基于DGT技术的污水处理厂新型有机污染物的去除效率及模拟研究

Emerging organic contaminants such as household and personal care products (HPCPs) and endocrine disrupting chemicals (EDCs) are widely existing in the wastewater with high concentrations. Due to the poor removal efficiencies of these contaminants in the wastewater treatment plants (WWTPs), they are detectable in aquatic environments and may pose risk to the ecosystem. Thus, it is important to study the removal efficiencies of these contaminants in WWTPs and the impact factors. Sampling is the foundation for chemical analysis of the wastewater and evaluation of their removal efficiencies in WWTPs. The most commonly used method is spot sampling, which is time and cost consuming, highly variable and can miss the concentration changes over time. Passive sampling technique can solve this problem. In this proposal, a novel passive sampling technique based on the diffusive gradient in thin-films (DGT) will be used for monitoring the WWTPs at full scale and the influents and effluents in different processes as well as the sludge will be sampled by DGT, the occurrences and the removal efficiencies of HPCPs and EDCs and the impact factors will be studied. A Chinese version of SimpleTreat model will be developed according to the parameters characterized by Chinese WWTPs. The model will then be applied to simulate the concentrations and removal efficiencies of HPCPs and EDCs in WWTPs. The modeling results will be compared and evaluated with monitoring results. Results from this project could help to design and build the better WWTPs to improve the removal efficiencies in the future, help to control the water contamination and to protect the ecosystem and human health.

家用及个人护理品（HPCPs）和内分泌干扰物（EDCs）等新型污染物在污水中普遍存在且含量较高。污水处理厂对此类物质的去除效率不佳，导致其在水环境中广泛检出，对生态环境造成潜在危害。研究污水处理厂对此类物质的去除效率及其影响因素十分重要。污水采样是进行污水中污染物含量分析和去除效率评估的前提。常用方法为单次瞬时采样，但耗时且变异性大，不能真实反映污染物浓度和去除效率。被动采样技术可以弥补此缺点。本研究拟采用梯度扩散薄膜（DGT）技术，对典型污水处理厂进行全尺度（各级进水、出水及污泥）研究，分析HPCPs和EDCs的去除效率，并探讨影响因素。基于实际污水处理厂相关参数，优化改进SimpleTreat模型，建立中国版模型，模拟我国污水处理厂中HPCPs和EDCs的浓度及去除效率，并与实测数据进行对比验证。本研究对设计新建污水处理厂具有指导性意义，有助于控制水体污染，保护生态环境和人体健康。

新型污染物在污水中普遍存在且含量较高，而污水处理厂对此类物质的去除效率不佳，导致其在水环境中广泛检出，可能对生态环境造成危害。本研究以武汉市5座不同处理工艺的污水处理厂为研究对象，对原始进水、一级出水、二级出水、最终出水等四阶段全过程的污水采用样梯度扩散薄膜技术（DGT）进行了样品采集，并使用高效液相色谱与串联质谱联用仪（LC-MS/MS）定量分析了样品中以家用和个人护理品（HPCPs）和内分泌干扰物（EDCs）为代表的新型有机污染物。在此基础上，基于SimpleTreat 4.0模型，采用符合国内实际情况的数据参数，优化改进了SimpleTreat模型。研究结果发现，5座污水处理厂的原始进水中14种HPCPs和EDCs的总浓度范围为1471-2077 ng/L，最终出水中的总浓度范围为88.7-194 ng/L。防腐剂、抗菌剂和双酚在出水中的占比较进水中有明显变化，而抗氧化剂和雌激素的占比变化小。不同污水处理厂的原始进水中HPCPs和EDCs的总浓度和组成存在差异。整体看来，各污水处理厂对目标污染物有一定的去除效果。除EE2外，污水处理厂对污染物的平均去除效率为86.5%-90.5%。SimpleTreat模型的灵敏度分析计算发现流量、活性污泥浓度、污泥负荷、进水生化需氧量、初沉池对BOD去除比例、初沉池对进水固体的去除比例、进水固体密度、进水固体质量、初沉池固体密度、进水中固体的有机碳比例和活性污泥有机碳比例等11个参数与出水预测值具有较强的相关性，在优化模型是需要重点关注的参数。杀菌剂、抗氧化剂和双酚这三类污染物的预测浓度与实测浓度较为接近，但部分防腐剂和雌激素的预测浓度要远高于实测数据，表明模型对这两类物质的模拟预测可能偏向保守，从而导致预测值偏高。结合蒙特卡罗模拟能在一定程度上降低由于污水处理厂参数的可变性导致的模型结果的不确定性，从而使得模型结果更为合理。研究成果有助于提高污水处理厂污染物的去除效率和对未来污水处理厂工艺的选择有一定的指导意义。