Recorded at AIHce EXP 2021
Continuing with the framework for RTDS deployment, Part 3 will discuss: 1) the needs assessment, selection, design, deployment and implementation of a mercury air monitoring system in a water treatment plant that processes radioactive wastewater; 2) the application of principal component analysis (PCA) as a decision-making tool; and 3) a case study involving dust monitoring data. Emphasis will be placed on: a) the AIHA Framework for Direct Reading Instruments; b) overcoming cultural challenges to IH decision-making; and c) customizing the detection system configuration to meet project objectives. Chemometric techniques, such as principal component analysis (PCA), can help in investigating the different correlations among variables (sensors) across the samples (data points). The PCA technique can be more effective because it considers the variance in the datasets all at once. The benefit of this analysis is a) recognition of anomalies; b) the verification of the effectiveness of interventions; and c) the identification of different trends. PCA empowers the IH to have a comprehensive overview of the hazard and its exposure risks.
Upon completion of the session, the participant will be able to:
- Develop a proposal for the use of continuous real-time monitoring systems.
- Apply Appendix B (EFCOG Paper) to direct-reading instruments/systems.
- Identify common obstacles to implementing real-time monitoring systems.
- Define continuous monitoring that is across agents, areas, and applicability.
- Use data to identify risk reduction targets instead of compliance.
- Analyze real-time sensor variability with chemometric techniques.
- Determine a datapoint from plant-wide sensors as the set of responses from each real-time sensor.
Dina Siegel, CIH CSP CBSP FAIHA
Alexander Brown, CIH, CSP
Dr. Emanuele Cauda