Search

In the present paper, the effect of the depth of the bedrock layer on the land subsidence of the Isfahan plain was studied. The geological bedrock layer was modeled by the results of obtained data from the geotechnical exploratory boreholes, depth of deep wells and geoelectrical in-situ imaging. Regarding the bedrock depth, the case study area was classified into six categories (None, very low, low, medium, high and very high) to show the land subsidence potential zones and to evaluate the risk of the vertical displacement of some critical places. The results indicate that the most of the historical buildings are located in very low-risk and low-risk of the land subsidence areas, however, some places such as Isfahan international airport need land subsidence consideration for any probable destructions due to the vertical displacements.

The short-term deformation of Cochin International Airport Limited (CIAL), southwestern India, built on the massive floodplain of the Periyar River, is the topic of inquiry in this study. An unprecedented flood of August 2018 instigated a refined understanding of the ground deformation, if any, of the CIAL property. Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), using Sentinel-1A images, was used for documenting the ground deformation, which generated 5563 Persistent Scatterer Interferometric (PSI) points. Though the velocity of PSI points swayed positively (maximum velocity of 23.61 mm/y) and negatively (minimum velocity of − 21.83 mm/y), the majority values were negative. Interpolation of velocity values showed the predominance of the negative field for all the components of CIAL infrastructure. Ground deformation was modelled using Settle3, based on standard penetration test (SPT) values of five boreholes in the study area. Comparison between the PSInSAR and Settle3 modelling of deformation shows correlation amongst the mean values of both the approaches. PSInSAR monitoring and Settle3 modelling results relate to the varying thickness and properties of soils both in situ and the landfilled material. Findings also highlight the need for geological and geotechnical site characterization before the construction, and remote monitoring of critical long-term assets, especially strategic ones such as airport.

Surface movement radar (SMR) is emerging as critical air traffic control to prevent runway incursion. In order to reach, or exceed, the demanding requirements for the International Civil Aviation Organization, this paper aims to develop an SMR signal chain architecture which extracts information about radar objects of interest in airport surveillance video. This research results can be integrated into radar analyzer and compressor data processor to enable the system to quickly detect objects of moving or stationary. It can work normally in the case of pulses are lost in burst transmission or the resources. The state-of-the-art performance of this signal chain architecture is verified by simulations with X-band radar trials data are collected at Kunming Changshui International Airport of China, which ensure the reliability of research. The work presented here is practical and straightforward; it brings an evident engineering application prospect.

The present paper designed to understand the variations in the atmospheric pollutants viz. PM10, PM2.5, SO2, NO2, and CO during the COVID-19 pandemic over eight most polluted Indian cities (Mumbai, Delhi, Bangalore, Hyderabad, Lucknow, Chandigarh, Kolkata, and Ahmedabad). A significant reduction in the PM2.5 (63%), PM10 (56%), NO2 (50%), SO2 (9%), and CO (59%) were observed over Major Dhyan Chand Stadium. At Chhatrapati Shivaji International Airport, a decline of 44% in PM2.5 and 50% in PM10 was seen just a week during the initial phase of the lockdown. Gaseous pollutants (NO2, SO2 & CO) dropped up-to 36, 16, and 41%, respectively. The Air Quality Index (AQI) shows a dramatic change from 7% to 67% during observation at Chandigarh and Ballygunge during the inspection. Whereas, Ahmedabad, Worli, Income Tax Office, Talkatora, Lalbagh, and Ballygaunge have showed a significant change in AQI from 25.76% to 68.55%. However, Zoo Park, CST, Central School, and Victoria show relatively low variation in AQI in the range of 3.0% to 14.50% as compare to 2019 after lockdown. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analysis suggested that long range transportation of pollutants were also a part and parcel contributing to changes in AQI which were majorly coming from the regions of Iran, Afghanistan, Saudi Arabia, as well as a regional grant from Indian Gangatic plains and Delhi Non-capital region.

Gunay, Gurkan/0000-0003-0597-1511; GOKASAR, ILGIN/0000-0001-9896-9220 Mode choice of airport ground access has been covered by several studies, but there is a lack of research in the case of airport ground egress; that is, mode choices of inbound passengers for ground trips from the airport to the city center. This study aimed to cover this gap by modeling the ground egress mode choice of passengers, employing mixed logit and comparing it with the multinomial logit model. The data for this research was collected at Istanbul's Sabiha Gokcen International Airport (SAW) in 2015. Analyses included six modes, namely automobile, pick-up, public transit, taxi, shuttle and public transit (SP), and shuttle and taxi (ST). An important outcome was that a mixed logit model with error components outperformed the multinomial logit model. Results showed that significant variables affecting the ground egress mode choice included the income of the passenger, the cost of a ground trip from the airport, auto ownership status, number of luggage and trip purpose. Passengers are less constrained by ground travel time in their airport egress trips than in their airport access trips. By this, a significant finding was that prioritizing egress trip cost over travel time affected the mode choice.

In every Airport, management options are facing different issues that may cause problems for aviation operations. Hazard identification and risk modeling must be the priority of airport management. Our research focused on runway safety, so that is very important, and it has various risks. Factors affecting flight safety include runway incursion, runway excursion, loss of control on the ground, bird strike, etc. Collision with wildlife is one of the most critical factors affecting the environment. Our study goal was that bird strikes pose a significant threat to aviation safety worldwide. This issue has two perspectives; first, wildlife significantly affects safety by increasing collision risk with airplanes. Second, the aviation operation causes danger for animals' lives and, consequently, to the environment. To carry out the research method, we attempt to present a historical background and record of wildlife collision and their environmental risks and simultaneous a way to identify these hazards and control their impacts. An essential part of the research results was introducing two hazard identification forms and wildlife risk modeling at Sardar-e-Jangal international airport of the Rasht City of Iran. The risks summarized in this case, from March to September 2019. The results of daily observations showed that a variety of birds always used the runway. Based on observation, safety risk modeling has been done. Most birds that collide with aircraft were of the Pheasants type, as a relatively large bird species. Given all of these factors, the severity of this hazard is catastrophic. So the safety risk index is 5A and unacceptable. Therefore, it is necessary to make specific arrangements, especially, Abundant rivers, canals, and waterways in the Airport, creating diverse vegetation that attracts small insects and animals (rodents, amphibians, etc.) needed food, shelter in vegetation. In addition, making the right environment for childbirth, high rainfall in the Medium to a long-term action plan for each according to local circumstances.

