LEESU (UMR MA 102, Université Paris-Est, AgroParisTech), Université Paris-Est Créteil, Créteil, France.
SIAAP, Direction Innovation Environnement, Colombes, France.
Environ Sci Pollut Res Int. 2018 Mar;25(9):8765-8776. doi: 10.1007/s11356-018-1205-1. Epub 2018 Jan 11.
The online monitoring of dissolved organic matter (DOM) in raw sewage water is expected to better control wastewater treatment processes. Fluorescence spectroscopy offers one possibility for both the online and real-time monitoring of DOM, especially as regards the DOM biodegradability assessment. In this study, three-dimensional fluorescence spectroscopy combined with a parallel factor analysis (PARAFAC) has been investigated as a predictive tool of the soluble biological oxygen demand in 5 days (BOD) for raw sewage water. Six PARAFAC components were highlighted in 69 raw sewage water samples: C2, C5, and C6 related to humic-like compounds, along with C1, C3, and C4 related to protein-like compounds. Since the PARAFAC methodology is not available for online monitoring, a peak-picking approach based on maximum excitation-emission (Ex-Em) localization of the PARAFAC components identified in this study has been used. A good predictive model of soluble BOD using fluorescence spectroscopy parameters was obtained (r = 0.846, adjusted r = 0.839, p < 0.0001). This model is quite straightforward, easy to automate, and applicable to the operational field of wastewater treatment for online monitoring purposes.
在线监测原污水中的溶解有机物质 (DOM) 有望更好地控制废水处理过程。荧光光谱法是在线和实时监测 DOM 的一种可能性,特别是在 DOM 可生物降解性评估方面。在这项研究中,三维荧光光谱法结合平行因子分析 (PARAFAC) 已被研究用作预测原污水中 5 天可溶生物需氧量 (BOD) 的工具。在 69 个原污水样本中突出了六个 PARAFAC 成分:与腐殖质类化合物有关的 C2、C5 和 C6,以及与蛋白质类化合物有关的 C1、C3 和 C4。由于 PARAFAC 方法不适用于在线监测,因此使用了基于本研究中确定的 PARAFAC 成分的最大激发-发射 (Ex-Em) 定位的峰选择方法。使用荧光光谱参数获得了可溶 BOD 的良好预测模型 (r=0.846,调整 r=0.839,p<0.0001)。该模型非常简单,易于自动化,适用于废水处理的操作领域,可用于在线监测目的。