In recent years, air emergency rescue capabilities have become increasingly important as an indicator of national comprehensive strength and development status. Air emergency rescue performs an indispensable role in addressing social emergencies by virtue of its fast response capabilities and extensive coverage. This vital aspect of emergency response ensures the timely deployment of rescue personnel and resources, enabling efficient operations in diverse and often challenging environments. To enhance regional emergency response capabilities, this paper presents a novel siting model that overcomes the limitation of single-objective approaches by integrating multiple objectives and considering the synergistic effects of network nodes, and the corresponding efficient solving algorithm is designed for this model. First, a multi-objective optimization function is established that fully incorporates the construction cost of the rescue station, response time, and radiation range. A radiation function is developed to evaluate the degree of radiation for each candidate airport. Second, the multi-objective jellyfish search algorithm (MOJS) is employed to search for Pareto optimal solutions of the model using MATLAB tools. Finally, the proposed algorithm is applied to analyze and verify the site selection for a regional air emergency rescue center in a certain region of China, and ArcGIS tools are used to draw the site selection results separately by prioritizing the construction cost under different numbers of site selection points. The results demonstrate that the proposed model can achieve the desired site selection goals, thus providing a feasible and accurate method for future air emergency rescue station selection problems.