Modelling the fate of organic carbon and micropollutants in Biological Active Granular Activated Carbon Filters

模拟生物活性颗粒活性炭过滤器中有机碳和微污染物的命运

• 批准号: 498237570
• 负责人: Professorin Dr. Susanne Lackner
• 金额: --
• 依托单位: Fachgebiet Abwasserwirtschaft
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/498237570?language=en
• 关键词: Modelling; fate; organic; carbon; micropollutants

The presence of Organic Micropollutants (OMPs) in receiving waterbodies is of great concern, due to their potential threat to the environment and human health. Wastewater Treatment Plants (WWTP) effluents are known to be one major source of OMPs; as a response, legal frameworks are currently under discussion and various technologies for the reduction of OMPs are investigated. Granular Activated Carbon (GAC) filters have established themselves as a suitable technology for OMP removal from WWTP effluents. Alongside adsorptive removal GAC-filters have the ability to also biologically remove organic matter and OMPs. The phenomena governing adsorptive and biological reduction of OMPs as well as the synergies between these two mechanisms are of great importance. The investigation of these processes is, however, highly complex. On the one hand, WWPT effluents are multi-component mixtures and difficult to characterize; on the other hand, the various interactions that take place between the GAC, the biofilm, the OMPs and the organic matter, is rather complicated to measure or track experimentally. Mathematical models are powerful tools to overcome such experimental barriers, to analyze various scenarios and eventually to support the design of further experiments. Using lab and pilot-scale data, a first mathematical model capable of satisfactorily describing the dissolved organic carbon removal in a biological active GAC-filter has been developed. This project aims to improve and extend this model with new key features that are required for further application of the model. In particular, three hypotheses will be tested: (i) Is it possible to introduce the pore size distribution to the model? Pore size distribution is key parameter for the characterization of different GAC-types, thus its implementation into the model is vital. Nevertheless the conventional approaches require parameters that are difficult to determine. (ii) Could a microbial community including the N-cycle improve the explanatory power of the model? With experimental evidence that relates biodegradation of OMPs to the activity of nitrifiers, the project aims to implement co-metabolic processes and to assess their effect on the global modelling results. (iii) How can individual OMPs be included into the model and their behavior be satisfactory reproduced? The prediction of the removal of individual OMPs is of high relevance and therefore, four OMPs will exemplarily be implemented into the model and used as proxy for the removal of other OMPs of interest. Since the mechanistic description of the OMPs may easily get complicated, the modeling approach will combine mechanistical modeling with machine learning methods as support.

受纳水体中有机微污染物（OMPs）的存在受到极大关注，因为它们对环境和人类健康具有潜在的威胁。众所周知，污水处理厂（WWTP）的流出物是OMP的一个主要来源;作为回应，目前正在讨论法律的框架，并研究各种减少OMP的技术。颗粒活性炭（GAC）过滤器已经确立了自己作为一个合适的技术OMP去除污水处理厂的流出物。除了吸附去除之外，GAC过滤器还具有生物去除有机物质和OMP的能力。OMPs的吸附还原和生物还原以及这两种机制之间的协同作用是非常重要的。然而，对这些过程的研究是非常复杂的。一方面，WWPT废水是多组分混合物，难以表征;另一方面，在GAC、生物膜、OMP和有机物之间发生的各种相互作用在实验上测量或跟踪相当复杂。数学模型是克服这些实验障碍、分析各种情景并最终支持进一步实验设计的有力工具。利用实验室和中试规模的数据，第一个数学模型能够令人满意地描述溶解性有机碳去除生物活性GAC过滤器已经开发。该项目旨在改进和扩展该模型，增加进一步应用该模型所需的新的关键功能。具体而言，将测试三个假设：（i）是否有可能将孔径分布引入模型？孔径分布是表征不同GAC类型的关键参数，因此其在模型中的实现至关重要。然而，常规方法需要难以确定的参数。(ii)包括氮循环在内的微生物群落是否能提高模型的解释力？该项目的实验证据表明，OMP的生物降解与硝化菌的活性有关，旨在实施共代谢过程，并评估其对全球建模结果的影响。(iii)如何将个体OMP纳入模型，并使其行为得到满意的再现？对单个OMP的去除的预测具有高度相关性，因此，将示例性地将四个OMP实施到模型中，并用作去除其他感兴趣的OMP的代理。由于OMP的机械描述可能容易变得复杂，建模方法将联合收割机机械建模与机器学习方法相结合作为支持。