PEP-M4.
Design and Optimization of Ambient Air Monitoring Networks using Atmospheric Dispersion Modeling and Frequency of Detection Methods AS Rood*, K-Spar Inc
Abstract: Ambient air monitoring networks are a critical part of environmental monitoring programs at nuclear power plants, nuclear processing facilities, and U.S Department of Energy sites. Often times annual wind roses or dispersion patterns from an atmospheric transport model are used to establish air monitoring locations. While these methods provide a good first cut at favorable monitoring locations, they do not provide a quantitative measure of either a sampler or network performance in terms of meeting the performance objectives of the network. Frequency of detection analysis provides a rigorous structure to analyze quantitatively the performance of an air monitoring network. The analysis first defines of the performance objective of the network followed by a quantitative evaluation of the network that establishes its acceptability in terms of meeting the performance objective. Frequency of detection methods can be applied to design of a new network or evaluation of an existing networks. The analysis can determine optimal sampler placement and operating parameters and identify redundant samplers. This course will provide an overview of frequency of detection methods including defining performance objectives, developing input, interpreting results, and developing network optimization. The method requires an atmospheric transport model capable of calculating hourly time-integrated concentrations. Basic principles of atmospheric transport modeling important for frequency of detection analysis will be reviewed and discussed including industry standard codes. Application of the method will be illustrated using three case studies at the Idaho National Laboratory, Hanford Reservation, and a former uranium mine. Frequency of detection methods will be demonstrated using software available to the attendant. Site environmental monitoring program technical and managerial staff and regulators should find this course useful.
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