Non-destructive testing techniques are highly valuable in the present day scenario as it can save money and time for the qualitative evaluation of any site. This paper presents a case study utilizing one such technique, employing a ground-coupled Ground-Penetrating Radar (GPR). The GPR was used to estimate the damages to the pavement and underlying subgrade soil at Cochin International Airport Limited (CIAL), Cochin, Kerala, India. The state of Kerala received 75% more than expected rainfall in the monsoon of 2018 and hence, faced one of the worst natural disasters in the form of floods between July and August. Therefore, a subsurface survey was performed at CIAL to analyse the pavement area and identify any detrimental effects caused by the floods. The subsurface survey scope was to image the subsurface to an approximate depth of 2–3 m to map the anomalies and quantitatively evaluate the affected areas of the runway, taxiways, and the link-ways. Non-destructive testing was opted not to affect the regular operations at the airport. This investigation involved the use of remote measurement methods, and therefore, all the findings presented here are the result of the measurement and interpretation of GPR data. The analysis was performed using a dedicated data analytics software called RADAN7. Based on the analysis, a quantitative criterion called the “stripping index” has been computed to define the degree of damages sustained by the pavement and its underlying layers. The results are both graphically and quantitatively discussed in this paper.

Airport plays an important role in the heart of the regions in which they are located, as well as in certain sectors of activity, such as tourism. Air transport makes a major contribution to sustainable development by supporting and promoting international tourism. The available rating systems need to better incorporate the broader socioeconomic settings associated with the built environment. This paper identified key indicators for assessing the sustainability performance of an airport construction projects. The research data used for analysis were collected from a questionnaire survey given to three groups of experts, including employer, consulting engineers, and contractors of Iranian airport construction projects. The importance of sustainability indicators was identified by using statistical analysis and software such as SPSS. The fuzzy set theory was used to establish key assessment indicators (KAIs). Cronbach’s alpha coefficient method was used in this study to evaluate the data reliability. A questionnaire survey among practitioners confirmed the necessity and identified priority indicators of sustainability. A procedure for using the KAIs is demonstrated by a case study. The research results demonstrated the importance of sustainability knowledge, indicators, as a positive step toward assessing sustainability in airport projects. The authors identified 25 key indicators of airport construction projects based on Iran conditions that are consistent with the principles of sustainable development. Findings showed that technical aspect with a weight factor of 32% is the highest aspect and then economic and environment aspects with 24% and, finally, social aspect with 20%.

According to Airport Council International, Juanda International Airport (JIA) is the second busiest airport in Indonesia. JIA has two terminals: The domestic terminal (T1) has an area of 62,700 m2, while the international terminal (T1) covers an area of 49,000 m2. Both T1 and T2 were designed to accommodate 12.5 million passengers per year; in 2015, the actual number of passengers passing through the terminals reached 17 million. Therefore, the purpose of this research was to find a solution to the terminals’ overcapacity (or congestion) problem by analyzing the factors affecting the efficiency of the existing terminals. This research uses analytic hierarchy process (AHP), a three-level process consisting of goals, criteria, and sub criteria. The main objective of this research is determining the factor that most affects the efficiency levels of T1 and T2. Three priority variables were identified - convenience, punctuality, and accessibility. The sub criteria include the processes that a passenger must go through when using the passenger terminal, including the security check point 1 (SCP I) and the security check point 2 (SCP II), check-in, walking time, and boarding lounge. The analysis results show that the factors that influence the efficiency of T1 were check-in process (32.7%), SCP I (32.4%), walking time and SCP II (13.2%), and boarding lounge (8.5%). The factors which influence the effectiveness of T2 were 28.1% for SCP I, 26.9% for check-in process, 17.9% for walking time I, 10.6% for SCP II, 9.9% for walking time II and 6.6% for boarding lounge. Thus, the factors affecting both terminals’ efficiency are the processes of SCP I and check-in process when passengers first access the terminal.

The increase in world population and the value of time in the current period are changing the importance of air transportation. Due to increase popularity, airport officials have increased the number of flights. Because of the fact that the airports capacity is constant, airport traffic has increased. Regarding this, airport managers are looking for a solution to reduce traffic at airports and optimize the performance of service cars at the airport. The most important innovation of this research is developing a model for dynamic location of Equipment Parking Area (EPA) with optimal allocation of airport services in two different service modes. The goal of model is reducing costs and traffic and optimizing available spaces. To find optimal solution, two objective functions have been developed in the form of median and cover problems, and EPA locations have been located in a way that minimize the objective functions. The purpose of these functions are minimizing traffic at the airport and minimizing delays in flights. Using the developed model, EPA locations can be located for different time period flights and can be used to optimize the operations of the service cars without delay. The proposed model has been implemented for the Imam Khomeini International Airport and the results indicate that the number of service cars for nine flights has been decreased about 30% without any delay, as well as the amount of traffic have been decreased about 1300 meters in the first case and in 500 m in the second one.

For daily airport operations, the insufficient number and the improper scheduling of ground support vehicles are the main causes of flight delays. In this paper, a novel network model is proposed to complement the optimal scheduling of ferry vehicles for the flight ground support service. In the process of model construction, we first innovatively construct a ferry vehicle capacity network by having the introduced virtual flights and the ferry vehicle depot as nodes, in which the directed edges indicate that the two nodes associated may be consecutively served by the same ferry vehicle. Based on the capacity network, a mixed integer programming model is constructed to minimize the number of ferry vehicles needed. In addition, this paper shows that the mixed integer programming is equivalent to a linear programming when the service start time of each flight is fixed, which makes the solving process more efficient, and the linear programming model can be applied to solve the minimum node-disjoint path cover of directed acyclic graphs. The efficiency and accuracy of the method are validated by the actual flight data obtained from Beijing Capital International Airport. This study will provide a methodological reference for the optimal scheduling of airport ferry vehicles.

