To overcome the limitations of static airport noise assessment, this paper proposes a dynamic evaluation framework that integrates data-driven and simulation-based approaches. Based on ADS-B data, a two-stage clustering method is employed to extract representative flight trajectories. Noise simulation is conducted using the Aviation Environmental Design Tool (AEDT), and by integrating high-resolution population data, a spatial noise-population exposure model is constructed, enabling simultaneous fine-grained assessment of both the noise-affected area and the exposed population. The results show that NADP2 performs better in reducing the impacted area within the 70 — 80dB range, whereas NADP1 achieves more pronounced noise reduction in high-noise regions above 85dB. A key policy-relevant paradox is revealed: noise abatement procedures can reduce the overall noise-impacted area, yet may increase population exposure due to spatial redistribution of the noise field. This finding underscores the necessity of incorporating demographic data into dynamic airport noise management.
Li et al. (Tue,) studied this question.