Source term determination with elastic plume bias correction

Area of Science:

• Environmental Science
• Atmospheric Science
• Nuclear Science

Background:

• Accurate estimation of atmospheric radionuclide emissions is crucial for nuclear emergency response and accident analysis.
• Current source term estimates are often inaccurate due to biases in atmospheric transport and meteorological data.
• Existing methods lack robust bias correction, impacting the reliability of emergency response predictions.

Purpose of the Study:

• To develop and validate a novel method for atmospheric plume bias correction to improve source term estimation.
• To enhance the accuracy of radionuclide release rate calculations by incorporating concentration gradient information.
• To provide a versatile plume bias correction method applicable to various atmospheric hazardous material releases.

Main Methods:

• Proposed an elastic model for plume bias correction, utilizing concentration gradients from neighborhood measurements.
• Integrated information on concentration gradients already available from atmospheric transport models.
• Employed regularization techniques based on the known topology of the measurement network for model stability.

Main Results:

• Validated the methodology using data from the European Tracer Experiment.
• Demonstrated the method's effectiveness in a challenging case involving Ruthenium-106 (¹⁰⁶Ru) over Europe in 2017.
• Achieved significantly improved reconstruction of measurements compared to state-of-the-art estimates.

Conclusions:

• The proposed plume bias correction method effectively reduces uncertainties in source term estimation.
• The method can be coupled with existing source term estimation algorithms for immediate application.
• This approach offers a significant advancement for nuclear safety and environmental monitoring.