Civil Engineering, University of Pavia, 5, 27100 Pavia, Italy.
Department of Civil and Environmental Engineering, University of Rome "LA Sapienza", 18, 00184 Roma, Italy.
Int J Environ Res Public Health. 2020 Dec 14;17(24):9366. doi: 10.3390/ijerph17249366.
The biological denitrification process is extensively discussed in scientific literature. The process requires anoxic conditions, but the influence of residual dissolved oxygen () on the efficiency is not yet adequately documented. The present research aims to fill this gap by highlighting the effects of on the specific denitrification rate () and consequently on the efficiency of the process. at a temperature of 20 °C () is the parameter normally used for the sizing of the denitrification reactor in biological-activated sludge processes. A sensitivity analysis of to variations is developed. For this purpose, two of the main empirical models illustrated in the scientific literature are taken into consideration, with the addition of a deterministic third model proposed by the authors and validated by recent experimentations on several full-scale plants. In the first two models, is expressed as a function of the only variable food:microrganism ratio in denitrification (), while in the third one, the dependence on is made explicit. The sensitivity analysis highlights all the significant dependence of on characterized by a logarithmic decrease with a very pronounced gradient in correspondence with low concentrations. Moreover, the analysis demonstrates the relatively small influence of on the and on the correlation between and . The results confirm the great importance of minimizing and limiting, as much as possible, the transport of oxygen in the denitrification reactor through the incoming flows and mainly the mixed liquor recycle. Solutions to achieve this result in full-scale plants are reported.
生物反硝化过程在科学文献中被广泛讨论。该过程需要缺氧条件，但残留溶解氧（）对效率的影响尚未得到充分记录。本研究旨在通过强调对特定反硝化速率（）的影响，从而对该过程的效率产生影响，来填补这一空白。在 20°C（）的温度下，通常用于生物活性污泥过程中反硝化反应器的设计的参数是。开发了对 到 的变化的敏感性分析。为此，考虑了科学文献中说明的两个主要经验模型，并添加了作者提出的确定性第三个模型，并通过最近对几个全规模工厂的实验进行了验证。在前两个模型中，被表示为反硝化中微生物与食物的唯一变量比（）的函数，而在第三个模型中，明确依赖于。敏感性分析突出显示了与对数减少相关的所有显著的对的依赖关系，并且在低浓度时梯度非常明显。此外，该分析还证明了在和之间的相关性上，对的影响相对较小。研究结果证实了最小化和尽可能限制氧气在反硝化反应器中的传输的重要性，这可以通过进入流和主要是混合液回流来实现。报告了在全规模工厂中实现这一结果的解决方案。
