Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya 464-8601, Japan.
Water Sci Technol. 2010;61(8):1957-63. doi: 10.2166/wst.2010.070.
We examined the use of near infrared (NIR) spectroscopy as a rapid technique for the evaluation of sewage quality. Influent water samples, primary sedimentation tank water samples, and final effluent water samples were collected from sewage treatment facilities in Nagoya, Japan and their NIR spectra obtained. Partial least squares (PLS) models for total phosphate (TP), total nitrogen (TN), biochemical oxygen demand (BOD), total organic carbon (TOC), and turbidity of sewage water were constructed from the NIR data. The models provided good correlation between measurements obtained conventionally and those predicted from spectroscopy. Spectral variation induced by background interference in samples affected accuracy. Loading plots and score plots derived from PLS regression analysis resolved the background interference and allowed highly accurate predictions. Spectral variation induced by contamination in the sewage was a main predictor of sewage quality. These results show that NIR spectroscopy shows potential for in-line, non-destructive measurement of sewage quality.
我们研究了近红外（NIR）光谱作为一种快速评估污水质量的技术的应用。采集了日本名古屋污水处理厂的进水水样、初沉池水样和出水水样，并获得了它们的近红外光谱。从 NIR 数据中构建了总磷酸盐（TP）、总氮（TN）、生化需氧量（BOD）、总有机碳（TOC）和浊度的偏最小二乘（PLS）模型。这些模型提供了传统测量值和光谱预测值之间的良好相关性。由样品中背景干扰引起的光谱变化会影响准确性。从 PLS 回归分析中得出的载荷图和得分图解决了背景干扰问题，并允许进行高度准确的预测。由污水中的污染引起的光谱变化是污水质量的主要预测因子。这些结果表明，近红外光谱法具有在线、非破坏性测量污水质量的潜力。
