The work for both flight crews and ATCOs can have no room for errors as their decisions have a direct implication on the safety of the passengers on board [4]. For instance, a mid-air collision might result if the flight crews in charge do not follow the appropriate instructions from the ATCOs, or if the ATCOs issue an instruction that is not feasible from the pilots' perspective. The accidents resulted would transfer to injuries and casualties; thus, a zero-tolerance policy to safety regulation violations is enforced mandatorily in air-transport operations. Nevertheless, human error is inevitable during the flight crews' and ATCOs' decision-making processes, but the corresponding risk should be mitigated or minimised to a level that is generally acceptable by the industry. Human error is prevalent in every industry, and, in principle, 90% of workplace accidents are caused by human errors [5]. In aviation, up to 80% of accidents result from human errors [6]. With the increased workload of the operators, such accidents are more likely to happen in dense air traffic environments. To minimise the potential faults from happening in real ATC situations, decent training, licence renewals, annual reassessment under normal and emergency procedures [7], and decision aids are common strategies that are proven effective and are widely adopted in the airline and flight training industry. Most airlines and flight training schools have adopted the digital twin of a real aircraft (high-fidelity flight simulators) as the key equipment to train pilots with a lowered risk of accidents [8; 9]. According to the AIAA Digital Engineering Integration Committee [10], a digital twin is defined as \"a set of virtual information constructs that mimics the structure, context, and behaviour of an individual/unique physical asset, or a group of physical assets, is dynamically updated with data from its physical twin throughout its life cycle and informs decisions that realise value\". Digital twins are also integrated for offline training with real-time monitoring, decision making, data-driven modelling and analytics [11], and human-computer-machine fusion [12]. The high-fidelity flight simulator software (mimicking the actual flight operations) in commercial settings is connected with third-party physical assets to formulate a digital twin environment, with the virtual training scenario being dynamically updated on the basis of actual physical inputs from assets. On the ATC side, the training of ATCOs is also done via digital twin with pre-set scenarios [13]. The complexity of ATC tasks is a result of its multimodality and the task nature as the coordinator to control the operations of different aircraft in the airspace using dissimilar technologies [14]. In academic research, digital twins are also widely used to analyse human performance in ATC [15; 16; 17]. For instance, [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [17] investigated the situational awareness and stress level of ATCOs via ATC simulators with the aid of electroencephalography (EEG). [PERSON] et al. [18] correlated situational awareness and signals from EEG with assigned tasks to subjects, and this could be implemented in the ATC context with ATC digital twin by assigning context-related tasks. Yet, existing training which focuses on analysing human performance only cannot cope with the swelling air traffic volume. The use of digital twin plays a crucial role in driving industrial skill training and academic research, and proper decision aids could minimise human errors in aviation. As operations in aviation require collaborative actions from different stakeholders, every collaborating party could be jointly considered as a team [19; 20; 21]. In air traffic operations, the team comprises at least the flight crews and the ATCOs. Hence, their performance and effectiveness should be well managed in order to ensure the team's ability to safeguard the passengers' wellbeing.