Subject(s)
Airports , Lead , Humans , Lead/blood , North Carolina , Child, Preschool , Infant , Male , Environmental Exposure/statistics & numerical data , Female , Air Pollutants/analysis , Residence CharacteristicsABSTRACT
The intensification of agricultural practices and urbanisation are widespread causes of biodiversity loss. However, the role of artificial habitats in genetic rescue is an aspect that is not well understood. Implementing genetic rescue measures to improve gene flow and maintain a viable population of keystone species is a crucial prerequisite for promoting diverse and resilient ecosystems. Landscape fragmentation and modern agricultural methods have caused the decline and the isolation of the remnant colonies of the endangered European ground squirrel (Spermophilus citellus) throughout its range. However, the artificial habitat, such as airport fields with regular grass mowing, provides suitable conditions for this grassland specialist. We measured home range size and genetic variation of seven souslik colonies in western Slovakia. Based on the 6904 ddRAD SNPs, we found significantly higher individual heterozygosity in colonies on airports compared to colonies on pastures. This indicates a potential for higher fitness of individuals from airport colonies, which can serve as a source for evidence-based translocations. Such an intervention can preserve the genetic diversity of small and isolated populations in the region. We emphasize that conservation management strategies would be strengthened including a specific focus on human-made grassland habitats.
Subject(s)
Agriculture , Airports , Genetic Variation , Animals , Agriculture/methods , Ecosystem , Sciuridae/genetics , Slovakia , Conservation of Natural Resources/methods , Endangered Species , Polymorphism, Single Nucleotide , Gene Flow , BiodiversityABSTRACT
Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level.
Subject(s)
Aircraft , Airports , Bayes Theorem , Time Factors , Models, Theoretical , China , HumansABSTRACT
The concept of an innovative human-machine interface and interaction modes based on virtual and augmented reality technologies for airport control towers has been developed with the aim of increasing the human performances and situational awareness of air traffic control operators. By presenting digital information through see-through head-mounted displays superimposed over the out-of-the-tower view, the proposed interface should stimulate controllers to operate in a head-up position and, therefore, reduce the number of switches between a head-up and a head-down position even in low visibility conditions. This paper introduces the developed interface and describes the exercises conducted to validate the technical solutions developed, focusing on the simulation platform and exploited technologies, to demonstrate how virtual and augmented reality, along with additional features such as adaptive human-machine interface, multimodal interaction and attention guidance, enable a more natural and effective interaction in the control tower. The results of the human-in-the-loop real-time validation exercises show that the prototype concept is feasible from both an operational and technical perspective, the solution proves to support the air traffic controllers in working in a head-up position more than head-down even with low-visibility operational scenarios, and to lower the time to react in critical or alerting situations with a positive impact on the human performances of the user. While showcasing promising results, this study also identifies certain limitations and opportunities for refinement, aimed at further optimising the efficacy and usability of the proposed interface.
Subject(s)
Airports , Augmented Reality , Man-Machine Systems , User-Computer Interface , Humans , Virtual Reality , AviationABSTRACT
The aviation sector is believed to be responsible for considerable environmental damage attributed to emission of a large number and amount of pollutants. Airports are often surrounded by forest fragments and humid areas that attract birds of prey and hence may potentially serve as useful bioindicators. The aim of the present study was to examine genotoxic potential in raptors exposed to airport pollution using the micronucleus (MN) test and morphological changes as evidenced by bilateral symmetry. This investigation was conducted at Salgado Filho International Airport of Porto Alegre - RS as well as in private and zoological breeding grounds. The presence of metals was measured in the blood cells of the collected birds. Seventeen birds (Caracara (Polyborus) plancus) were used in this study 11 from exposed and 6 from non-exposed group. The nuclear alterations clearly indicate that organisms exposed to airport pollution exhibited a significantly higher frequency of genetic damage compared to non-exposed birds. Further, manganese and chromium were detected exclusively in the blood of the exposed group. In contrast, the analysis of bilateral symmetry did not detect any significant morphologic differences between the two groups. Therefore, data indicate that blood genotoxic stress occurs in birds of prey living in civil aviation areas as evidenced by MN frequency increase and presence of manganese and chromium.
