SFB 1253: Catchments as Reactors: Metabolism of Pollutants on the Landscape Scale (CAMPOS)

人为污染物在景观尺度上的命运和行为是环境科学面临的最大挑战之一。过去十年的研究强调，在实验室实验中确定的污染物转化速率往往与自然系统中记录的速率形成鲜明对比。这种差异源于我们对流域尺度上控制污染物周转的相关过程的不完全了解。在CAMPOS中，我们假设在实验室规模上难以捉摸的过程在现场变得有效。虽然实验室研究可能会错过缓慢但重要的过程，但实地的常规监测活动受到水文动态的阻碍，水文动态会引发生物地球化学梯度的变化，从而发生重大的污染物转化。CAMPOS的主要目标是预测土壤和水质的未来趋势，作为土地利用和气候条件变化的函数。我们已经确定了反应性景观元素，并通过高分辨率的生物地球化学污染物转化的详细实地研究量化了过程动力学。为此，我们结合了新的分析和传感技术（例如，化合物特异性同位素分析，非靶标筛选，生物分析，原位传感器，组学技术和标记物质的现场规模实验），并开发了随机建模方法。在CAMPOS中定义的每个项目都融合了来自不同学科的专业知识，这些专业知识需要在理解自然界污染物的持久性和最终命运方面取得新的突破。研究相关景观元素的方法已被证明是成功的，并将在CAMPOS第二期应用。研究的景观要素为河流（P1），河流是景观中污染物通量的大集成者；以不同土地用途为特征，主要出口农用化学品的低阶溪流子集水区（P2）；洪泛平原（P3/P4）通常由第四纪沉积物填满，并含有极易受到污染的浅层含水层；裂缝性含水层（P5），由于停留时间长，能够将污染物储存在岩石基质中数十年甚至数百年；土壤（P6），它们接受大气污染物和农用化学品的直接输入。第一阶段开发了一个考虑所有不确定性来源的随机建模框架（P7），并将在第二阶段扩展到景观尺度上的反应性运输。数据基础设施（INF）项目、实验和建模支持项目（S1、S2）以及中央行政(Z)项目为CAMPOS提供了进一步的支持。

The fate and behavior of anthropogenic pollutants on the landscape scale is one of the greatest challenges in environmental sciences. The past decade of research has highlighted that pollutant transformation rates determined in laboratory experiments are often in stark contrast with rates documented in natural systems. This disparity stems from our incomplete knowledge of the relevant processes governing pollutant turnover on the catchment scale. In CAMPOS we have hypothesized that processes become effective in the field which are elusive on the laboratory scale. While laboratory research may miss slow but essential processes, conventional monitoring campaigns in the field are hampered by the dynamics of hydrology that triggers shifts of biogeochemical gradients at which significant pollutant transformations occur. The major goal of CAMPOS is to predict future trends in soil and water quality as a function of changing land use and climatic conditions. We have identified reactive landscape elements and quantified process dynamics with detailed field studies on biogeochemical pollutant transformations at high resolution. Towards this end we have combined novel analytical and sensing techniques (e.g., compound-specific isotope analysis, non-target screening, bioanalysis, in-situ sensors, ‚omics’-technologies, and field scale experiments with labelled substances), and developed stochastic modeling methods. Each project defined within CAMPOS merges expertise from different disciplines needed to break new ground in understanding the persistence and ultimate fate of pollutants in nature. The approach to study relevant landscape elements has proven successful and will also be applied in CAMPOS phase II. The studied landscape elements are rivers (P1), as the big integrators of pollutant fluxes in landscapes; subcatchments (P2) of lower order streams characterized by different land uses and mainly exporting agrochemicals; floodplains (P3/P4) typically filled by Quaternary sediments and containing shallow aquifers which are very vulnerable to pollution; fractured aquifers (P5) which are able to store pollutants in the rock matrix for decades and centuries due to large residence times; and soils (P6),which receive direct input of atmospheric pollutants and agrochemicals. A stochastic Modeling Framework (P7) accounting for all sources of uncertainty has been developed in the first phase and will be extended to reactive transport on the landscape scale in the second phase. Further support to CAMPOS is provided by a Data Infrastructure (INF) project, the Experimental and Modeling Support projects (S1, S2) and the Central Administrative (Z) project.