Norwegian Institute for Water Research, NIVA, Gaustadalléen 21, Oslo, Norway.
Biotechnol Bioeng. 2012 Nov;109(11):2757-69. doi: 10.1002/bit.24553. Epub 2012 May 24.
Conventional models for predicting the fate of xenobiotic organic trace chemicals, identified, and calibrated using data obtained in batch experiments spiked with reference substances, can be limited in predicting xenobiotic removal in wastewater treatment plants (WWTPs). At stake is the level of model complexity required to adequately describe a general theory of xenobiotic removal in WWTPs. In this article, we assess the factors that influence the removal of diclofenac and carbamazepine in activated sludge, and evaluate the complexity required for the model to effectively predict their removal. The results are generalized to previously published cases. Batch experimental results, obtained under anoxic and aerobic conditions, were used to identify extensions to, and to estimate parameter values of the activated sludge modeling framework for Xenobiotic trace chemicals (ASM-X). Measurement and simulation results obtained in the batch experiments, spiked with the diclofenac and carbamazepine content of preclarified municipal wastewater shows comparably high biotransformation rates in the presence of growth substrates. Forward dynamic simulations were performed using full-scale data obtained from Bekkelaget WWTP (Oslo, Norway) to evaluate the model and to estimate the level of re-transformable xenobiotics present in the influent. The results obtained in this study demonstrate that xenobiotic loading conditions can significantly influence the removal capacity of WWTPs. We show that the trace chemical retransformation in upstream sewer pipes can introduce considerable error in assessing the removal efficiency of a WWTP, based only on parent compound concentration measurements. The combination of our data with those from the literature shows that solids retention time (SRT) can enhance the biotransformation of diclofenac, which was not the case for carbamazepine. Model approximation of the xenobiotic concentration, detected in the solid phase, suggest that between approximately 1% and 16% of the total solid carbamazepine and diclofenac concentrations, respectively, is due to sorption-the remainder being non-bioavailable and sequestered. We demonstrate the effectiveness of the model's predictive power over conventional tools in a statistical analysis, performed at four levels of structural complexity. To assess WWTP retrofitting needs to remove xenobiotic trace chemicals, we suggest using mechanistic models, e.g., ASM-X, in regional risk assessments. For preliminary evaluations, we present operating charts that can be used to estimate average xenobiotic removal rates in WWTPs as a function of SRT and the xenobiotics mass loads normalised to design treatment capacity.
传统的预测方法是基于使用参考物质添加的批量实验来识别和校准外来有机痕量化学物质的命运，但在预测废水处理厂（WWTP）中的外来物质去除方面可能存在局限性。关键在于需要模型的复杂性来充分描述 WWTP 中外来物质去除的一般理论。在本文中，我们评估了影响活性污泥中双氯芬酸和卡马西平去除的因素，并评估了模型有效预测它们去除所需的复杂性。结果被推广到以前发表的案例中。在缺氧和有氧条件下进行的批量实验结果用于确定 Xenobiotic trace chemicals（ASM-X）活性污泥建模框架的扩展，并估计其参数值。在预澄清的城市废水中添加双氯芬酸和卡马西平的含量进行的批量实验的测量和模拟结果表明，在有生长基质存在的情况下，生物转化率相当高。使用从 Bekkelaget WWTP（挪威奥斯陆）获得的全尺寸数据进行正向动态模拟，以评估模型并估计存在于进水口中的可再转化外来生物的水平。本研究的结果表明，外来物质的负荷条件会显著影响 WWTP 的去除能力。我们表明，仅根据母体化合物浓度测量，上游污水管道中的痕量化学再转化会在评估 WWTP 的去除效率方面引入相当大的误差。将我们的数据与文献中的数据相结合表明，固体停留时间（SRT）可以增强双氯芬酸的生物转化，而卡马西平则不然。模型对外来化合物浓度的近似值表明，总固体卡马西平和双氯芬酸浓度中分别约有 1%至 16%是由于吸附作用，其余部分是不可生物利用的并被隔离。我们通过在四个结构复杂性水平上进行统计分析，证明了该模型在预测能力方面优于传统工具的有效性。为了评估 WWTP 去除外来痕量化学物质的改造需求，我们建议在区域风险评估中使用机制模型，例如 ASM-X。对于初步评估，我们提供了操作图表，可以根据 SRT 和标准化到设计处理能力的外来物质质量负荷来估计 WWTP 中外来物质去除率的平均值。