Subject(s)
Airports , Micronucleus Tests , Animals , Brazil , Environmental Monitoring , Micronuclei, Chromosome-Defective/chemically induced , DNA Damage , Cell Nucleus/drug effects , Raptors , MaleABSTRACT
Mpox is an emerging, infectious disease that has caused outbreaks in at least 91 countries from May to August 2022. We assessed the link between international air travel patterns and Mpox transmission risk, and the relationship between the translocation of Mpox and human mobility dynamics after travel restrictions due to the COVID-19 pandemic had been lifted. Our three novel observations were that: i) more people traveled internationally after the removal of travel restrictions in the summer of 2022 compared to pre-pandemic levels; ii) countries with a high concentration of global air travel have the most recorded Mpox cases; and iii) Mpox transmission includes a number of previously nonendemic regions. These results suggest that international airports should be a primary location for monitoring the risk of emerging communicable diseases. Findings highlight the need for global collaboration concerning proactive measures emphasizing realtime surveillance.
Subject(s)
Air Travel , COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/transmission , Mpox (monkeypox)/epidemiology , Mpox (monkeypox)/transmission , Global Health , Pandemics , Airports , Communicable Diseases, Emerging/epidemiology , Travel , Disease OutbreaksABSTRACT
INTRODUCTION: Travel by airline starts and ends at airports. Thousands of people consisting of passengers, relatives of passengers, and employees gather at airports every day. In this study, medical events (MEs) encountered at Istanbul Atatürk Airport (IAA) and health services provided were analyzed.METHODS: The MEs encountered in IAA between January 1, 2016, and December 31, 2018, and health services provided by the private medical clinic in the airport terminal building were retrospectively analyzed.RESULTS: During the study period, 192,500,930 passengers traveled from the IAA and a total of 11,799 patients were seen at the clinic. There were 4898 (41.5%) male patients. The median age of the 9466 (80.2%) patients whose age was recorded was 34 (28-51) yr. Of 11,799 patients included in the present study, 9228 (78.21%) patients had medical complaints, 1122 (9.5%) patients had trauma complaints, 1180 patients (10%) were transferred to the hospital, and 269 (2.27%) patients required a certificate of preflight fitness. The most common medical complaint was gastrointestinal (1515 patients, 12.84%). The most common trauma was soft tissue injury (345 patients, 2.92%).DISCUSSION: MEs in airports can be as various and also critical as health conditions seen in emergency departments. It is important to provide medical services with an experienced medical team trained in aviation medicine and adequate medical equipment at airports.Ceyhan MA, Demir GG, Cömertpay E, Yildirimer Y, Kurt NG. Medical events encountered at a major international airport and health services provided. Aerosp Med Hum Perform. 2024; 95(5):259-264.
Subject(s)
Airports , Humans , Male , Adult , Middle Aged , Female , Retrospective Studies , Turkey , Travel/statistics & numerical data , Young Adult , Adolescent , Child , Wounds and Injuries/therapy , Wounds and Injuries/epidemiologyABSTRACT
BACKGROUND: While airport screening measures for COVID-19 infected passengers at international airports worldwide have been greatly relaxed, observational studies evaluating fever screening alone at airports remain scarce. The purpose of this study is to retrospectively assess the effectiveness of fever screening at airports in preventing the influx of COVID-19 infected persons. METHODS: We conducted a retrospective epidemiological analysis of fever screening implemented at 9 airports in Okinawa Prefecture from May 2020 to March 2022. The number of passengers covered during the same period was 9,003,616 arriving at 9 airports in Okinawa Prefecture and 5,712,983 departing passengers at Naha Airport. The capture rate was defined as the proportion of reported COVID-19 cases who would have passed through airport screening to the number of suspected cases through fever screening at the airport, and this calculation used passengers arriving at Naha Airport and surveillance data collected by Okinawa Prefecture between May 2020 and March 2021. RESULTS: From May 2020 to March 2021, 4.09 million people were reported to pass through airports in Okinawa. During the same period, at least 122 people with COVID-19 infection arrived at the airports in Okinawa, but only a 10 suspected cases were detected; therefore, the capture rate is estimated to be up to 8.2% (95% CI: 4.00-14.56%). Our result of a fever screening rate is 0.0002% (95%CI: 0.0003-0.0006%) (10 suspected cases /2,971,198 arriving passengers). The refusal rate of passengers detected by thermography who did not respond to temperature measurements was 0.70% (95% CI: 0.19-1.78%) (4 passengers/572 passengers). CONCLUSIONS: This study revealed that airport screening based on thermography alone missed over 90% of COVID-19 infected cases, indicating that thermography screening may be ineffective as a border control measure. The fact that only 10 febrile cases were detected after screening approximately 3 million passengers suggests the need to introduce measures targeting asymptomatic infections, especially with long incubation periods. Therefore, other countermeasures, e.g. preboarding RT-PCR testing, are highly recommended during an epidemic satisfying World Health Organization (WHO) Public Health Emergency of International Concern (PHEIC) criteria with pathogen characteristics similar or exceeding SARS-CoV-2, especially when traveling to rural cities with limited medical resources.
