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生物动力学模型预测大型污水处理厂一氧化二氮排放季节性变化的局限性。

Limitations of a biokinetic model to predict the seasonal variations of nitrous oxide emissions from a full-scale wastewater treatment plant.

机构信息

KWR Water Research Institute, Nieuwegein, the Netherlands; Section Sanitary Engineering, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands.

KWR Water Research Institute, Nieuwegein, the Netherlands.

出版信息

Sci Total Environ. 2024 Mar 20;917:170370. doi: 10.1016/j.scitotenv.2024.170370. Epub 2024 Jan 26.

Abstract

A biokinetic model based on BioWin's Activated Sludge Digestion Model (ASDM) coupled with a nitrous oxide (NO) model was setup and calibrated for a full-scale wastewater treatment plant (WWTP) Amsterdam West, in the Netherlands. The model was calibrated using one year of continuous data to predict the seasonal variations of NO emissions in the gaseous phase. This, according to our best knowledge, is the most complete full-scale data set used to date for this purpose. The results obtained suggest that the currently available biokinetic model predicted the winter, summer, and autumn NO emissions well but failed to satisfactorily simulate the spring peak. During the calibration process, it was found that the nitrifier denitrification pathway could explain the observed emissions during all seasons while a combination of the nitrifier denitrification and incomplete heterotrophic denitrification pathways seemed to be dominant during the emissions peak observed during the spring season. Specifically, kinetic parameters related to free nitrous acid (FNA) displayed significant sensitivity leading to increased NO production. The obtained values of two kinetic parameters, i.e., the FNA half-saturation during ammonia oxidising bacteria (AOB) denitrification and the FNA inhibition concentration related to heterotrophic denitrification, suggested a strong influence of the FNA bulk concentration on the NO emissions and the observed seasonal variations. Based on the suboptimal performance and limitations of the biokinetic model, further research is needed to better understand the biochemical processes behind the seasonal peak and the influence of FNA.

摘要

基于 BioWin 的活性污泥消化模型 (ASDM) 与一氧化二氮 (NO) 模型耦合的生物动力学模型已为荷兰阿姆斯特丹西部的一个全规模废水处理厂 (WWTP) 建立和校准。该模型使用一年的连续数据进行了校准,以预测气态 NO 排放的季节性变化。据我们所知,这是迄今为止为此目的使用的最完整的全规模数据集。所得结果表明,当前可用的生物动力学模型很好地预测了冬季、夏季和秋季的 NO 排放,但未能令人满意地模拟春季峰值。在校准过程中,发现硝化反硝化途径可以解释所有季节的观测到的排放,而硝化反硝化和不完全异养反硝化途径的组合在春季观测到的排放高峰期似乎占主导地位。具体而言,与游离亚硝酸 (FNA) 相关的动力学参数表现出显著的敏感性,导致 NO 产量增加。两个动力学参数的值,即氨氧化菌 (AOB) 反硝化过程中游离亚硝酸的半饱和值和与异养反硝化相关的游离亚硝酸抑制浓度,表明 FNA 总体浓度对 NO 排放和观测到的季节性变化有很强的影响。基于生物动力学模型的次优性能和局限性,需要进一步研究以更好地了解季节性峰值背后的生化过程和 FNA 的影响。

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