Aerial logistics systems are increasingly being explored for time-critical operations such as emergency response, medical supply delivery, and rural connectivity. However, conventional routing approaches often assume static, symmetric travel costs that do not capture the environment-dependent nature of aerial transportation. In practice, wind speed and wind direction can directly affect energy consumption, route feasibility, and remaining battery reserve. This paper presents a simulation-driven routing framework for environment-aware aerial logistics in which directed edge costs are computed dynamically using a reduced-order energy model. The framework estimates edge energy from route distance, travel bearing, payload, vehicle characteristics, and wind alignment, allowing the routing cost matrix to change across environmental scenarios. A geospatially grounded rural logistics network with a central depot and multiple county-level service locations is used for evaluation. Controlled wind scenarios are simulated to isolate the impact of wind direction on routing decisions. Results show that wind produces asymmetric edge costs, triggers route-switching behavior, and creates measurable differences between distance-based and environment-aware routing solutions. Compared with distance-based routing, the proposed approach reduces energy consumption under several wind scenarios while preserving route-level battery feasibility. These findings demonstrate the importance of treating aerial logistics routing costs as dynamic outputs of system behavior rather than fixed network attributes.