Systems approach to evaluating sensor characteristics for real-time monitoring of high-risk indoor contaminant releases

Sreedharan, Priya; Sohn, Michael D.; Gadgil, Ashok J.; Nazaroff, William W.

doi:10.1016/j.atmosenv.2006.01.052

Systems approach to evaluating sensor characteristics for real-time monitoring of high-risk indoor contaminant releases

Journal Article · Wed Mar 22 00:00:00 EST 2006 · Atmospheric Environment (1994)

DOI:https://doi.org/10.1016/j.atmosenv.2006.01.052· OSTI ID:1826684

Sreedharan, Priya ^[1]; Sohn, Michael D. ^[2]; Gadgil, Ashok J. ^[2]; Nazaroff, William W. ^[1]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Rapid detection of toxic agents in the indoor environment is essential for protecting building occupants from accidental or intentional releases. While there is much research dedicated to designing sensors to detect airborne toxic contaminants, little research has addressed how to incorporate such sensors into a monitoring system designed to protect building occupants. To design sensor systems, one must quantify design tradeoffs, such as response time and accuracy, and select values to optimize the performance of an overall system. Here, we illustrate the importance of a systems approach for properly evaluating such tradeoffs, using data from tracer gas experiments conducted in a three-floor building at the Dugway Proving Grounds, Utah. We explore how well a Bayesian interpretation approach can characterize an indoor release using threshold sensor data. We use this approach to assess the effects of various sensor characteristics, such as response time, threshold level, and accuracy, on overall system performance. The system performance is evaluated in terms of the time needed to characterize the release (location, amount released, and duration). We demonstrate that a systems perspective enables selecting sensor characteristics that optimize the system as a whole.

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231; AC03-76SF00098

OSTI ID:: 1826684

Journal Information:: Atmospheric Environment (1994), Journal Name: Atmospheric Environment (1994) Journal Issue: 19 Vol. 40; ISSN 1352-2310

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Identification of indoor contaminant source location by a single concentration sensor Wang, Lin-Lin; You, Xue-Yi Air Quality, Atmosphere & Health, Vol. 8, Issue 1 https://doi.org/10.1007/s11869-014-0280-9	journal	July 2014
Multi-objective optimization for sensor placement against suddenly released contaminant in air duct system Gao, Jun; Zeng, Lingjie; Cao, Changsheng Building Simulation, Vol. 11, Issue 1 https://doi.org/10.1007/s12273-017-0374-z	journal	May 2017
Locating time-varying contaminant sources in 3D indoor environments with three typical ventilation systems using a multi-robot active olfaction method Feng, Qilin; Cai, Hao; Li, Fei Building Simulation, Vol. 11, Issue 3 https://doi.org/10.1007/s12273-017-0424-6	journal	December 2017
Estimates of pollutant temporal and spatial variability in commercial buildings from the joint urban 2003 field experiments Sohn, Michael D.; Li, Xiwang; Chan, Wanyu R. Indoor Air, Vol. 30, Issue 2 https://doi.org/10.1111/ina.12626	journal	December 2019

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