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Development of Software Sensors for Determining Total Phosphorus and Total Nitrogen in Waters

机译:用于测定水中总磷和总氮的软件传感器的开发

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摘要

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.
机译:总氮(TN)和总磷(TP)浓度是评估水体质量的重要参数,并用作调节韩国废水处理厂(WWTP)出水水质的标准。因此,在韩国全国范围内使用现场仪器对TN和TP进行连续监测。然而,市场上大多数原位仪器价格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,在这项研究中,基于多元回归和一些易于现场测量的水质参数的软件传感器被用于估算溪流,湖泊,下水道联合溢流(CSO)和污水处理厂废水中的总氮和总磷浓度。通常,开发的软件传感器可以很好地预测污水处理厂废水和CSO的TN和TP浓度。但是,它们对溪流和湖泊水的总氮和总磷浓度显示出相对较低的可预测性,这可能是因为溪流和湖泊水的水质比污水处理厂废水或CSO的多。

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