The unified model (Version: UM10.4) wind gust prediction system using rose nesting suite at 300 m resolution over the Incheon international airport (IIA) is carried out, and the prediction results of multiple domain nesting with input initial and lateral boundary conditions from the Korea meteorological administration (KMA) operational global data assimilation and prediction system (GDAPS) are compared with the operational local data assimilation and prediction system and the observed automated weather stations (AWS) dataset. The 300 m nested prediction system over the IIA is built from the 17 km GDAPS output in KMA; it is downscaled with a multiple nesting domains to 300 m resolution from the GDAPS, here after called as IIA-300 m. The model results are validated against the AWS to see the accuracy of the IIA-300 m model’s skill in predicting the wind gust over the IIA. The nesting suite is run with the default ancillary files created by the central ancillary program 9.0 (CAP 9.0) as well as modified ancillary files created by modifying the land points over IIA region using an ancillary editor. The UM model wind prediction is done with both ancillary files to see the improvements achieved by adding additional land points over the IIA domain. Further the vegetation fraction from the international geosphere-biosphere program (IGBP) data classified as 9 tiles in the ancillary file is replaced by the environmental-geographic information system (E-GIS) data to see the effect on the UM model’s wind gust predictions. The prediction of two wind gust events on 30-August-2016 and 02-October-2016 reveals only modest improvements in the prediction with respect to AWS observations, even after the modification of ancillaries with land points over the IIA domain, and only minor improvements are noted for the vegetation fraction replacement from IGBP to E-GIS vegetation dataset over the Incheon International Airport and exhibited only a marginal wind speed decrease due to warming up of the land part, particularly on the peripheries of the IIA-domain.

The own-ethnicity effect (OEE) is a recognition deficit for faces of other ethnic groups compared to one’s own group. Thirty-two border patrol (i.e., police) officers at a major international airport expected to have high frequency contact with multiple other ethnic group faces were compared with 32 bank employees and 64 students. German participants viewed out-group faces of African Americans, Mexican Americans/Mexican Nationals, and Turkish faces and German (in-group) faces in a standard recognition and a delayed-matching task. Generally, performance was better as a function of self-reported daily job contact for both tasks. Patrol officers were better with Black faces, while students were better with German faces for the standard recognition task. Although an OEE was present for all groups, it was attenuated for border patrol officers. Job contact with multiple out-groups was associated with face processing. Errors in recognition and matching faces of other ethnic groups pose problems for security in an increasingly global society. Customs agencies and security organizations employing an ethnically diverse workforce along with perceptual training for recognizing and matching out-group members will be better prepared to meet the demands of international security.

Lanzhou Zhongchuan International Airport [International Civil Aviation Organization (ICAO) code ZLLL] is located in a wind shear prone area in China, where most low-level wind shear events occur in dry weather conditions. We analyzed temporal distribution and synoptic circulation background for 18 dry wind shear events reported by pilots at ZLLL by using the NCEP final (FNL) operational global analysis data, and then proposed a lidar-based regio-nal divergence algorithm (RDA) to determine wind shear intensity and location. Low-level wind shear at ZLLL usually occurs in the afternoon and evening in dry conditions. Most wind shear events occur in an unstable atmosphere over ZLLL, with changes in wind speed or direction generally found at 700 hPa and 10-m height. Based on synoptic circulations at 700 hPa, wind shear events could be classified as strong northerly, convergence, southerly, and weak wind types. The proposed RDA successfully identified low-level wind shear except one southerly case, achieving 94% alerting rate compared with 82% for the operational system at ZLLL and 88% for the ramp detection algorithm (widely used in some operational alert systems) based on the same dataset. The RDA-unidentified southerly case occurred in a near neutral atmosphere, and wind speed change could not be captured by the Doppler lidar.

Invasive security practices create resentment, especially when targeting minority groups. Many studies of homeland security as well as of general policing practices, emphasized the harm such security checks produce; however, they could not tell us what effect avoiding these practices had on perceptions of trust. Our study follows a security screening reform in Israel’s Ben-Gurion international airport, a reform that was done to eliminate a specific practice which we found, in a previous study, to cause significant emotional harm. Employing a quasi-experimental design, we tested the effect that avoiding that specific harmful component had on perception of trust among Israeli citizens of Arab ethnicity. We found that eliminating that harmful component of the security screening was highly effective in improving the feelings of Israeli citizens of Arab ethnicity. We found that limited trust and perceptions of unfair treatment are not inevitable feelings among minorities, even in stressful situations such as airport security screening, as they predominantly depend not on background characteristics, but rather on the characteristics of the direct treatment they receive.

One of the most acute environmental effects of urban sprawl in a changing climate is related to human thermal comfort (HTC) especially in developing countries. This necessitates applied urban design and civil engineering works that take HTC into account. Here, we employ the radiation and human-bioclimate model, RayMan to interrogate HTC and urban climate in Zambia’s biggest city—Lusaka. We chose RayMan because of its tried and proven robust ability to compute radiation flux densities and thermo-physiologically important indices using only a few input variables. To assess HTC, we used synoptic data at 3 hourly intervals as observed at Kenneth Kaunda International Airport (KKIA) from 2000 to 2018. We also retrieved high-resolution monthly data for the period 1901–2016 from the Climatic Research Unit and used it to better understand the long-term evolution of urban climate over Lusaka. We observed that during September–November (SON), the highest physiologically equivalent temperature (PET) values are similar to those of the December–February (DJF) season with moderate heat stress at midday. However, with PET values of about 11 °C at dawn, SON is slightly colder than DJF hence making DJF the most thermal stressful season to people in Lusaka. In the evening, the city is generally comfortable to slightly warm from October to March and experiences moderate cold stress to no thermal stress from April to August. The most obvious finding to emerge from these analyses is that the thermal comfort of Lusaka varies between moderate cold stress and slight heat stress. Together, these results provide important insights that can be used in applied urban design for the health of urban dwellers.

Unsuitable weather phenomena are considered one of the most influential factors on flight schedules in world airports. It is a well-known fact that it is a non-controllable force that significantly affects airport operations systems and safety performance. In this paper, the impact of dust storms on flight schedules was explored in Kuwait International Airport during 2016 and 2017. A comparison was made between 32 days free of dust and another 32 days exposed to dust cloud. It was concluded that the average arrival and departure times, on days where dust incidents occurred, were decreased by 42% and 17.2%, respectively, when compared to the reference days.

Aviation is a basic necessity of our world, but its contribution to air pollution is considered significant. In this paper, the contribution of air traffic to air pollution levels in the area of the three larger airports of Greece is examined through the use of EDMS (Emission and Dispersion Modeling System), a regulatory model proposed by the US EPA (United States Environmental Protection Agency). To ensure a better understanding of air traffic contribution to air quality levels, the hourly aircraft movements along with the corresponding meteorological data for a whole year, 2009, were taken into account. During this year, air traffic peaked both in Greece as a total and in each of the three airports of this work. Airport emissions calculated by EDMS are found to be in good agreement with emissions monitored at Athens International Airport as well as with emission results and published data for International Zurich Airport. Concentration results have shown that PM10 and SO2 concentrations are well below the limit values, whereas NO2 concentrations exceeding limit value are expected in small areas under specific circumstances, when heavy air traffic coincides with meteorological conditions favoring air pollutant accumulation. Finally, the comparison of computational results with monitoring air quality data shows a good agreement, if other sources of air pollution are excluded.

