Volume 67 Issue 5
May  2023
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MA Yunyun, CHAI Wenxuan, LI Hongli, ZOU Yingjie, XIE Qian, XIAO Yang, XU Weihong. A Study on the Methodology for Evaluating the Quality Control Status of VOCs Monitoring Systems through Statistical Analysis[J]. Metrology Science and Technology, 2023, 67(5): 64-71. doi: 10.12338/j.issn.2096-9015.2023.0063
Citation: MA Yunyun, CHAI Wenxuan, LI Hongli, ZOU Yingjie, XIE Qian, XIAO Yang, XU Weihong. A Study on the Methodology for Evaluating the Quality Control Status of VOCs Monitoring Systems through Statistical Analysis[J]. Metrology Science and Technology, 2023, 67(5): 64-71. doi: 10.12338/j.issn.2096-9015.2023.0063

A Study on the Methodology for Evaluating the Quality Control Status of VOCs Monitoring Systems through Statistical Analysis

doi: 10.12338/j.issn.2096-9015.2023.0063
  • Received Date: 2023-03-08
  • Accepted Date: 2023-05-10
  • Rev Recd Date: 2023-05-19
  • Available Online: 2023-08-01
  • Publish Date: 2023-05-31
  • Monitoring photochemical precursors in the atmosphere can provide essential data for researching the formation mechanisms of composite pollution from ozone (O3) and fine particulate matter (PM2.5). The quality of the monitoring data significantly influences the accuracy of air pollution control measures. Therefore, executing scientific monitoring is critical for preventive measures and has paramount importance in continually improving China's air quality. Volatile Organic Compounds (VOCs), key precursors to O3 and PM2.5 pollution, participate in photochemical reactions in the atmosphere. This paper introduces the structure and function of VOCs' online monitoring systems in the photochemical monitoring network. After a preliminary analysis of quality control indicators and error sources, potential typical array distribution forms of quality control results were discussed. The paper further explores methods for evaluating the quality control status of the monitoring system through statistical analysis and conducts correlation analyses between residuals and quality control results, as well as between operational duration and component qualification rates. The paper recommends collecting a large sample of quality control data, carrying out systematic and meticulous correlation analyses among quality control indicators, and investigating factors that affect the quality control status of the monitoring system and the quality of measured data.
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