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Aerosol-cloud interactions play a vital role in climate change. This study leverages observations from the King-350 aircraft over the North China Plain on November 29, 2019, to examine aerosol and cloud microphysical characteristics of mixed-phase clouds. Through detailed vertical and spectral distributions, we investigate aerosol, cloud droplet, and ice crystal distributions in seeded clouds (SC) and natural precipitating clouds (NPC) within the same cloud system. From the vertical profile, SC and NPC have similar vertical distributions of aerosol and cloud droplets, with over 95 % of aerosols concentrated below 1600 m near the ground. Cloud droplets are more evenly distributed within the two clouds, cloud droplet number concentrations (Nc) in SC were three orders of magnitude higher than in NPC. Ice water content (IWC) and ice crystal number concentration (Ni) show distinct layer preferences-accumulating predominantly in SC's top layer and NPC's middle layer. From spectral distribution, a smaller proportion of cloud droplets (40-50 µm in diameter, the same hereafter) in SC compared to NPC. Rimed ice crystals and globular graupel (1325-1550 µm in diameter) were in SC, while plate and irregular ice crystals (300-450 µm) were in NPC with an order of magnitude higher than in SC. These microphysical differences highlight the complexity of cloud seeding efficacy, which varies based on cloud conditions and microphysical properties. In the first seeding, Ni increased by 1-2 orders of magnitude (125-300 µm) in the high Nc (Nc > 1.11 × 105 L-1) region. Seeding in low Nc (Nc < 1.11 × 105 L-1) regions was hard to be effective, especially in low Nc and low liquid water content (LWC) (LWC < 0.122 g/m3) regions. In the second seeding, ice crystals (125-250 µm) produced by the first seeding enhance the seeding efficiency. The responded regions were more sensitive to subsequent seeding, resulting in stronger reactions or longer duration.
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Low-altitude airspace is developing rapidly, but the utilization rate of airspace resources is low. Therefore, in order to solve the problem of the safe operation of the fusion of large UAVs and manned aircraft in the same airspace, this paper analyzes the theoretical calculation of the collision risk of the fusion operation of manned aircraft and UAVs at Feng Ming Airport in Zigong, verifying that while assessing the safety spacing of 10 km in the lateral direction, it further simulates the possibility of calculating the theoretical smaller safety spacing. The study will propose a new theory of error spacing safety margin and improve it according to the traditional Event collision risk model, combining the error spacing safety margin to establish an improved collision model more suitable for the fusion operation of manned and unmanned aircraft and reduce the redundancy of calculation. The error factors affecting manned and unmanned aircraft at Zigong Airport are analyzed, and theoretical calculations are analyzed by combining the actual data of Zigong Airport. Finally, the Monte Carlo simulation method is used to solve the error, substitute the calculation results, and simulate a section of the trajectory of the fusion operation for the reverse argument. The theoretical calculation results show that the collision risk from 10 km to 8 km satisfies the lateral target safety level (TSL) specified by ICAO under both traditional and improved models. The collision risk calculated by the improved model incorporating the error spacing safety margin is smaller, which enhances the safety of the model calculations. The results of the study can provide theoretical references for the fusion operation of manned and unmanned aircraft.