The motivation of this study originates from the need for the United States Transportation Command (USTRANSCOM) to estimate the annual flying hours budget for future fiscal years. USTRANSCOM is responsible for managing the global defense transportation network and creating movement plans in response to various world events. Recently, USTRANSCOM has overestimated annual flying hours by 25% and underestimated by 402%. This article presents analyses of historical flight data and a methodology to forecast annual flying hours. A main contribution of this article is the meticulous coupling of the forecasting methodology and intricacies of a complex and challenging real-world problem. The methodology may be extended to applications where historical data are used to predict future demand and requirements under uncertainty. An application using the programming language R and open source platform R Studio is developed to ingest data and produce forecasts using the methodology developed in this article. Due to data classification concerns, a representative data set of annual flights in and out of Los Angeles International Airport from 2006–2016 is used as a case study to validate the methodology for public release.

Wildlife hunting has been in practice since the colonial phase of India which caused a great loss to the nation’s biodiversity. In last few years, several incidences have been reported where live animals and their parts and products were confiscated from the international airports being shipped to meet the emerging demand of wildlife in grey market. Several wild animals have been in a constant demand following the belief that wildlife and its parts have the potential to cure several ailments. In this study, we investigated two detained parcels confiscated by the Customs Authority in the suspicion of illegal wildlife trade containing mysterious animal products of wild origin. The parcels were in transit and were being shipped via air-mail to the United States of America from the Netaji Subhas Chandra Bose International Airport, Kolkata, India. We sequenced the partial fragments of cytochrome b gene and surprisingly, the confiscated specimens showed a 99% homology with the known sequences of Oriental house rat (Rattus tanezumi). On phylogenetic analysis, the confiscated specimens clustered with the known sequences Rattus tanezumi with 100% bootstrap support. These specimens also showed least genetic divergence (DA 0.003–0.013) with Rattus tanezumi, thus identified specimens to be originated from Oriental house rat. This study has proven the imperativeness of the molecular diagnostics tools in ascertaining the species identity from morphologically disfigured and unrecognisable specimens.

Beirut Rafic Hariri International Airport (B-RHIA), the only international airport in Lebanon, is situated within the heart of a densely populated metropolitan area surrounded by hills towards both the east and south-east directions. Over the years, chaotic and unauthorized expansion of built-up structures surrounding the airport created a hazard to aviation safety. Aviation safety around an airport is maintained through well-defined virtual obstacle limitation surfaces (OLS) based on Annex 14 of International Civil Aviation Organization (ICAO). In this paper, a study of OLS for Beirut Rafic Hariri International Airport is presented. Geographical information systems (GIS) technologies were used to visualize and monitor the aerodrome with its surfaces in two and three dimensions and assess any deviations through them. Results showed a large number of obstacles infringing the OLS including the terrain surrounding the airport. Their locations and elevations were determined. Corresponding recommendations for mitigating the effects of those violations were presented.

Collisions between wildlife and aircraft are a serious and growing threat to aviation safety. Understanding the frequency of these collisions, the identity of species involved, and the potential damage that can be inflicted on to aircraft aid mitigation efforts by airfield managers. A record of all animal carcasses recovered from Dublin International Airport, Ireland’s largest civil aviation airport, has been maintained since 1990 where strikes with the endemic Irish hare (Lepus timidus hibernicus), a protected subspecies of mountain hare, are of particular concern despite substantial management efforts from the airfield authority. The first strike event with a hare was recorded in 1997, and strike events have substantially increased since then, with a sharp increase recorded in 2011. Over a 30-year period, a total of 320 strike events with the Irish hare have been recorded at the airfield. To date, no strike event with a hare has resulted in damage to an aircraft. However, carcasses can present as a major attraction to avian scavenger species in addition to posing as a risk of causing foreign object damage in the event of an undetected carcass. Hare strikes are discussed in the context of the rate of civil aircraft movements, possible direct and indirect damage to aircraft, and airfield wildlife hazard management. Here, we demonstrate that not only are strike events increasing by 14% on an annual basis, but that the kinetic energy of such an event has the potential to cause significant damage to an aircraft.

This article uses ARCGIS software to conduct circle and hot spot analysis of enterprises within 10 km radius of Zhengzhou International Airport to track the evolution of the area and its spatial structure. First, we observed the industrial distribution around Zhengzhou International Airport, defined the airport’s airport economic zone, and then analyzed the distribution of different airport-dependent industries in the inner, middle, and outer rings. As well as the distribution of industries of different industry classifications in the airport economic zone, combined with the characteristics of the airport economic zone, the dynamic mechanism of the airport economic zone is studied from both endogenous and external dynamics. The results show that, after decades of development, the airport has moved from a one-way expansion in the initial stage to a multi-directional expansion similar to urban areas. At the same time, the resident enterprises are from an increasing range of industries, pointing to a diversified development. Besides, the agglomeration pattern of enterprises is shifting from the airport center to the periphery as the dependence on the airport itself weakens. Industrial hot spots are gradually evolving from scattered points to axial lines. The layout of core industries around the airport and the transportation access has morphed into a “North-South development” pattern. The status of the airport hub, the functional zoning of the airport area, the control of the airport area, and the airport orientation of industry each affect the development and clustering patterns of the economic zone.

International audience; This study used AEDT 2.d to estimate the pollutant emissions at Montreal’s Pierre Elliott Trudeau International Airport (YUL) for 2015 while quantifying the impact of the airport’s taxi time and atmospheric conditions on aircraft emissions. Using the more airport-specific parameters available and ICAO standard values otherwise, the yearly emissions of NOx, HC, CO, PM10, SOx, and CO2 at YUL were, respectively, 7.64 102, 1.18 102, 1.33 103, 1.35 101, 6.77 101, and 2.31 105 tonnes/year. The results show that reducing aircraft taxi time by 31 % reduced aircraft emissions by 6 % (NOx) and 27 % (CO). Atmospheric conditions impact aircraft emissions of NOx, CO and HC with a seasonal effect. Summer conditions reduced NOx emissions by 5 % and increased CO emissions by 2 %, while winter conditions reduced HC and CO emissions by approximately 15 % and increased NOx emissions by 1 %. To further investigate the impact of atmospheric conditions, dispersion calculations of NOx and CO emissions were carried out using identical air-traffic and weather data from the warmest and coldest weeks in 2015. The results demonstrate that pollutant concentrations were higher during the winter and that pollutants were also dispersed further during the winter than the summer according to the dominant wind direction. A 1-h NOx and CO concentrations greater than 10 μg/m3 were found up to 24 km and 30 km, respectively, away during the winter compared to 14 km and 20 km during the summer. Yet, local air quality standards were satisfied as pollutant concentrations found outside the airport enclosure were below those standards.

