Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis

Yang Shuo, Zhiqiang Pan, X. Niu, Geng Lei, Zhijing Sun, Dongchang Ma, Douwen Wang
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Abstract

: Concerning the SO 2 pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS 0 ), constant bias correction (CSS 1 ) and linear bias correction (CSS 2 ) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i
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基于回归分析的工厂排放污染物SO2在线监测结果可靠性研究
关于so2污染源的监测,一直是环境学界讨论甚至争论的话题。坚持“绿水青山就是金山银山”的宗旨,当务之急是建立完整、正确的QA/QC监控体系。在中国,由于在线设备相对于实验室技术的优势,有大量的在线设备可以进行测试。但是,也不得不承认,在线系统属于非标准系统,更应该关注其有效性。本文采用一种可变误差模型的Deming回归技术,逐步进行无偏校正(css0)、常偏校正(css1)和线性偏校正(css2),在在线与标准系统之间的层次上进行拟合。然后对所选的CSS进行F和t以及χ2分布检验。最后,在独立同分布(i
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