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High temperature superconductors (HTSs) are enablers of extensive electrification for aircraft propulsion. Indeed, if used in electrical machines, HTS materials can drastically improve their performance in terms of the power-to-weight ratio. Among the different topologies of superconducting electrical machines, a flux modulation machine based on HTS bulks is of interest for its compactness and light weight. Such a machine is proposed in the FROST (Flux-barrier Rotating Superconducting Topology) project led by Airbus to develop new technologies as part of their decarbonization goals driven by international policies. The rotor of the machine will house large ring-segment-shaped HTS bulks in order to increase the output power. However, the properties of those bulks are scarcely known and have barely been investigated in the literature. In this context, the present work aims to fill out partially this scarcity within the framework of FROST. Thus, a thorough characterisation of the performances and homogeneity of 11 large REBaCuO bulks was carried out. Ten of the bulks are to be utilized in the machine prototype, originally keeping the eleventh bulk as a spare. A first set of characterisation was conducted on the eleven bulks. For this set, the trapped field mapping and the critical current were estimated. Then, a series of in-depth characterisations on the eleventh bulk followed. It included critical current measurement, X-ray diffraction, and scanning electron microscopy on different millimetre-size samples cut out from the bulk at various locations. The X-ray diffraction and scanning electron microscopy showed weakly oxygenated regions inside the bulk explaining the local drop or loss in superconducting properties. The objective was to determine the causes of the inhomogeneities found in the trapped field measured on all the bulks, sacrificing one of them, here the spare one. To help obtain a clearer picture, a numerical model was then elaborated to reproduce the field map of the eleventh bulk using the experimental data obtained from the characterisation of its various small samples. It is concluded that further characterisations, including the statistics on various bulks, are still needed to understand the underlying reasons for inhomogeneity in the trapped field. Nonetheless, all the bulks presented enough current density to be usable in the construction of the proposed machine.
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This analysis examined systemic causes of Uncrewed Air Vehicle (UAV) accidents identifying operator, environmental, supervisory, and organisational factors through the use of the Human Factors Analysis and Classification System (HFACS). HFACS is a system-based analysis method for investigating the causal factors associated with accidents and incidents and has previously been used to reliably and systematically identify active and latent failures associated with both military and general aviation accidents. Whilst HFACS has previously been applied to UAV accidents, the last known application was conducted in 2014. Using reports retrieved from nine accident investigation organisations' databases, causal factors were coded against unsafe acts, preconditions, and failures at the supervisory, organisational, and environmental levels. Causal factors were assessed on 77 medium or large UAV mishaps/accidents that occurred over a 12-year period up to 2024. 42 mishap reports were deemed to involve a human factor as a causal factor. A large proportion of the mishaps contained factors attributed to Decision Errors at level 1 (Unsafe Acts) which was found to be associated with both the Technological Environment and Adverse Mental State at level 2 (Pre-conditions). Causal factors were identified at each of the other 3 levels (Supervisory, Organisational and External) with a number of emergent associations between causal factors. These data provide support for the identification and development of interventions aimed at improving the safety of organisations and advice of regulators for Uncrewed Air Systems.
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Aircraft ducts play an indispensable role in various systems of an aircraft. The regular inspection and maintenance of aircraft ducts are of great significance for preventing potential failures and ensuring the normal operation of the aircraft. Traditional manual inspection methods are costly and inefficient, especially under low-light conditions. To address these issues, we propose a new defect detection model called LESM-YOLO. In this study, we integrate a lighting enhancement module to improve the accuracy and recognition of the model under low-light conditions. Additionally, to reduce the model's parameter count, we employ space-to-depth convolution, making the model more lightweight and suitable for deployment on edge detection devices. Furthermore, we introduce Mixed Local Channel Attention (MLCA), which balances complexity and accuracy by combining local channel and spatial attention mechanisms, enhancing the overall performance of the model and improving the accuracy and robustness of defect detection. Finally, we compare the proposed model with other existing models to validate the effectiveness of LESM-YOLO. The test results show that our proposed model achieves an mAP of 96.3%, a 5.4% improvement over the original model, while maintaining a detection speed of 138.7, meeting real-time monitoring requirements. The model proposed in this paper provides valuable technical support for the detection of dark defects in aircraft ducts.