Since the 9/11 terrorist attacks, research has enveloped numerous areas within the psychological sciences as a means to increase the ability to spot potential threats. While airports took to heightened security protocols, many academics looked deeper into ways of detecting deception within international airport settings. Various verbal and nonverbal systems were intensely scrutinised under the empirical magnifying glass with the aim of creating security environments that are better able to detect potential threats. However, in 2018, a €4.5 m grant from the European Union’s Horizon 2020 research and innovation programme, number 700,626, was awarded to further in vivo test the use of computational methods to detect deception from facial cues. The system is deemed a noninvasive psychological profiling system and stems from that of a system called ‘Silent Talker’ (Rothwell et al. in Appl Cognit Psychol 20(6):757–777, 2006). The ‘iBorderCtrl’ AI system uses a variety of ‘at home’ pre-registration systems and real time ‘at the airport’ automatic deception detection systems. Some of the critical methods used in automated deception detection are that of micro-expressions. In this opinion article, we argue that considering the state of the psychological sciences current understanding of micro-expressions and their associations with deception, such in vivo testing is naïve and misinformed. We consider the lack of empirical research that supports the use of micro-expressions in the detection of deception and question the current understanding of the validity of specific cues to deception. With such unclear definitive and reliable cues to deception, we question the validity of using artificial intelligence that includes cues to deception, which have no current empirical support.

In recent years, the pollution caused by aviation has sharply been increasing as a result of growing the air traffic. In this study, the emission of pollutants caused by aircrafts’ operations during landing and takeoff cycles was calculated and the impact of meteorological parameters on emission along with its distribution at Imam Khomeini International Airport and Mehrabad Airport was also estimated. Moreover, the pollutants such as carbon monoxide, nitrogen oxides, hydrocarbon and sulphur dioxide were examined. The pollutant emission rate of each aircraft was estimated using the engines’ pollutant database of International Civil Aviation Organization. In order to evaluate the aircraft emission, the flights data of both airports, dated from 2011 to 2016, were used and their total emissions were also calculated. Finally, the atmospheric dispersion model system was used for modelling the dispersion of emissions of these two airports. The results indicated that the highest rate of the total emission at Mehrabad Airport was considered as 2718.47 ton/year in 2016. As for the Imam Khomeini International Airport, the highest rate of total emission was considered to be 4259.12 ton/year in 2015. Moreover, the dispersion of the pollutants along with their distribution at two airports was also modelled and explained, respectively. The results indicated that Mehrabad Airport through which more flights are operated and handled compared to Imam Khomeini International Airport produced lower emission. Moreover, eastern side of these airports suffered from more pollution because of most common wind direction from west to east at these airports.

Airport bus is an important public transportation mode for large international airport. To improve the bus station coverage, passenger demand compatibility and the scheduling flexibility of Beijing International Airport bus line, a dynamic line generation and vehicle scheduling method is proposed in this paper. Firstly, based on multi-source big data from the airport (including data from taxi, ride-hailing service, subway, regular bus, airport bus, etc.), we accurately extract candidate stations, which are very popular with passengers and convenient for parking and transfer, through public transportation demand level calculation, iterative clustering and POI matching. Then, the candidate stations need to be partitioned appropriately by selecting suitable features and calculating the similarity of candidate stations, so as to make the stations within each group a moderate size and have a consistent spatial orientation. Finally, a line generation and vehicle scheduling algorithm, which is compatible with multi-vehicle, high success rate of ride-sharing matching and low cost, is designed to realize accurate and rapid operation scheduling within each group according to the situation of passengers booking tickets. We have carried out experiments in Wangjing and Yayuncun, and the results show that our method can satisfy passenger demand fast and accurately.

The focus of this study is Anthemountas basin in northern Greece, where land subsidence phenomena had been previously identified. The basin has a NNW-SSE orientation, which is optimal to the currently acting ~ N-S extension field in the back-arc Aegean area and is bordered to its north and south edge by two, well-pronounced faults. The region of study is located close to the greater metropolitan city of Thessaloniki and comprises a number of critical facilities including the city’s international airport. The research object is the monitoring of the evolution of the displacement at Anthemountas graben, using InSAR time-series and the investigation of the dominant driving mechanism. We show new surface displacement results from the ENVISAR satellite, and overall, an enhanced dataset of SAR time-series is presented, spanning the period 1992 to 2010, by using the satellites ERS1, ERS2 and ENVISAT. Results indicate a continuously deforming environment in both decades, with an increasing magnitude. The detailed study of the deformation pattern together with the analysis of in situ data defines aquifer overpumping as the main cause of the detected displacement of both decades. Critical regions are examined in detail, as for example: an area close to Thermi, the town of Perea and the Thessaloniki’s international airport, a major hub of the Balkans. The latter was subjected to an increasing deforming velocity during the monitoring period. Overall, we conclude that a water management plan should be of high priority for the area.

There are many Nepali men working in the Middle East and Malaysia and media reports and anecdotal evidence suggest a high risk of workplace-related accidents and injuries for male Nepali workers. Therefore, this study aims to explore the personal experiences of male Nepali migrants of unintentional injuries at their place of work. In-depth, face-to-face interviews (n = 20) were conducted with male Nepali migrant workers. Study participants were approached at Kathmandu International Airport, hotels and lodges around the airport. Interviews were transcribed and analysed using thematic analysis. Almost half of study participants experienced work-related accident abroad. The participants suggested that the reasons behind this are not only health and safety at work but also poor communication, taking risks by workers themselves, and perceived work pressure. Some participants experienced serious incidents causing life-long disability, extreme and harrowing accounts of injury but received no support from their employer or host countries. Nepali migrant workers would appear to be at a high risk of workplace unintentional injuries owing to a number of interrelated factors poor health and safety at work, pressure of work, risk taking practices, language barriers, and their general work environment. Both the Government of Nepal and host countries need to be better policing existing policies, introduce better legislation where necessary, ensure universal health (insurance) coverage for labour migrants, and improve preventive measures to minimize the number and severity of accidents and injuries among migrant workers.

