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Quantifying, predicting, and mitigating nitrous oxide emissions in a full-scale partial nitritation/anammox reactor treating reject water.
Water Research ( IF 11.4 ) Pub Date : 2025-01-25 , DOI: 10.1016/j.watres.2025.123200
Xavier Flores-Alsina, Anna Katrine Vangsgaard, Nerea Uri Carreno, Per H. Nielsen, Krist V. Gernaey

In this paper, a set of mathematical tools are developed and assembled to quantify, predict and virtually assess N2O emission migration strategies in partial nitritation (PN) / anammox (ANX) granular based reactors. The proposed approach is constructed upon a set of data pre-treatment methods, process simulation models, control tools (and algorithms) and key performance indicators to analyze, reproduce, and forecast the behavior of multiple operational variables within aerobic granular sludge systems. All these elements are tested on two full-scale data sets (#D1, #D2) collected over a period of four months (Sept-Dec 2023). Results show that data pretreatment is essential for noise reduction, filling data gaps, and ensuring smooth process simulations. The model accurately predicts (normalized RMSE< 1) multiple N oxidation states (NHx, NO2-, NO3-, N2O) and dissolved oxygen (DO), demonstrating its capability to describe bacterial behavior within the studied system. Special emphasis is placed on weak acid-base chemistry where pH is reliably reproduced, and it can be used for control purposes. Both biological and physico-chemical aspects are predicted at different time scales (months, days, minutes). While nitritation mainly occurred in the bulk, biofilm distribution showed inactive inner granule parts and increasing biomass (mostly ANX) towards the surface, with distinct organic concentrations. Gradients for multiple soluble compounds could also be reflected. The model revealed that the system was suffering from low ANX activity leading to NO2- accumulation. This in combination with low DO levels, resulted in nitrifier denitrification (ND) as the main identified N2O production pathway and an unusually high emission factor (EF) as a result. The validation data set also yielded satisfactory results (normalized RMSE< 1). The scenario analysis revealed that modification of the aeration patterns and operational volatile suspended solids (VSS) concentration could improve the ANX activity and lead to N2O emission rates that are in line with what is normally expected from similar systems. The study includes a discussion on transitioning from process models to digital shadows/ twins for real-time process monitoring. Additionally, it emphasizes the necessity of evaluating reject water technologies from a plant-wide perspective.

中文翻译:


量化、预测和减轻处理废水的全尺寸部分硝化/厌氧氨氧化反应器中的一氧化二氮排放。



在本文中,开发和组装了一套数学工具,用于量化、预测和虚拟评估部分硝化 (PN) /厌氧氨氧化 (ANX) 颗粒反应器中的 N2O 排放迁移策略。所提出的方法建立在一组数据预处理方法、过程模拟模型、控制工具(和算法)和关键性能指标之上,以分析、再现和预测好氧颗粒污泥系统中多个操作变量的行为。所有这些元素都在四个月(2023 年 9 月至 12 月)收集的两个全尺寸数据集(#D1、#D2)上进行了测试。结果表明,数据预处理对于降噪、填补数据空白和确保顺利的流程仿真至关重要。该模型准确预测(归一化 RMSE< 1)多种 N 氧化态(NHx、NO2-、NO3-、N2O)和溶解氧 (DO),证明其能够描述所研究系统内的细菌行为。特别强调弱酸碱化学,其中 pH 值可以可靠地再现,并且可用于控制目的。生物和物理化学方面都是在不同的时间尺度(月、天、分钟)预测的。虽然硝化主要发生在本体中,但生物膜分布显示不活跃的内部颗粒部分和向表面增加的生物量(主要是 ANX),具有不同的有机浓度。也可以反射多种可溶性化合物的梯度。该模型显示,该系统的 ANX 活性较低,导致 NO2- 积累。 这与低 DO 水平相结合,导致硝化器反硝化 (ND) 成为已确定的主要 N2O 生产途径,因此具有异常高的排放因子 (EF)。验证数据集也产生了令人满意的结果(归一化 RMSE< 1)。情景分析表明,修改曝气模式和工作挥发性悬浮固体 (VSS) 浓度可以提高 ANX 活性,并导致 N2O 排放率与类似系统的正常预期一致。该研究包括关于从流程模型过渡到数字影子/孪生以进行实时流程监控的讨论。此外,它还强调了从全厂角度评估废水技术的必要性。
更新日期:2025-01-25
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