This paper studies fairness in Air Traffic Flow Management (ATFM). The existing models for ATFM do not impose the following two controls: 1) they don’t ensure that the order of flight arrivals in the resulting solution is close to the flight ordering in the original published schedules, ie, there are no guarantees on the number of pairwise reversals and 2) the airlines are not taken into account in the decision-making process, ie, there are no guarantees on the resulting distribution of delays across the airlines involved. We collectively call the lack of these controls as “fairness issues”. This paper makes the following contributions:(a) we formulate these two “fairness” controls as integer programming models;(b) we provide empirical results of the proposed optimization models on real world, national-scale datasets spanning across six days that illustrate that the proposed models successfully address these “fairness issues”;(c) we report computational times of less than 30 minutes for upto 25 airports and provide theoretical evidence on the strength of our formulations;(d) we achieve solutions that are attractive from both “fairness” perspectives with a relatively small increase in total delay costs (less than 10%).