Subject(s)
Airports , COVID-19 , Fever , Mass Screening , SARS-CoV-2 , Humans , COVID-19/diagnosis , COVID-19/epidemiology , Japan/epidemiology , Fever/diagnosis , Fever/epidemiology , Fever/virology , Retrospective Studies , Mass Screening/methods , SARS-CoV-2/isolation & purification , Travel , Male , Adult , FemaleABSTRACT
With the recent advancement in artificial intelligence, there are new opportunities to adopt smart technologies for the sorting of materials at the beginning of the recycling value chain. An automatic bin capable of sorting the waste among paper, plastic, glass & aluminium, and residual waste was installed in public areas of Milan Malpensa airport, a context where the separate collection is challenging. First, the airport waste composition was assessed, together with the efficiency of the manual sorting performed by passengers among the conventional bins: paper, plastic, glass & aluminium, and residual waste. Then, the environmental (via the life cycle assessment - LCA) and the economic performances of the current system were compared to those of a system in which the sorting is performed by the automatic bin. Three scenarios were evaluated: i) all waste from public areas, despite being separately collected, is sent to incineration with energy recovery, due to the inadequate separation quality (S0); ii) recyclable fractions are sent to recycling according to the actual level of impurities in the bags (S0R); iii) fractions are sorted by the automatic bin and sent to recycling (S1). According to the results, the current separate collection shows a 62 % classification accuracy. Focusing on LCA, S0 causes an additional burden of 12.4 mPt (milli points) per tonne of waste. By contrast, S0R shows a benefit (-26.4 mPt/t) and S1 allows for a further 33 % increase of benefits. Moreover, the cost analysis indicates potential savings of 24.3 /t in S1, when compared to S0.
Subject(s)
Airports , Recycling , Refuse Disposal , Solid Waste , Recycling/methods , Recycling/economics , Solid Waste/analysis , Refuse Disposal/methods , Refuse Disposal/economics , Italy , Costs and Cost Analysis , Waste Management/methods , Waste Management/economics , Automation , Incineration/methods , Incineration/economicsABSTRACT
Wastewater-based epidemiological surveillance at municipal wastewater treatment plants has proven to play an important role in COVID-19 surveillance. Considering international passenger hubs contribute extensively to global transmission of viruses, wastewater surveillance at this type of location may be of added value as well. The aim of this study is to explore the potential of long-term wastewater surveillance at a large passenger hub as an additional tool for public health surveillance during different stages of a pandemic. Here, we present an analysis of SARS-CoV-2 viral loads in airport wastewater by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) from the beginning of the COVID-19 pandemic in Feb 2020, and an analysis of SARS-CoV-2 variants by whole-genome next-generation sequencing from Sep 2020, both until Sep 2022, in the Netherlands. Results are contextualized using (inter)national measures and data sources such as passenger numbers, clinical surveillance data and national wastewater surveillance data. Our findings show that wastewater surveillance was possible throughout the study period, irrespective of measures, as viral loads were detected and quantified in 98.6 % (273/277) of samples. Emergence of SARS-CoV-2 variants, identified in 91.0 % (161/177) of sequenced samples, coincided with increases in viral loads. Furthermore, trends in viral load and variant detection in airport wastewater closely followed, and in some cases preceded, trends in national daily average viral load in wastewater and variants detected in clinical surveillance. Wastewater-based epidemiology at a large international airport is a valuable addition to classical COVID-19 surveillance and the developed expertise can be applied in pandemic preparedness plans for other (emerging) pathogens in the future.
