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归宿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，实验室实验中确定的污染物转化率通常与自然系统中记录的转化率形成鲜明对比。这种差异源于我们的知识不完整的相关过程中，污染物周转的流域尺度。在CAMPOS中，我们假设在实验室规模上难以实现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力学的阻碍，水文动力学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量的未来趋势，作为土地使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和量化的过程动力学与详细的实地研究在高分辨率的生态地球化学污染物转化。为此，我们结合了新的分析和传感技术（例如，化合物特定同位素分析、非目标筛选、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。CAMPOS内定义的每个项目都融合了不同学科的专业知识，以在了解自然界污染物的持久性和最终命运方面开辟新天地。研究相关景观要素的方法已证明是成功的，也将应用于CAMPOS第二阶段。研究的景观要素有：河流（P1），作为景观中污染物通量的重要组成部分;次级流域（P2），以不同的土地利用方式为特征，主要输出农用化学品;洪泛平原（P3/P4），主要由第四纪沉积物填充，含水层较浅，易受污染;断裂含水层（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和数百年;和土壤（P6），直接输入大气污染物和农用化学品。一个随机建模框架（P7）占所有来源的不确定性已在第一阶段，并将扩展到反应运输的景观尺度在第二阶段。对CAMPOS的进一步支持由数据基础设施项目、实验和建模支持项目（S1、S2）和中央行政项目（Z）提供。

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.