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开发用于测定水中总磷和总氮的软件传感器。

Development of software sensors for determining total phosphorus and total nitrogen in waters.

机构信息

M-Cubic Co., Ltd. Migun Technoworld, 533 Yongsan-dong, Yuseong-gu, Daejeon, 305-500, Korea.

出版信息

Int J Environ Res Public Health. 2013 Jan 10;10(1):219-36. doi: 10.3390/ijerph10010219.

Abstract

Total nitrogen (TN) and total phosphorus (TP) concentrations are important parameters to assess the quality of water bodies and are used as criteria to regulate the water quality of the effluent from a wastewater treatment plant (WWTP) in Korea. Therefore, continuous monitoring of TN and TP using in situ instruments is conducted nationwide in Korea. However, most in situ instruments in the market are expensive and require a time-consuming sample pretreatment step, which hinders the widespread use of in situ TN and TP monitoring. In this study, therefore, software sensors based on multiple-regression with a few easily in situ measurable water quality parameters were applied to estimate the TN and TP concentrations in a stream, a lake, combined sewer overflows (CSOs), and WWTP effluent. In general, the developed software sensors predicted TN and TP concentrations of the WWTP effluent and CSOs reasonably well. However, they showed relatively lower predictability for TN and TP concentrations of stream and lake waters, possibly because the water quality of stream and lake waters is more variable than that of WWTP effluent or CSOs.

摘要

总氮(TN)和总磷(TP)浓度是评估水体质量的重要参数,也是韩国污水处理厂(WWTP)出水水质的标准。因此,韩国在全国范围内使用原位仪器对 TN 和 TP 进行连续监测。然而,市场上的大多数原位仪器都很昂贵,并且需要耗时的样品预处理步骤,这阻碍了原位 TN 和 TP 监测的广泛使用。因此,本研究应用了基于少数易于原位测量的水质参数的多元回归的软件传感器来估算溪流、湖泊、合流污水溢流(CSO)和 WWTP 出水的 TN 和 TP 浓度。一般来说,开发的软件传感器可以合理地预测 WWTP 出水和 CSO 的 TN 和 TP 浓度。然而,它们对溪流和湖泊水的 TN 和 TP 浓度的预测能力相对较低,这可能是因为溪流和湖泊水的水质比 WWTP 出水或 CSO 更具变异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e43/3564139/fe414a3a3bf4/ijerph-10-00219-g001.jpg

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