Projected network performance for next generation aerosol monitoring systems

Comparison of source-location algorithms for atmospheric samplers

Numerous algorithms have been developed to determine the source characteristics for an atmospheric radionuclide release, e.g., (Bieringer et al., 2017). This study compares three models that have been applied to the data collected by the International Monitoring System operated by the Comprehensive Nuclear-Test-Ban Treaty Organization Preparatory Commission to estimate source event parameters. Each model uses a different approach to estimate the parameters. A deterministic model uses a possible source region (PSR) approach (Ringbom et al., 2014) that is based on the correlation between predicted and measured sample values. A model (now called BAYEST) developed at Pacific Northwest National Laboratory uses a Bayesian formulation (Eslinger et al., 2019, 2020; Eslinger and Schrom, 2016). The FREAR model uses a different Bayesian formulation (De Meutter and Hoffman, 2020; De Meutter et al., 2021a, 2021b). The performance of the three source-location models is evaluated with 100 synthetic release cases for the single xenon isotope, 133Xe. The release cases resulted in detections in a fictitious network with 120 noble gas samplers. All three source-location models use the same sampling data. The two Bayesian models yield more accurate location estimates than the deterministic PSR model, with FREAR having slightly better location performance than BAYEST. Samplers with collection periods of 3, 6, 8, 12, and 24-h were used. Results from BAYEST show that location accuracy improves with each reduction in sample collection length. The BAYEST model is slightly better for estimating the start time of the release. The PSR model has about the same spread in start times as the FREAR model, but the PSR results have a better average start time. The Bayesian source-location algorithms give more accurate results than the PSR approach, and provide release magnitude estimates, while the base PSR model does not estimate the release magnitude. This investigation demonstrates that a reasonably dense sampling grid will sometimes yield poor location and time estimates regardless of the model. The poor estimates generally coincide with cases where there is a much larger distance between the release point and the first detecting sampler than the average sampler spacing.

Examining the potential for detecting simultaneous noble gas and aerosol samples in the international monitoring system radionuclide network

The purpose of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is to establish a legally binding ban on nuclear weapon test explosions or any other nuclear explosions. The Preparatory Commission for the CTBT Organization (CTBTO PrepCom) is developing the International Monitoring System (IMS) that includes a global network of 80 stations to monitor for airborne radionuclides upon entry into force of the CTBT. All 80 radionuclide stations will monitor for particulate radionuclides and at least half of the stations will monitor for radioxenon. The airborne radionuclide monitoring is an important verification technology both for the detection of a radionuclide release and in the determination of whether the release event originates from a nuclear explosion as opposed to an industrial use of nuclear materials. Nuclear power plants and many medical isotope production facilities release radioxenon into the atmosphere. Low levels of a few particulate isotopes, such as iodine, may also be released. Detections of multiple isotopes are useful for screening the radionuclide samples for relevance to the Treaty. This paper examines the anticipated joint detections in the IMS of noble gas and particulate isotopes from underground nuclear explosions where breaches in the underground containment vents from low levels to up to 1% of the radionuclide inventory of the resulting fission products to the atmosphere. Detection probabilities are based on 844 simulated release events spaced out at 17 release locations and one year in time. Six different release (venting) scenarios, including two fractionated scenarios, were analyzed. When ranked by detection probability, 11 particulate isotopes and one noble gas isotope (133Xe) appear in the top 20 isotopes for all six release scenarios. Using the 11 particulate isotopes and the one noble gas isotope, the IMS has nearly the same detection probability as when 45 particulate and 4 noble gas isotopes are used. Thus, a limited list of relevant radionuclides may be sufficient for treaty verification purposes. The probability that at least one particulate and at least one radioxenon isotope would be detected in the IMS from the release events ranged from 0.15 to 0.86 depending on the release scenario.

Radionuclide measurements of the international monitoring system

The International Monitoring System (IMS) is a unique global network of sensors, tuned to measure various phenomenology, with the common goal of detecting a nuclear explosion anywhere in the world. One component of this network collects measurements of radioactive particulates and gases (collectively known as radionuclides) present in the atmosphere; through this, compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) can be verified. The radionuclide sub-network consists of 120 sensors across 80 locations, supported by 16 measurement laboratories. All radionuclide stations make use of a form of γ-ray spectroscopy to measure radionuclides from samples; this remains largely unchanged since the network was first established 25 years ago. Advances in sampling and spectroscopy systems can yield improvements to the sensitivity of the network to detect a nuclear explosion. This paper summarises the status of the IMS radionuclide network, the current suite of technology used and reviews new technology that could enhance future iterations, potentially improving the verification power of the IMS.

Electrostatic precipitator collection efficiency studies using atmospheric radon progeny as aerosol analogs for nuclear explosion radionuclides

Electrostatic precipitation (ESP) is an attractive low-powered collection mechanism for mobile and fixed aerosol detection of radionuclides (RNs) for Nuclear Explosion Monitoring (NEM). Aerosol samplers deployed in the International Monitoring System use a blower to draw air through a filter media to collect particulates. ESP-based samplers collect aerosols without a filter, which can greatly increase volumetric flow capacity per watt of power consumed. ESP-based collectors may be optimized to perform low-power mobile RN collection or to improve the air throughput of existing monitoring stations. This effort describes the use of unknown concentrations of atmospheric RNs to determine the collection efficiency of a compact ESP design. For this analysis, naturally occurring radon progeny are simultaneously collected by a single stage wire-plate ESP and a filter-based sampler with a known collection efficiency. The activity of resulting samples is measured with gamma-spectroscopy and decay corrected for analysis time offsets. RN collection efficiencies are then derived for an experimental survey of ESP operational parameters that influence the ionization, transit, and collection of aerosols. At volumetric flow rates of 1.5-2 CMM, the optimized collection efficiency was calculated as 21±2%, and slower rates around 0.5 CMM resulted in 55 ±5% collection efficiency. The monitoring performance of the ESP-based collector was assessed for a simplified nuclear explosion source term by calculating the minimal detectable concentrations of short-lived fission & activation products. Results of the study suggest that a low-power ESP is feasible for NEM at distances of 100s of km.