Abstract: In recent years, radioactive leakage incidents from unknown sources have garnered widespread attention. In response to such events, nuclear emergency responses often lack source term inputs, making it difficult to make radiation consequence assessment based on atmospheric dispersion models. As a result, methods for reconstructing radioactive leakage source parameters based on limited environmental monitoring data have become a research focus. This paper systematically introduces a comprehensive framework for radioactive leakage source parameter inversion, including four key elements: monitoring data, prior information, atmospheric dispersion models, and inversion methods. The inversion methods are classified into two major categories: iterative optimization methods and Bayesian inference methods. This study conducts an in-depth analysis and comparison of these two approaches, summarizes the latest research developments, and proposes future research direction based on a comprehensive evaluation of the performance of various methods.

Key words: radioactive leakage source parameter inversion, environmental monitoring data, atmospheric dispersion model, iterative optimization, Bayesian inference