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BACKGROUND: Inter-hospital transfer is necessary for the transport of patients to specialized treatment. Rotor-wing aircraft may be used in lieu of ambulances in time-critical conditions over long distances and when specialist team skills are called for. The purpose of the review is to assess the current scientific literature that describes the scenario to develop a national guideline for inter-hospital transfers using rotor-wing aircraft. The aim is to describe the patterns and challenges. METHODS AND ANALYSIS: The authors will conduct a scoping review as per Joanna Briggs Institute guideline. The protocol for the scoping review will adhere to the Open Science Framework guideline for scoping reviews and we will report the findings of the scoping review as per PRISMA-ScR guideline. We have developed the search strategy with the help of a research librarian and will conduct search in relevant electronic databases and include gray literature as well, using the PRESS and PRISMA-S guidelines. Two authors will independently screen titles and abstracts for inclusion as per eligibility criteria and conflicts will be resolved by a third reviewer. Full text retrieval will be conducted accordingly. We will analyze the extracted data using validated statistical methods. ETHICS AND DISSEMINATION: According to Danish law, scoping reviews are exempt from ethics committee approval. The findings of this scoping review will provide the scientific foundation for a national guideline on rotor-wing aircraft conveyed inter-hospital transfers in Denmark. Furthermore, we will publish the results of the scoping review in a relevant scientific journal.
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Recently, Sustainable Aviation Fuel (SAF) blends and novel combustion technologies have been introduced to reduce aircraft engine emissions. However, there is limited knowledge about the impact of combustion technology and fuel composition on toxicity of primary Particulate Matter (PM) emissions, comparable to regulated non-volatile PM (nvPM). In this study, primary PM was collected on filters using a standardised approach, from both a Rich-Quench-Lean (RQL) combustion rig and a bespoke liquid fuelled Combustion Aerosol Standard (CAST) Generator burning 12 aviation fuels including conventional Jet-A, SAFs, and blends thereof. The fuels varied in aromatics (0-25.2%), sulphur (0-3000 ppm) and hydrogen (13.43-15.31%) contents. Toxicity of the collected primary PM was studied in vitro utilising Air-Liquid Interface (ALI) exposure of lung epithelial cells (Calu-3) in monoculture and co-culture with macrophages (differentiated THP-1 cells). Cells were exposed to PM extracted from filters and nebulised from suspensions using a cloud-based ALI exposure system. Toxicity readout parameters were analysed 24 h after exposure. Results showed presence of genotoxicity and changes in gene expression at dose levels which did not induce cytotoxicity. DNA damage was detected through Comet assay in cells exposed to CAST generated samples. Real-Time PCR performed to investigate the expression profile of genes involved in oxidative stress and DNA repair pathways showed different behaviours after exposure to the various PM samples. No differences were found in pro-inflammatory interleukin-8 secretion. This study indicates that primary PM toxicity is driven by wider factors than fuel composition, highlighting that further work is needed to substantiate the full toxicity of aircraft exhaust PM inclusive of secondary PM emanating from numerous engine technologies across the power range burning conventional Jet-A and SAF.
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Contaminantes Atmosféricos , Aeronaves , Daño del ADN , Material Particulado , Emisiones de Vehículos , Material Particulado/toxicidad , Material Particulado/análisis , Humanos , Contaminantes Atmosféricos/toxicidad , Contaminantes Atmosféricos/análisis , Emisiones de Vehículos/toxicidad , Emisiones de Vehículos/análisis , Línea Celular , Macrófagos/efectos de los fármacos , Células Epiteliales/efectos de los fármacos , Aerosoles/toxicidad , Aerosoles/análisis , AviaciónRESUMEN
Papiliotrema laurentii 5307AH was isolated from an aircraft polymer-coated surface. The genome size is 19,510,785 bp with a G + C content of 56%. The genome harbors genes encoding oxygenases, cutinases, lipases, and enzymes for styrene degradation, all of which could play a critical role in survival on xenobiotic surfaces.
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Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line-Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine's piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.
