Despite advances in wastewater treatment plant (WWTP) efficiencies, multiple contaminants of concern, such as microplastics, pharmaceuticals, and per- and poly-fluoroalkyl substances (PFAS) remain largely untreated near discharge points and can be highly concentrated before they are fully mixed within the receiving river. Environmental agencies enforce mixing zone permits for the temporary exceedance of water quality parameters beyond targeted control levels under the assumption that contaminants are well-mixed and diluted downstream of mixing lengths, which are typically quantified using empirical equations derived from one-dimensional transport models. Most of these equations were developed in the 1970s and have been assumed to be standard practice since then. However, their development and validation lacked the technological advances required to test them in the field and under changing flow conditions. While new monitoring techniques such as remote sensing and infrared imaging have been employed to visualize mixing lengths and test the validity of empirical equations, those methods cannot be easily repeated due to high costs or flight restrictions. We investigated the application of Lagrangian and Eulerian monitoring approaches to experimentally quantify mixing lengths downstream of a WWTP discharging into the Rio Grande near Albuquerque, New Mexico (USA). Our data spans river to WWTP discharges ranging between 2-22x, thus providing a unique dataset to test long-standing empirical equations in the field. Our results consistently show empirical equations could not describe our experimental mixing lengths. Specifically, while our experimental data revealed “bell-shaped” mixing lengths as a function of increasing river discharges, all empirical equations predicted monotonically increasing mixing lengths. Those mismatches between experimental and empirical mixing lengths are likely due to the existence of threshold processes defining mixing at different flow regimes, i.e., jet diffusion at low flows, the Coanda effect at intermediate flows, and turbulent mixing at higher flows, which are unaccounted for by the one-dimensional empirical formulas. Our results call for a review of the use of empirical mixing lengths in streams and rivers to avoid widespread exposures to emerging contaminants.

中文翻译：

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实验和经验混合长度之间偏差的证据：干旱河流系统中的多次排放现场测试

尽管废水处理厂 (WWTP) 的效率取得了进步，但多种令人关注的污染物，例如微塑料、药品以及全氟烷基物质和多氟烷基物质 (PFAS) 在排放点附近基本上仍未得到处理，并且在完全混合到污水处理厂之前可能会高度浓缩。接收河。环境机构在假设污染物在混合长度下游充分混合和稀释的情况下，强制执行混合区允许暂时超出目标控制水平的水质参数，这通常使用从一维传输模型得出的经验方程进行量化。这些方程大部分是在 20 世纪 70 年代开发的，从那时起就被认为是标准做法。然而，它们的开发和验证缺乏在现场和变化的流动条件下测试它们所需的技术进步。虽然遥感和红外成像等新的监测技术已被用来可视化混合长度并测试经验方程的有效性，但由于成本高昂或飞行限制，这些方法不易重复。我们研究了拉格朗日和欧拉监测方法的应用，以实验量化排入新墨西哥州阿尔伯克基附近格兰德河的污水处理厂下游的混合长度。我们的数据涵盖河流到污水处理厂的排放量，范围为 2-22 倍，从而提供了一个独特的数据集来测试现场长期存在的经验方程。我们的结果一致表明经验方程无法描述我们的实验混合长度。具体来说，虽然我们的实验数据显示“钟形”混合长度是河流流量增加的函数，但所有经验方程都预测单调增加的混合长度。实验和经验混合长度之间的不匹配可能是由于存在定义不同流态下混合的阈值过程，即低流量下的射流扩散、中间流量下的柯恩达效应以及较高流量下的湍流混合，而这些都没有被考虑在内。由一维经验公式。我们的结果要求对溪流和河流中经验混合长度的使用进行审查，以避免广泛暴露于新出现的污染物。