Subject(s)
Airports , COVID-19 , SARS-CoV-2 , Viral Load , Wastewater , COVID-19/epidemiology , Wastewater/virology , Netherlands/epidemiology , Humans , Wastewater-Based Epidemiological Monitoring , Environmental Monitoring/methodsABSTRACT
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.
Subject(s)
Aircraft , Airports , COVID-19 , SARS-CoV-2 , Wastewater , Humans , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Wastewater/virology , COVID-19/diagnosis , COVID-19/epidemiology , Singapore/epidemiology , Viral LoadABSTRACT
OBJECTIVE: Aircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses' Health Study (NHS and NHSII) cohorts. METHODS: Aircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995-2010. Biennial surveys (1994-2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45-54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status. RESULTS: At baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45-54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: -1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0-29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers. DISCUSSION: In two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway.
Subject(s)
Aircraft , Airports , Body Mass Index , Environmental Exposure , Humans , Female , United States , Prospective Studies , Middle Aged , Adult , Environmental Exposure/statistics & numerical data , Noise, Transportation/adverse effects , Noise, Transportation/statistics & numerical data , Obesity/epidemiology , Nurses/statistics & numerical dataABSTRACT
Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development.
Subject(s)
Airports , China , Sustainable Development , Models, Theoretical , Algorithms , AviationABSTRACT
The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020-2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020-2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development.
Subject(s)
Aviation , COVID-19 , Humans , Airports , COVID-19/epidemiology , Public Health , TravelABSTRACT
Traffic-related activities are widely acknowledged as a primary source of urban ambient ultrafine particles (UFPs). However, a notable gap exists in quantifying the contributions of road and air traffic to size-resolved and total UFPs in urban areas. This study aims to delineate and quantify the traffic's contributions to size-resolved and total UFPs in two urban communities. To achieve this, stationary sampling was conducted at near-road and near-airport communities in Seattle, Washington State, to monitor UFP number concentrations during 2018-2020. Comprehensive correlation analyses among all variables were performed. Furthermore, a fully adjusted generalized additive model, incorporating meteorological factors, was developed to quantify the contributions of road and air traffic to size-resolved and total UFPs. The study found that vehicle emissions accounted for 29% of total UFPs at the near-road site and 13% at the near-airport site. Aircraft emissions contributed 14% of total UFPs at the near-airport site. Notably, aircraft predominantly emitted UFP sizes below 20 nm, while vehicles mainly emitted UFP sizes below 50 nm. These findings reveal the variability in road and air traffic contributions to UFPs in distinct areas. Our study emphasizes the pivotal role of traffic layout in shaping urban UFP exposure.
Subject(s)
Air Pollutants , Air Pollution , Particulate Matter/analysis , Air Pollutants/analysis , Vehicle Emissions/analysis , Washington , Airports , Environmental Monitoring , Particle Size , Air Pollution/analysisABSTRACT
Airport security screening is a visual inspection task comprising search and decision. Problem solving is used to support decision making. However, it is not well understood. This study investigated how airport security screeners employ problem solving during x-ray screening, and how strategies change with experience. Thirty-nine professional security screeners were observed performing x-ray screening in the field at an Australian International Airport. Video and eye-tracking data were collected and analysed to explore activity phases and problem-solving strategies. Less-experienced screeners performed more problem solving and preferred problem-solving strategies that rely on visual examination without decision support or that defer decision making, compared to more-experienced screeners, who performed efficient and independent strategies. Findings also show that screeners need more time to develop problem-solving skills than visual scanning skills. Screeners would benefit from problem-solving support tools and intensified training and mentorship within the first six months of experience to advance problem-solving competencies.