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To reveal complex causes of aircraft events, this paper aims to mine association rules between the trigger probability and relative strength via a modified Apriori algorithm. Clustering is adopted for data preprocessing and TF-IDF value calculation. Causative item sets of aircraft events are obtained based on the accident causation 2-4 model and are coded to establish code indicators. By avoiding the use of statistical methodologies to resolve not-a-number (NaN) values for altering the interrelations among causes, an enhancement in the Apriori algorithm is proposed by considering frequent items. By extracting frequent patterns, in this paper, all the association rules that satisfy three perspectives (support, confidence and lift) are determined by constantly generating and pruning candidate item sets. A network graph is used to visualize the association rules between different unsafe events and all types of causes. Finally, 9835 representative pieces of data, including general unsafe events, general incidents and serious incidents from the Southwest Air Traffic Management Bureau, are selected for analysis. The results show that improper energy allocation, poor conflict resolution ability, inadequate onsite management duties, adoption of a luck mentality, and occurrence of controller oversight are highly correlated with general unsafe events, and failure to rectify incorrect recitation is notably correlated with general incidents, while inadequate manual promotion, lack of conflict judgement and insufficient safety management are strongly correlated with serious incidents. This study quantitatively reveals the potential patterns and characteristics of mutual interactions among various types of historical aircraft events and highlights directions for controllable prevention and prediction of aircraft events.
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Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.
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The aircraft-acquired transmission of SARS-CoV-2 poses a public health risk. Following PRISMA guidelines, we conducted a systematic review and analysis of articles, published prior to vaccines being available, from 24 January 2020 to 20 April 2021 to identify factors important for transmission. Articles were included if they mentioned index cases and identifiable flight duration, and excluded if they discussed non-commercial aircraft, airflow or transmission models, cases without flight data, or that were unable to determine in-flight transmission. From the 15 articles selected for in-depth review, 50 total flights were analyzed by flight duration both as a categorical variable-short (<3 h), medium (3-6 h), or long flights (>6 h)-and as a continuous variable with case counts modeled by negative binomial regression. Compared to short flights without masking, medium and long flights without masking were associated with 4.66-fold increase (95% CI: [1.01, 21.52]; p < 0.0001) and 25.93-fold increase in incidence rates (95% CI: [4.1, 164]; p < 0.0001), respectively; long flights with enforced masking had no transmission reported. A 1 h increase in flight duration was associated with 1.53-fold (95% CI: [1.19, 1.66]; p < 0.001) increase in the incidence rate ratio (IRR) of cases. Masking should be considered for long flights.
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Aeronaves , COVID-19 , Humanos , COVID-19/transmisión , COVID-19/epidemiologíaRESUMEN
The growing use of thermoplastic composites (TPCs) like low-melting polyaryletherketone (LM-PAEK) matrices reinforced with unidirectional carbon fiber (CF) in aircraft structures presents a significant challenge in terms of lightning strikes and electromagnetic interference shielding during aircraft operations. This is due to the weak electrical conductivity of TPC structures, which results in widespread damage when struck by lightning. The repair and maintenance of these extended damaged sites can increase operational costs and loss of flights. Several lightning strike protection (LSP) systems have been developed and implemented to address these concerns. This study evaluated a highly conductive coating with a low filler rate for its effectiveness as an LSP solution for TPCs on exterior aircraft surfaces. The TPC panel without any coatings was first studied. Subsequently, the level of conductivity was increased by incorporating the nanoscale conductive fillers, silver-coated copper (Ag/Cu) nanoflakes, with a silver content of 20 wt.% (Ag20/Cu) and 30 wt.% (Ag30/Cu), correspondingly, into the coating at two loadings of 55 wt.% and 70 wt.% in an epoxy carrier for the surface coatings. The behavior of electrical and surface conductivity was thoroughly examined to understand the impact of Ag/Cu with a high aspect ratio and the effectiveness of the LSP solution. In addition, the spray-coated TPC panels underwent rigorous Zone 2A lightning strike testing using simulated lightning current, in agreement with the industry standard of Society of Automotive Engineers (SAE) Aerospace Recommended Practice (ARP) 5412B. Despite the higher resistance due to the lower conductive coating weight, the TPC panels with Ag30/Cu at loading of 70 wt.% achieved better results than those with Ag30/Cu at loading of 55 wt.%. This is evidenced by the minor structural delamination and CF breakage on the front surface, which proposes a new economic route for a sustainable post-processed LSP system in the aviation industry.
