial capacity to catalyze it. The proposed project aims at quantitatively linking aquifer hydraulic and biogeochemical properties with the “reactivity” of aquifer sediments, and their ability to reduce nitrate via denitrification. Via a coupled hydrogeological, sedimentological and microbiological field-site investigations, flow-through column experiments with field-collected cores and data-informed reactive transport modelling at the laboratory and aquifer scales, we aim to yield a unique dataset that will enable reliable estimates of site- and facies-specific reactivity estimates to feed larger scale (denitrification) predictive models. The project will rely on Direct-Push field investigations at five sites across a spectrum of hydraulic conductivity, nitrate contamination, and organic matter / redox-active mineral content in Germany and Austria for core-logging and sediment sample extraction. Field surveys will inform biogeochemical flow through experiments that will monitor denitrification and denitrifying microbial activity in sediments. A detailed sedimentological characterization of field collected cores will help elucidate the reactive potential of sedimentological facies and build site-specific conceptual sedimentological models. Reactive transport models will help quantifying reaction-rate coefficients that will ultimately yield estimates of overall sediment reactivity. The latter will feed into aquifer scale virtual floodplain aquifer models based on the concept of “cumulative relative reactivity” to solve for reactive transport. We expect this project to advance our understanding of fundamental sedimentological controls on matrix-mediated redox reactions and microbial activity in aquifers, and yield aquifer-scale models that can predict denitrification as a function of an aquifer’s sedimentological setting.
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