Subject(s)
Airports , Problem Solving , Humans , Adult , Male , Female , Security Measures , Decision Making , Task Performance and Analysis , Australia , Middle Aged , Eye-Tracking Technology , X-Rays , Video Recording , Young AdultSubject(s)
Airports , Humans , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , TravelABSTRACT
This study examines the global air travel demand pattern using complex network analysis. Using the data for the top 50 airports based on passenger volume rankings, we investigate the relationship between network measures of nodes (airports) in the global flight network and their passenger volume. The analysis explores the network measures at various spatial scales, from individual airports to metropolitan areas and countries. Different attributes, such as flight route length and the number of airlines, are considered in the analysis. Certain attributes are found to be more relevant than others, and specific network measure models are found to better capture the dynamics of global air travel demand than others. Among the models, PageRank is found to be the most correlated with total passenger volume. Moreover, distance-based measures perform worse than the ones emphasising the number of airlines, particularly those counting the number of airlines operating a route, including codeshare. Using the PageRank score weighted by the number of airlines, we find that airports in Asian cities tend to have more traffic than expected, while European and North American airports have the potential to attract more passenger volume given their connectivity pattern. Additionally, we combine the network measures with socio-economic variables such as population and GDP to show that the network measures could greatly augment the traditional approaches to modelling and predicting air travel demand. We'll also briefly discuss the implications of the findings in this study for airport planning and airline industry strategy.
Subject(s)
Air Travel , Travel , AirportsABSTRACT
How to efficiently utilize the existing airport capacity without physical expansion and considerable economic inputs to meet air traffic needs is one of the important tasks of air traffic management. To improve the efficiency of capacity utilization, it is necessary to find the actual airport capacity properly. In this work, taking Shuangliu International Airport as an example, a methodology for capacity estimation is proposed that combines the empirical method with an analytical approach that uses historical performance data from the airport to construct a capacity envelope to approximate the airport's actual capacity to the greatest extent, establishes a collaborative optimization model that reflects the inherent relations between airport capacity and arrival and departure traffic demand, adopts an improved optimization algorithm to solve the model, and generates an optimal flight allocation scheme. Priority ratio is introduced to dynamically adjust management preferences for arrival and departure traffic demand to further reveal the synergy mechanism between departure and arrival traffic flow demand and the airport capacity. The result shows that the Flight On-time Performance rate is lifted by 6% in the case study which proves the feasibility of the proposed method, demonstrating its value for maximizing airport capacity and traffic flow demand without requiring expansions on airport scales.
Subject(s)
Airports , AlgorithmsABSTRACT
BACKGROUND: Ultrafine particles (UFP) are unregulated air pollutants abundant in aviation exhaust. Emerging evidence suggests that UFPs may impact lung health due to their high surface area-to-mass ratio and deep penetration into airways. This study aimed to assess long-term exposure to airport-related UFPs and lung cancer incidence in a multiethnic population in Los Angeles County. METHODS: Within the California Multiethnic Cohort, we examined the association between long-term exposure to airport-related UFPs and lung cancer incidence. Multivariable Cox proportional hazards regression models were used to estimate the effect of UFP exposure on lung cancer incidence. Subgroup analyses by demographics, histology and smoking status were conducted. RESULTS: Airport-related UFP exposure was not associated with lung cancer risk [per one IGR HR, 1.01; 95% confidence interval (CI), 0.97-1.05] overall and across race/ethnicity. A suggestive positive association was observed between a one IQR increase in UFP exposure and lung squamous cell carcinoma (SCC) risk (HR, 1.08; 95% CI, 1.00-1.17) with a Phet for histology = 0.05. Positive associations were observed in 5-year lag analysis for SCC (HR, 1.12; 95% CI, CI, 1.02-1.22) and large cell carcinoma risk (HR, 1.23; 95% CI, 1.01-1.49) with a Phet for histology = 0.01. CONCLUSIONS: This large prospective cohort analysis suggests a potential association between airport-related UFP exposure and specific lung histologies. The findings align with research indicating that UFPs found in aviation exhaust may induce inflammatory and oxidative injury leading to SCC. IMPACT: These results highlight the potential role of airport-related UFP exposure in the development of lung SCC.