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This study addressed the critical problem of repairing cracks in aging aircraft structures, a safety concern of paramount importance given the extended service life of modern fleets. Utilized a finite element (FE) method enhanced by the design of experiments (DOE) and adaptive neuro-fuzzy inference system (ANFIS) approaches to analyze the efficacy of piezoelectric actuators in mitigating stress intensity factors (SIF) at crack tips-a novel integration in structural repair strategies. Through simulations, we examined the impact of various factors on the repair process, including the plate, actuator, and adhesive bond size and characteristics. In this work, initially, the SIF estimation used the FE approach at crack tips in aluminum 2024-T3 plate under the uniform uniaxial tensile load. Next, numerous simulations have been performed by changing the parameters and their levels to collect the data information for the analysis of the DOE and ANFIS approach. The FE simulation results have shown that changing the parameters and their levels will result in changing of SIF. Several DOE and ANFIS optimization cases have been performed for the depth analysis of parameters. The current results indicated that optimal placement, size, and voltage applied to the piezoelectric actuators are crucial for maximizing crack repair efficiency, with the ability to significantly reduce the SIF by a quantified percentage under specific conditions. This research surpasses previous efforts by providing a comprehensive parameter optimization of piezoelectric actuator application, offering a methodologically advanced and practically relevant pathway to enhance aircraft structural integrity and maintenance practices. The study innovation lies in its methodological fusion, which holistically examines the parameters influencing SIF reduction in aircraft crack repair, marking a significant leap in applying intelligent materials in aerospace engineering.
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This paper investigates the performance of concrete incorporating high-volume fly ash (HVFA) and steel slag aggregates against the detrimental effects of combined cycles of environmental thermal fatigue and exposure to leaked aircraft fluids. A total of 128 cubes and 90 prisms were cast for five mixes and exposed to 60, 120, 180, 240 and 300 combined cycles. The results demonstrate the positive effect of utilization of HVFA which reduces the total amount of portlandite available in the system. The SS aggregates demonstrate a strong interlocking with the surrounding matrix and supply the necessary portlandite for continued pozzolanic reaction. However, their reaction with aircraft fluids causes significant degradation to flexural strength initially, which is redeemed by pozzolanic reaction at a later stage. Hybrid basalt and polypropylene fibres were successful in enhancing the flexural strength and reducing the cracking. The mercury intrusion porosimetry revealed a reduction in pore volume because of HVFA. Scanning electron microscopy and differential scanning calorimetry were also employed to uncover the underlying mechanisms of damage and assess the performance of the cementitious composite.
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Radar-absorbing materials (RAMs) covering the exterior surfaces of installed parts and assembled devices are crucial in absorbing most incident electromagnetic (EM) waves. This absorption minimizes reflected energy, thereby enhancing pilot safety and the stability of operating electronic devices without interference. Particularly, active stealth aircraft require effective protection from near- and far-field EM radiation across a wide spectrum of frequencies from both highly integrated electronic components and advanced enemy radars. Studies of RAMs often prioritize absorption over crucial tunability in frequency selectivity, revealing a research gap. In this study, we propose smart RAMs with frequency-selective absorption capabilities. Our approach involves incorporating two types of core-shell spheres in a polymer matrix, which feature shells of either wave-diffuse reflecting metal or wave-absorbing graphene. The key innovation lies in the ability to tailor absorption frequencies in the X-band range (8.2-12.4 GHz) by adjusting the interstitial spaces between the metallic spheres while the scattered waves are efficiently attenuated by graphene networks in the composites. On a metal substrate, a 2 mm-thick composite with an optimized structural composition and ratio of the two types of spheres exhibits a maximum absorption efficiency of 99.3%, effectively trapping and extinguishing incident waves. Combined with the structural tunability and frequency-selective properties of spherical fillers, our approach provides a scalable and effective method for creating functional isotropic coverings on various metallic surfaces.
