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Global nuclear security is threatened by nuclear accidents and the purposeful use of nuclear weapons. Accordingly, atmospheric pollution prediction and control for nuclear accidents, including identifying sources in nuclear or radiological incidents, predicting hazards to persons and environments, and optimally controlling accident hazards, are current areas of nuclear security research. Source inversion, hazard prediction, and optimal control are three interrelated key issues for nuclear accident emergencies. Although progress has been made in hazard prediction for nuclear accidents since the 1970s and some source inversion methods were presented after the Fukushima nuclear accident, optimal control methods are rarely reported, source inversion methods are less practical, and prediction accuracy remains unsatisfactory. Thus, novel theories are required for optimal control and source inversion for nuclear accidents, and to develop methods for simulating the influences of radioactive plume dispersion and deposition under complex meteorological and terrain conditions. This work reviews the current progress, uncertainties, and research needs in nuclear security. In addition, a rapid source inversion method based on the Lagrangian model is developed and implemented in a test case. To address future challenges, an innovative architecture for Atmospheric Pollution Prediction and Optimal Control System for nuclear accidents (APPOCS) is proposed, and the perspectives are generalized to promote future research on nuclear accident hazard prediction and optimal control. At this time, forward-looking ideas and revolutionary perspectives are required to foster nuclear security research in the academic community.