To address the issues of energy waste in air conditioning systems and reduced passenger comfort caused by load variations and uneven spatiotemporal distribution of passenger flow in multifunctional zones of airport terminals, a spatiotemporal distribution model of passenger flow that integrates dwell and movement behaviors was constructed. Furthermore, a dual-layer operation optimization strategy for air conditioning systems was proposed, jointly considering thermal-humidity comfort and indoor air quality. A model predictive control algorithm was employed in the strategy, where the upper thermal-humidity optimization layer dynamically adjusts air supply parameters, while the lower fresh air optimization layer dynamically regulates the fresh air ratio, achieving rolling-horizon optimization. Simulation results indicate that, compared to the baseline strategy relying solely on temperature control, the proposed strategy synergistically incorporates thermal-humidity regulation, fresh air optimization and passenger flow responsiveness. Under the premise of ensuring zonal thermal-humidity comfort and air quality, this strategy achieves a 14.6% reduction in air conditioning energy consumption.