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Dynamic Demand and Capacity Balancing (dDCB) focuses on reducing the existent gap between the Air Traffic Flow and Capacity Management (ATFCM) and the Air Traffic Control (ATC) activities by introducing a more dynamic management of the airspace resources. This dynamism could be achieved by the application of Short-Term ATFCM Measures (STAM) that consists of detecting potential hotspots, identifying the flights producing the complexity, and applying minor changes to selected flights. This thesis presents a research about the application of STAM in a Multi-Airport System (MAS). Firstly, it is proposed an Operational Concept (OpsCon) designed to apply those STAMs that suggest changes in the take-off time of selected flights (temporal displacements in the planned trajectory). The operational concept is tested by real-time simulations (including the human- in-the-loop) with the objective of evaluating the performance of the ground ATCOs while dealing with most of the uncertainties produced before take-off. Subsequently, it is proposed a methodology that characterizes and evaluates the performance of the aircraft operation in a complex systemized TMA based on the study of its standard routes and their actual traffic in order to reduce the uncertainties after take-off. The process is composed of two main components. The first component identifies recurrent deviation patterns by comparing the Spatio-Temporal (S-T) differences between the actual and planned trajectories. The second component identifies and characterizes concurrence events based on the analysis of the standard routes and the along-track deviation derived from the first component with the objective to analyse the causes that produce recurrent patterns in the terminal airspace. The developed framework is applied to a study case of a representative MAS. The quantitative effectiveness of the framework is derived by simulations using historical traffic data samples of the London TMA.