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Aluminum structures are routinely used in aircraft due to their lightweight and corrosion resistance properties. Multi-layered aluminum plates are generally joined by rivets forming regions which are prone to fatigue crack formation in an aircraft. Therefore, the detection and monitoring of fatigue cracks at rivet joints in aluminum structures are crucial for ensuring flight safety. In this study, piezoelectric sensors were utilized to generate and detect Lamb waves on aluminum plates with rivet joints to investigate the feasibility of a newly developed Sideband Peak Count (SPC) technique for detecting fatigue cracks around these joints. To overcome the limitations of existing SPC-I (Sideband Peak Count - Index) and SPI (Sideband Peak Intensity) techniques in capturing harmonic and modulating wave frequencies due to material nonlinearity, a comprehensive index, the Sideband Intensity Index (SII) is introduced. Comparative analysis with existing SPC-I and SPI techniques confirm the effectiveness of the SII technique. This investigation shows that the SII technique significantly improves the detection capability of initial fatigue cracks around rivet joints on aluminum plates. This study offers a more efficient method for detecting critical fatigue cracks in rivet joints.
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BACKGROUND: As global travel resumed in coronavirus disease 2019 (COVID-19) endemicity, the potential of aircraft wastewater monitoring to provide early warning of disease trends for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and other infectious diseases, particularly at international air travel hubs, was recognized. We therefore assessed and compared the feasibility of testing wastewater from inbound aircraft and airport terminals for 18 pathogens including SARS-CoV-2 in Singapore, a popular travel hub in Asia. METHODS: Wastewater samples collected from inbound medium- and long-haul flights and airport terminals were tested for SARS-CoV-2. Next Generation Sequencing was carried out on positive samples to identify SARS-CoV-2 variants. Airport and aircraft samples were further tested for 17 other pathogens through quantitative reverse transcription polymerase chain reaction. RESULTS: The proportion of SARS-CoV-2-positive samples and the average virus load was higher for wastewater samples from aircraft as compared with airport terminals. Cross-correlation analyses indicated that viral load trends from airport wastewater led local COVID-19 case trends by 2-5 days. A total of 10 variants (44 sub-lineages) were successfully identified from aircraft wastewater and airport terminals, and four variants of interest and one variant under monitoring were detected in aircraft and airport wastewater 18-31 days prior to detection in local clinical cases. The detection of five respiratory and four enteric viruses in aircraft wastewater samples further underscores the potential to expand aircraft wastewater to monitoring pathogens beyond SARS-CoV-2. CONCLUSION: Our findings demonstrate the feasibility of aircraft wastewater testing for monitoring infectious diseases threats, potentially detecting signals before clinical cases are reported. The triangulation of similar datapoints from aircraft wastewater of international travel nodes could therefore serve as a useful early warning system for global health threats.
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Aeronaves , Aeropuertos , COVID-19 , SARS-CoV-2 , Aguas Residuales , Humanos , SARS-CoV-2/genética , SARS-CoV-2/aislamiento & purificación , Aguas Residuales/virología , COVID-19/diagnóstico , COVID-19/epidemiología , Singapur/epidemiología , Carga ViralRESUMEN
Air travel has an important role in the spread of viral acute respiratory infections (ARIs). Aircraft offer an ideal setting for the transmission of ARI because of a closed environment, crowded conditions, and close-contact setting. Numerous studies have shown that influenza and COVID-19 spread readily in an aircraft with one virus-positive symptomatic or asymptomatic index case. The numbers of secondary cases differ markedly in different studies most probably because of the wide variation of the infectiousness of the infector as well as the susceptibility of the infectees. The primary risk factor is sitting within two rows of an infectious passenger. Elite athletes travel frequently and are thus prone to contracting an ARI during travel. It is anecdotally known in the sport and exercise medicine community that athletes often contract ARI during air travel. The degree to which athletes are infected in an aircraft by respiratory viruses is unclear. Two recent studies suggest that 8% of Team Finland members traveling to major winter sports events contracted the common cold most probably during air travel. Further prospective clinical studies with viral diagnostics are needed to understand the transmission dynamics and to develop effective and socially acceptable preventive measures during air travel.