Shipboard cabins may experience persistent emissions of oil aerosols and vapors during mechanically intensive operation, while limited ventilation promotes long-term accumulation on surfaces and in materials. To characterize such contamination, we developed a compound-resolved multiphase mass-transfer model coupling gas–particle-surface exchange, dynamic organic-film growth on impermeable surfaces, and depth-resolved transport in permeable materials. Based on qualitative source characterization, 32 oil-borne organic pollutants were simulated under an equal-mass assumption to examine compound-dependent distribution, accumulation, and exposure. Validation of the air–particle–dust transport framework against published indoor measurements showed satisfactory agreement for airborne and settled-dust concentrations. Under zero external ventilation, total suspended particles, particle-phase oil, and gas-phase oil stabilized at 3.2 mg/m³, 1.75 × 10³ μg/m³, and 1.5 × 10² μg/m³, respectively, compared with 0.05 mg/m³, 2.15 μg/m³, and 1.75 μg/m³ under ventilation. In permeable materials, the near-surface dust concentration reached about 2.0 kg/m³ under zero external ventilation, approximately 40 times the ventilated value, while the total internal oil concentration was nearly 3.5 × 10⁹ μg/m³ under zero external ventilation and on the order of 10⁷ μg/m³ under ventilation. Upward-facing oil films reached about 700 nm by day 365 under zero external ventilation. Under the conservative continuous-exposure scenario, total daily intake decreased from approximately 5 × 10² μg/(kg·day) under zero external ventilation to 4 μg/(kg·day) under ventilation, while the corresponding screening-level hazard index decreased from 49–62 to 0.25–0.46. These results provide a mechanistic basis for evaluating multiphase pollutant accumulation, crew exposure, and contamination-control strategies in confined shipboard environments.

Building energy flexibility is crucial for developing sustainable and resilient power grids. Airport terminals with high energy intensity and substantial carbon footprints are increasingly recognized as promising flexibility providers in electricity market. However, their dynamic occupancy patterns, omission of load aggregator, and stringent passenger service requirement pose significant challenges to their participation in demand response (DR) programs. To address these challenges, this work develops a multi-zone indoor temperature set-point optimization method based on spatiotemporal occupancy and passenger complaint constraint to unlock energy flexibility. First, a relation between allowable temperature offsets and spatiotemporal occupancy under the passenger complaint constraint was determined, and a DR-oriented PMV model to activate multi-zone flexibilities across different functional areas and seasons were established. Next, non-linear programming was used to generate optimal indoor temperature set-point profiles to balance economy-environment-passenger benefits. Last, a data-driven MPC for indoor temperature was conducted to unlock energy flexibility, and the Monte Carlo technique was employed to quantify its uncertainty associated with weather and holidays under multi-aggregation and multi-duration scales. The results showed that the proposed method enhanced the allowable temperature offset by 0.73 ℃, achieved a load-shifting capacity of 0.25 kWh/m², and reduced carbon emissions by 30%, saved electricity costs by 16% during the cooling season. The uncertainty of energy flexibility for cluster aggregating 63k m² consistently remained below 14% over periods ranging from one week to two months. This work provides a practical methodology and a reliable quantitative reference for airport terminals to participate in DR programs.