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Predicting source or background radionuclide emissions is limited by the effort needed to run gas/aerosol atmospheric transport models (ATMs). A high-performance surrogate model is developed for the HYSPLIT4 (NOAA) ATM to accelerate transport simulation through model reduction, code optimization, and improved scaling on high performance computing systems. The surrogate model parameters are a grid of short-duration transport simulations stored offline. The surrogate model then predicts the path of a plume of radionuclide particles emitted from a source, or the field of sources which may have contributed to a detected signal, more efficiently than direct simulation by HYSPLIT4. Termed the Atmospheric Transport Model Surrogate (ATaMS), this suite of capabilities forms a basis to accelerate workflows for probabilistic source prediction and estimation of the radionuclide atmospheric background., (Copyright © 2022. Published by Elsevier Ltd.)

In the early years of nuclear explosion monitoring, experts used downwind detections with meaningful ratios of radioactive species to identify an explosion. Today's reality is sparse networks of radionuclide monitoring stations looking for weak signals. Analysts need to discriminate between industrial background radioactivity and nuclear explosion signals, even using the detection of one isotope. Aerosol and xenon measurements potentially related to nuclear tests in 2006 and 2013 announced by the Democratic People's Republic of Korea and from worldwide civilian background radioactivity are considered when defining radionuclide detection anomalies to objectively guide the use of limited analyst resources and reduce the possibility of not detecting nuclear explosions. [ABSTRACT FROM AUTHOR]

Abstract Many source-term estimation algorithms for atmospheric releases assume the measured concentration data are influenced only by the releases of interest. However, there are situations where identifying a short-term release from an unknown location in the presence of long-term releases from a different location is of interest. One such example is determining if part or all of a typical magnitude concentration of a radioactive isotope in a sampler came from a nuclear explosion, such as the explosion announced by DPRK in 2013, while medical isotope facilities and nuclear power plants were also operating in the region. An estimation algorithm has been developed for the case where a short-duration release is confounded by a long-term nuisance signal associated with an additional release location. The technique is demonstrated using synthetic release data for a hypothetical medical isotope production facility and a hypothetical puff release from a different location. The algorithm successfully determines the location (within 30 km) and time-varying release rate (within a factor of 2) for the medical isotope production facility and the location (within 60 km), time (within 6 h), and release magnitude (within a factor of 4) of the puff release. Highlights • New algorithm for source-term estimation for two or more concurrent release locations. • Algorithm quantifies uncertainty in the release time and location. • Algorithm performs successfully using synthetic data for two release locations. [ABSTRACT FROM AUTHOR]

Large networks producing frequent atmospheric radionuclide measurements have additional power in characterizing and localizing radionuclide release events over the analysis performed with four or fewer radionuclide measurements. However, adding unrelated measurements to an analysis dilutes that advantage, unless source-term models are extended to account for this complexity. A key steppingstone to obtaining network power is to select a group of related sample measurements that are associated with a release event. Such collections of measurements can be assembled by an analyst, or perhaps they can be selected by algorithm. The authors explore, using a year of atmospheric transport calculations and realistic sensor sensitivities, the potential for a computed radionuclide association tool. • Using a group of measurements associated with a radionuclide release can yield better event characterization. • Selecting the measurements is currently a subjective and analyst-intensive job. • Several possible automated association schemes exist to objectively select related measurements. • A pre-computed scheme based on recent weather requires only modest computations. [ABSTRACT FROM AUTHOR]

Algorithms that estimate the location and magnitude of an atmospheric release using remotely sampled air concentrations typically involve a single chemical or radioactive isotope. A new Bayesian algorithm is presented that makes discrimination between possible types of releases (e.g., nuclear explosion, nuclear power plant, or medical isotope production facility) an integral part of the analysis for samples that contain multiple isotopes. Algorithm performance is demonstrated using synthetic data and correctly discriminated between most release-type hypotheses, with higher accuracy when data are available on three or more isotopes. • New algorithm for source-term estimation using two or more isotopes. • The algorithm selects the most likely type (power plant, explosion, etc.) of release event. • More isotopes discriminate between release types better than two isotopes. [ABSTRACT FROM AUTHOR]

The International Monitoring System (IMS) of the Comprehensive-Nuclear-Test-Ban-Treaty monitors the atmosphere for radioactive xenon leaking from underground nuclear explosions. Emissions from medical isotope production represent a challenging background signal when determining whether measured radioxenon in the atmosphere is associated with a nuclear explosion prohibited by the treaty. The Australian Nuclear Science and Technology Organisation (ANSTO) operates a reactor and medical isotope production facility in Lucas Heights, Australia. This study uses two years of release data from the ANSTO medical isotope production facility and 133Xe data from three IMS sampling locations to estimate the annual releases of 133Xe from medical isotope production facilities in Argentina, South Africa, and Indonesia. Atmospheric dilution factors derived from a global atmospheric transport model were used in an optimization scheme to estimate annual release values by facility. The annual releases of about 6.8 × 1014 Bq from the ANSTO medical isotope production facility are in good agreement with the sampled concentrations at these three IMS sampling locations. Annual release estimates for the facility in South Africa vary from 2.2 × 1016 to 2.4 × 1016 Bq, estimates for the facility in Indonesia vary from 9.2 × 1013 to 3.7 × 1014 Bq and estimates for the facility in Argentina range from 4.5 × 1012 to 9.5 × 1012 Bq. [ABSTRACT FROM AUTHOR]

Pacific Northwest National Laboratory (PNNL) staff developed the Radionuclide Aerosol Sampler Analyzer (RASA) for worldwide aerosol monitoring in the 1990s. Recently, researchers at PNNL and Creare, LLC, have investigated possibilities for how RASA could be improved, based on lessons learned from more than 15 years of continuous operation, including during the Fukushima Daiichi Nuclear Power Plant disaster. Key themes addressed in upgrade possibilities include having a modular approach to additional radionuclide measurements, optimizing the sampling/analyzing times to improve detection location capabilities, and reducing power consumption by using electrostatic collection versus classic filtration collection. These individual efforts have been made in a modular context that might constitute retrofits to the existing RASA, modular components that could improve a manual monitoring approach, or a completely new RASA. Substantial optimization of the detection and location capabilities of an aerosol network is possible and new missions could be addressed by including additional measurements. • Improved collection and measurement technology reviewed for legacy aerosol systems. • New capabilities enable the verification responsibilities of aerosol systems in high-level release scenarios. • Electrostatic precipitation improves sample air volume per watt. • Simple MDC analysis shows existing systems could benefit from alternative operations. • Shorter sampling intervals will enable better source location estimates. [ABSTRACT FROM AUTHOR]