Assessment of SRS ambient air monitoring network

doi:10.2172/1288261

GSTDTAP > 地球科学

DOI	10.2172/1288261
报告编号	SRNL--STI-2016-00403_R1
来源ID	OSTI ID: 1288261
	Assessment of SRS ambient air monitoring network
	Abbott, K.; Jannik, T.
	2016-08-03
出版年	2016
页数	28
语种	英语
国家	美国
领域	地球科学
英文摘要	Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, if any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the air monitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned
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来源平台	US Department of Energy (DOE)
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/7153
专题	地球科学
推荐引用方式 GB/T 7714	Abbott, K.,Jannik, T.. Assessment of SRS ambient air monitoring network,2016.