This paper describes the extended first-come first-served scheduler that is being developed for integrated departure and arrival management at airports. The previously developed scheduler with route assignment capability has been enhanced to handle actual wake turbulence separation requirements at runways instead of simple departure and arrival rate constraints. The scheduler is tested with recorded surface traffic data gathered for three days in April 2015 at Incheon International Airport. Three prioritization strategies of nominal, arrival, and partial arrival priorities, are compared. Both the arrival and partial arrival priorities decrease overall delays with significant reduction in arrival delays. The adverse impacts on departure delay are minimal.

The increase in fog frequency over the past few decades is a major cause of concern for the aviation and transportation sectors. Accurate forecasting of the spatio-temporal extent of fog is crucial for minimizing socioeconomic losses. The present study attempts to characterize the fog frequency and associated meteorological factors over Kempegowda International Airport, Bengaluru (KIAB), in Karnataka, India. Maximum fog occurrence is observed during the month of December, followed by January. The time of onset of fog lies usually between 1800 and 0300 UTC. No fog is formed between 0400 and 1700 UTC indicating the role of radiation fog. The predominant wind direction during fog events is east or southeasterly. There is significant positive correlation between the fog frequency and both the northeast monsoon, October–November (0.72), as well as December–January–February (DJF) rainfall (0.80). Soil moisture conditions during the DJF period also play a key role in fog occurrence and its climatology, which is evident from the correlation coefficient of order 0.68. These suggest that further research is needed for understanding the extent of impact on aviation at KIAB.

This study employs the Unified Model (UM) with the rose nesting suite at 300-m resolution to construct a high spatial and temporal resolution wind simulation model for predicting wind gusts over the Incheon International Airport (IIA). The model can enable efficient aircraft operation and avert accidents due to sudden wind gusts. Simulation results with different inputs from the Korea Meteorological Administration (KMA) operational data assimilation and prediction systems are compared with an observed dataset. The 300-m nested prediction systems are built using the 17 km Global Prediction System (GDAPS) and 1.5 km Local Prediction System (LDAPS) of KMA. They are downscaled to 300 m resolution using five and three nesting domains from the GDAPS and LDAPS, respectively. The model results are validated against automated weather stations (AWS) to determine the accuracy of the UM for simulating high-resolution winds over the IIA. Both nesting suites are identical, with the only difference being their initial (IC) and lateral boundary conditions (LBC). The major difference between LDAPS and GDAPS downscaled model results is that the GDAPS downscaled system has a lower wind direction RMSE and the LDAPS downscaled system has a lower wind speed RMSE for up to 48 hours of verification against observations; thus, it is better than the GDAPS downscaled system. Two case studies were performed; one for wind gust conditions and one for vertical wind shear over the IIA. The 300 m model performs better in both cases, making it useful for wind gust and wind shear predictions over the airport.

Airport operations are sensitive to visibility conditions. Low-visibility events may lead to capacity reduction, delays and economic losses. Different levels of low-visibility procedures (lvp) are enacted to ensure aviation safety. A nowcast of the probabilities for each of the lvp categories helps decision makers to optimally schedule their operations. An ordered logistic regression (OLR) model is used to forecast these probabilities directly. It is applied to cold season forecasts at Vienna International Airport for lead times of 30-min out to 2 h. Model inputs are standard meteorological measurements. The skill of the forecasts is accessed by the ranked probability score. OLR outperforms persistence, which is a strong contender at the shortest lead times. The ranked probability score of the OLR is even better than the one of nowcasts from human forecasters. The OLR-based nowcasting system is computationally fast and can be updated instantaneously when new data become available.

Most aviation communities have increasing concerns about the environmental impacts, which are directly linked to health issues for local residents near the airport. In this study, the environmental impact of different departure procedures using the Aviation Environmental Design Tool (AEDT) was analyzed. First, actual operational data were compiled at Gimpo International Airport (March 20, 2017) from an open source. Two modifications were made in the AEDT to model the operational circumstances better and the preliminary AEDT simulations were performed according to the acquired operational procedures. Simulated noise results showed good agreements with noise measurement data at specific locations. Second, a multi-objective optimization of departure procedures was performed for the Boeing 737–800. Four design variables were selected and AEDT was linked to a variety of advanced design methods. The results showed that takeoff thrust had the greatest influence and it was found that fuel burn and noise had an inverse relationship. Two points representing each fuel burn and noise optimum on the Pareto front were parsed and run in AEDT to compare with the baseline. The results showed that the noise optimum case reduced Sound Exposure Level 80-dB noise exposure area by approximately 5% while the fuel burn optimum case reduced total fuel burn by 1% relative to the baseline for aircraft-level analysis.

The ground support equipment such as the baggage towing tractors are widely used in the airport apron of Suvarnabhumi International Airport, Thailand. The tractor weight was heavy; therefore, the solid tire had been used instead of the pneumatic tire. The pneumatic tire life was short while the solid tires were hard for riding which were the huge problems of tractor tire usage. This research aimed to analyze effects of the rolling tires. The drum testing method had been performed to measure the rolling effect of tires. The vibration of rolling tires was analyzed to evaluate effects on the baggage towing tractor. The advantage of this study will be useful to develop the towing tractor tires in the future work.

This paper presents and discusses the fog occurrences before and after the construction of the Guarulhos International Airport, using data from 1951 to 2015. The analysis showed the following: (1) a total of 19,816 h of fog were registered. (2) The minimum average, mean and maximum average of the fog temperature had significantly increased after the airport was constructed from 1.2 to 6.9, 12.1 to 14.5 and 20.2 to 20.7 °C, respectively, due to the urban development around the airport during the study period. (3) The average fog hours per year decreased by approximately 73.1%, i.e., from 492 ± 84.45 to 132 ± 54.51 h per year. (4) Most of the fog events occurred due to longwave cooling on clear nights with relatively low wind speeds (characterizing radiation fog), with over 65% having duration of 2 h and occurring in the early hours of the day during March–September period. (5) The maximum probability of fog occurrence dropped about 10% from before to after the construction of the airport. Finally, two fog events are investigated using data collected during the fog evolution using atmospheric sounding profiles (from an acoustic sounder) and automatic meteorological stations and preliminary results showed that the values of cooling rate and turbulent kinetic energy play key roles in the onset and growth-dissipation phases of the fog, respectively.

