Uncertainty Research Of Continuous Emission Monitoring System

Flue gas Continuous Emission Monitoring System(CEMS) is a device for continuous monitoring of stationary pollution source discharge in China, especially for the continuous monitoring of pollution source in thermal power plant. At present the CEMS monitoring data has been taken as the basis of formulating verification of the sewage and sewage charges for relevant environmental departments. Therefore, the accuracy of CEMS monitoring data has important significance for environmental monitoring work. The performance of CEMS were detected from 2000 in China, it also called the applicability detection.The CEMS equipment monitoring data of a thermal power plant in Lanzhou was conducted uncertainty evaluation, and the data quality was further verified combined with quality control diagram. The dispersion and equipment stability of CEMS data are described from the angel of uncertainty. The 7 days monitoring data of CEMS monitoring daily table of this plant was selected as the monitoring result.The particles monitoring system was first analyzed, the result showed that the uncertainty degree and the data dispersion of particulate matter concentration in No.1, 2, 7monitoring report was great. The three quality control charts showed it is out of control. It is proved that the data quality is bad. The uncertainty degree in No.4, 5, 6, monitoring report was smaller, indicating that the data dispersion was small. The three quality control charts showed that three monitoring data report quality were good. From each component analysis, it is known that repeated measurements had a greater contribution, the contribution of accuracy and error of instrument was relatively small. The half width of the confidence interval and the half width of the allowable interval were analyzed of the particulate matter monitoring system, the half width of the confidence interval was 7.47%, and the half width of the allowable interval was 21.52%. It accorded with the requirement of the automatic monitoring instrument performance.For the gaseous pollutant monitoring system of the equipment, the monitoring data of concentration of SO2 and NOx was analyzed. The analysis result of uncertainty of SO2 concentration monitoring data in No.1 and No.3 report showed that it was great, and the data dispersion was high. The three quality control charts showed it was out of control. It is proved that the data quality was bad. The uncertainty of SO2 concentration monitoring data in No.4report was the smallest, the data dispersion was small, and data quality of No.4 monitoring report was the best. It was proved that the reliability of the data was high. The analysis result of uncertainty of NOx concentration monitoring data in No.1 report showed that it was great, and the data dispersion was high. The quality control chart showed it was out of control.It is proved that the data quality was bad and the reliability was low. The uncertainty of NOxconcentration monitoring data in No.4 report was the smallest, the data dispersion was small,and data quality of No.4 monitoring report was the best. It was proved that the reliability of the data was high. The analysis results showed the uncertainty of SO2 concentration was significantly greater than NOx concentration with the same measuring principle. The component analysis of uncertainty showed that the uncertain degree of the SO2 concentration was mainly consisted of the measurement repeatability, indicating that the measurement process had greater effect on the monitoring of SO2 concentration.The measurement model was not only to analyse the uncertainty of CEMS. The different measurement methods or procedures were taken, the analysis model of the uncertainty degree was different. This paper established corresponding preliminary analysis model according to the CEMS equipment of a thermal power plant in Lanzhou, and calculated the uncertainty of each system without missing out any uncertain sources. Provide reference for uncertainty analysis in the field of automatic monitoring of flue gas. It was further explained that the analysis of uncertainty degree had important academic value and practical significance in environmental monitoring.