Airplane deicing is a safety measure to eliminate/prevent icing on airplanes that can lead to airflow disruption and emergency conditions. Aircraft deicing/anti-icing fluids (ADF) are high in glycol content. At Dallas Fort Worth International Airport (DFW), the major aircraft deicing activities are conducted at designated deicing pads called Source Isolation Deicing Sites, where ADF run-off can be captured and conveyed into the airport’s glycol collection system. A portion of ADF drips from the aircraft during taxiing and shears off the aircraft during take-off, entering nearby waterways without treatment. Glycol acts as a nutrient for bacteria in the airport’s receiving waterways, resulting in an increase in bacterial growth and a subsequent reduction in dissolved oxygen (DO), potentially endangering aquatic life. This paper proposes a prototype data-driven deicing activities management framework for DFW to address the complexity of airport deicing operations and its impacts. The proposed framework uses stochastic dynamic programming (SDP) to assign airplanes in each hour to deicing pad locations, so as to maximize DO in the receiving waters, subject to airport constraints. Some data were artificially generated using the available knowledge of airport operations. The state transition equations in SDP were estimated. The proposed framework was demonstrated using three cases during major deicing events. Improvements in DO compared with actual DO recorded in the data were mixed; however, the results motivated DFW to implement a new data collection process to replace the artificially-generated data, so that a more accurate optimization could be conducted in the future.

We assume that during flights the amount of waste that is produced is limited. However, daily, approximately 8000 commercial airplanes fly above Europe's airspace while at the same time, more than 17,000 commercial flights exist in the entire world. Using primary data from airlines, which use the Larnaca's International Airport (LIA) in Cyprus, we have tried to understand why wastes are produced during a typical flight such as food waste, paper, and plastics, as well as how passengers affect the production of those wastes. The compositional analysis took place on 27 flights of 4 different airlines which used LIA as final destination. The evaluation indicated that the passenger's habits and ethics, and the policy of each airline produced different kinds of waste during the flights and especially food waste (FW). Furthermore, it was observed that the only waste management strategy that exists in place in the airport is the collection and the transportation of all those wastes from aircrafts and from the airport in the central unit for further treatment. Hence, this research indicated extremely difficulties to implement any specific waste minimization, or prevention practice or other sorting methods during the flights due to the limited time of the most flights (less than 3 h), the limited available space within the aircrafts, and the strictly safety roles that exist during the flights.

Emissions from civil airports are similar to those observed in industrial and urban areas. While air pollution and noise levels are regularly monitored and assessed, information on the status of heavy metals in soils close to airport facilities is limited. In this study, we monitored and assessed heavy metal distribution in soils close to Athens International Airport (AIA) in Attica, Greece. Following a grid sampling scenario, topsoil samples were collected from 86 sites at the periphery of AIA and total and available forms of Cu, Zn, Fe, Mn, Ni, Cr, Pb, and Ba concentrations were determined in aqua regia and DTPA soil extracts, respectively. Median concentration values for both metal forms are not considered as particularly high. However, 90th percentile concentration values for some metals are high, indicating soil enrichment. Evaluation of enrichment factor (EF) and availability ratio (AR) values and EFs spatial distribution have led to consistent conclusions of secondary and ongoing metal accumulation in the soils of the studied area. Tessier sequential extraction procedure was applied to 10% of the soil samples and the results showed high potential availability of Pb, Mn, Cu, and Ni, further supporting the continuous metal accumulation in the studied soils.

Ataturk International Airport (AIA) hosts the most crowded air traffic in Turkey. It is located to the south of the city in an urban area. A new airport is under construction in the north of Istanbul, which is a rural site. All commercial operations of AIA are going to be moved to the new airport after the completion of the construction. Aircraft emissions have adverse impact on ambient air quality, especially at urban sites. In this study, aircraft emissions from LTO cycles were estimated in AIA. NOx, CO, and HC emissions were 4249, 2153, and 181 t year−1, respectively. Taxi phase was responsible for the vast majority of CO and HC emissions. The majority of NOx emissions occurred from climb phase. Valuation of the emissions was estimated according to their unit damage price. The total damage value was 9,420,848 € year−1. NOx contributed more than 99% of the total amount. Dispersion of the pollutants was modeled with EPA’s AERMOD. The calculated NOx and CO concentrations at the closest air quality monitoring station to the airport were compared with the observed results. The contribution of aircraft emissions to NOx and CO concentrations at the station was 5.1 and 2.4%, respectively. The annual limit value of NOx was exceeded in most of the airport area and the residential area to the west of the airport. The highest concentration was 566 μg m−3, which was estimated at the parking/gate area. The maximum daily 8-h mean concentration of CO exceeded the limit value only at the gates and parking area.

This article provides an overview of economic analysis in three prominent merger investigations and litigations: Electrolux’s proposed acquisition of General Electric’s appliance division, Halliburton’s bid for Baker Hughes, and United Airline’s attempt to acquire additional airport slots at Newark Liberty International Airport. In each, the parties abandoned their proposed transaction after the Division had filed suit to block the acquisition. While we cannot recount all the analyses underpinning these outcomes, we hope to provide some insights into the challenges of enforcing antitrust law and the way in which economic analysis in particular is used to address those challenges.

Eel farming in Asia relies on wild-caught juvenile “glass eels” of the genus Anguilla. When supplies of Japanese eels (Anguilla japonica) declined in the 1990s, Asian eel farming shifted to using European eels (Anguilla anguilla). The European eel is currently classified as “Critically Endangered”, and export out of Europe has been suspended since March 2009. In early 2016, glass eels were seized at the Hong Kong International Airport and genetically identified using the COI barcode region. Samples matched A. anguilla with a similarity range of 99.39–99.85 %. To our knowledge, this is the first documented case of illegal trade of A. anguilla from Europe into Hong Kong using genetic evidence. Furthermore, multiple isolated incidents of eel seizures by customs indicate that Hong Kong is a major hub facilitating illegal trade in eels from Europe to Asia. We demonstrated that COI barcoding is a suitable tool in identifying illegally imported A. anguilla, which can support enforcement and prosecution as well as enable international cooperation between Europe and Asia.

Potential health effects from hexavalent chromium in groundwater have recently become a concern to regulators at the Tucson International Airport Area Superfund site. In 2016, the U.S. Geological Survey sampled 46 wells in the area to characterize the nature and extent of chromium in groundwater, to understand what proportion of total chromium is in the hexavalent state, and to determine if substantial differences are present between filtered and unfiltered chromium concentrations. Results indicate detectable chromium concentrations in all wells, over 75 % of total chromium is in the hexavalent state in a majority of wells, and filtered and unfiltered results differ substantially in only a few high-turbidity total chromium samples.

Determination of xenobiotics in samples of airport runoff water is both a complex and indispensable task due to an increasing threat resulting from the activities of numerous airports. The aim of this study was to develop, optimize, and validate a procedure based on liquid–liquid extraction (LLE) coupled with gas chromatography–mass spectrometry (GC–MS) for the determination of polycyclic aromatic hydrocarbons (PAHs). So far, no procedure was available that would ensure reliable data about concentration levels of these toxic pollutants in a new type of environmental samples, such as airport stormwater. The most difficult step in the analytical procedure used for the determination of fuel combustion products in airport stormwater samples is sample preparation. In this work, eight different protocols of sample preparation were tested. The evaluation of the LLE demonstrated that the best extraction conditions were as follows: dichloromethane (extraction solvent), solvent volume of 15 mL and sample volume of 250 mL. The percent recovery values ranged from 66 to 106 %, which shows that the LLE technique is a powerful method for extracting PAHs from airport runoff water samples with a complex matrix composition. Moreover, the developed procedure was characterized by satisfactory selectivity and a relatively low LOQ (0.17–0.52 μg/L). The procedure has been successfully applied to the analysis of stormwater samples collected from different sites at international airport in Poland. The procedure can thus be used as a tool for tracking the environmental fate of these compounds and for assessing the environmental effect of airports.

Border-based regulatory inspectorates, such as quarantine and customs organizations, intervene at national and state borders to ensure compliance of activities to relevant policies. Performance indicators can be used to help assess and compare the activities for the risk of non-compliance, and also to assess the inspectorate’s ability to detect and rectify non-compliance. We document a suite of three performance indicators that target inspectorate intervention at and before the border, and provide protocols for collecting the necessary data to compute point estimates of the indicators. For obtaining interval estimates, we then discuss mathematical models that account for the sources of uncertainty that are present during data collection. We cover three distinct setups, namely, the importation of certain classes of air cargo in Australia, both historically and under current policies, and passengers arriving at an international airport. The methodology developed here using the terminology of quarantine inspections can be applied in more general settings. Under the model which best describes the way data are collected, we provide confidence bounds for the performance indicators, with coverage close to the nominal level. The methodology is then illustrated on real and fabricated data.

This paper reports the use of data envelopment analysis (DEA) and a distance friction minimization (DFM) approach with fixed factors presented by Suzuki and Nijkamp (A stepwise efficiency improvement DEA model for airport operations with fixed production factors. Paper presented at the ERSA Congress. http://ideas.repec.org/p/wiw/wiwrsa/ersa11p1065.html #biblio. Accessed 18 April 2013, 2011) to assess the levels of match between expected demand for the next 25 years and infrastructure expansion investments announced by Infraero (the Brazilian Airport Authority) for the Rio de Janeiro International Airport (also known as “Galeao”). The main advantage of using the DFM approach with fixed factors lies in the fact that, to achieve maximum performance for inefficient units (away from the efficiency frontier), there is no need to linearly improve all input variables, as for most real situations, this assumption could be very difficult for management to implement and control. Additionally, this method enables the development of models with production factors that for some reason cannot be changed or adjusted by management. Based on the data regarding the planned infrastructure expansion explicit in the concession agreement for the Rio de Janeiro International Airport (established when the airport was recently privatized), the results of this study confirm those of some previous studies that had already suggested (but did not objectively measure the shortfall considering efficiency issues) a possible capacity shortfall in the medium and long run for the Rio de Janeiro International Airport.

This paper reviews existing approaches to the airport gate assignment problem (AGAP) and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods (to get robust optimization) while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. Genetic algorithm is adopted to solve the problem. An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm performance is further demonstrated using data of a terminal from Beijing Capital International Airport (PEK).

Comprehensive 25-year analysis of dense fog at Urumqi Diwopu International Airport (a major airport in western China) is performed using hourly weather data from January 1985 through December 2009 in an effort to better understand the climatological aspects of the phenomenon. The results show that dense fog is typically a cold-season phenomenon with more than 99 % of dense fog days occur from November through March. Within a day, dense fog peaks during the early morning hours and reaches a minimum in the late afternoon to early night. Most of dense fog events (68.2 %) lasted less than 3 h. Temperatures cooling to the range of −10 to −5 °C, and wind speeds of under 2 m s−1 are optimum for dense fog occurrences. Dense fog occurrences as brief as a couple of hours can disrupt air traffic locally even nationwide and affect flight on-time performance significantly, causing huge losses to both commercial airlines and passengers. There is a critical need for improving air traffic flow management. More importantly, aviation forecasters of airport should provide more timely and accurate information relating to dense fog to accommodate demands of different specific end users. However, the current situation is far from satisfactory. From a practical standpoint, some implications for dense fog forecasting are presented with the hope of improving the forecast of this phenomenon at the site.

Mid-wintertime spatial and temporal distributions of mountain wave excitation over the Kathmandu valley has been numerically simulated using Weather Research and Forecasting (WRF) modeling system. The study shows that low-level trapped mountain waves may remain very active during the night and early morning in the sky over the southern rim of the surrounding mountains, particularly, over the lee of Mt. Fulchoki. Calculations suggest that mountain wave activities are at minimum level during afternoon. The low-level trapped mountain waves in the sky over southern gateway of Tribhuvan International Airport (TIA) may pose risk for landings and takeoffs of light aircrafts. Detailed numerical and observational studies would be very important to reduce risk of air accidents and discomfort in and around the Kathmandu valley.

Background Over 24 million international visitors came to Japan in 2016 and the number is expected to increase. Visitors could be at a risk of illness or injury that may result in hospitalization in Japan. We assessed the effects of a four-minute digital animation titled Mari Info Japan on the level of anxiety experienced by international visitors to Japan. Methods We conducted a non-randomized, controlled study at Narita International Airport outside Tokyo in December 2014. On the first day, we recruited international visitors for the intervention group at predetermined departure gates and, the following day, we sampled visitors for the control group at the same gates. We repeated this procedure twice over 4 days. The intervention group watched the digital animation and the control group read a standard travel guidebook in English. After receiving either intervention, they completed a questionnaire on their level of anxiety. The outcome was assessed using the Mari Meter-X, The State-Trait Anxiety Inventory Form Y (STAI-Y), and a face scale, before and immediately after the intervention. We analyzed data with Wilcoxon rank sum tests. Results We recruited 265 international visitors (134 in the intervention group, 131 in the control group), 241 (91%) of whom completed the questionnaire. Most of them had no previous Japanese health information before arrival in Japan. The level of anxiety about health services in Japan was significantly reduced in the intervention group (Mari Meter-X median: − 5 and 0, p