Civil Airports Research Articles

Comparison of PFAS soil remediation alternatives at a civilian airport using cost-benefit analysis

Contamination of soil and water systems by per- and polyfluoroalkyl substances (PFAS) due to uncontrolled use of aqueous film-forming foams (AFFFs) at firefighting training sites at civilian and military airports is a universal issue and can lead to significant human health and environmental impacts. Remediation of these sites is often complex but necessary to alleviate the PFAS burden and minimise the risks of exposure by eliminating the hotspot/source from which the PFAS spreads. This study presents a probabilistic cost-benefit analysis (CBA) for evaluating PFAS remediation alternatives, which includes monetisation of both direct costs and benefits as well as externalities. The method is applied for a case study to compare five remediation alternatives for managing PFAS contaminated soil at Stockholm Arlanda Airport in Sweden. The social profitability, or the net present value (NPV), of each remediation alternative was calculated in comparison to two reference alternatives – ‘total excavation’ of the site (Alt 0) or ‘do nothing’. Sensitivity analyses and model scenarios were tested to account for uncertainties, including small or large PFAS spreading and simulating different values for the magnitude of annual avoided cost of inaction (i.e., aggregate benefit) from PFAS remediation. In comparison to total excavation, four of the five studied remediation alternatives resulted in a positive mean NPV. Excavation and stabilization/solidification of the hotspot on-site combined with stabilization using activated carbon for the rest of site (Alt 2) had the highest NPV for both spreading scenarios, i.e., Alt 2 was the most socially profitable alternative. Simulations of the annual avoided cost of inaction enabled estimation of the breakeven point at which a remediation alternative becomes socially profitable (NPV > 0) compared to ‘do nothing’. Alt 2 had the lowest breakeven point: 7.5 and 5.75 millions of SEK/year for large and small spreading, respectively.

Framework and Perception Survey of Tourism Accessibility Concerning Regional Airports Based on Nexus Thinking: An Empirical Study in Ganzi Prefecture, China

Blocking regional communication is the beginning of the deterioration and even destruction of civilization. Accessibility is the principal condition for the development of mountain areas and the first barrier to the breakthrough of tourism. In this context, the lack of unified transportation planning and analysis of tourists’ perceptions leads to poor accessibility and consequently the sustainable development of tourist destinations. This paper considers Yading Airport, the highest civil airport in the world, located in the mountainous area of southwest China, as an example. Based on the computed results of traffic accessibility, this research elucidates tourists’ perception with Nexus Thinking of sustainability. Furthermore, in light of deconstructing the connotation of accessibility by questionnaire, subdivision dimensions together with certain factors are paraphrased. The paper ultimately puts forward the following concepts: (1) The perception of accessibility represents invariant material form in the subjectivity space and attributes of the flow space; (2) Taking perception as the variable, evaluation of accessibility is considered affected by residents’ attitudes; (3) Tourism accessibility represents the duality between tourist flow and airport security management. These conclusions demonstrate that, in certain regions, tourism has an effect on integrating elements and constructing identity. Relevant suggestions are presented in this paper for sustainable development that relate to tourism in mountainous areas.

PFAS in fish from AFFF-impacted environments: Analytical method development and field application at a Canadian international civilian airport

Methods targeting anionic per- and polyfluoroalkyl substances (PFAS) in aquatic biota are well established, but commonly overlook many PFAS classes present in aqueous film-forming foams (AFFFs). Here, we developed an analytical method for the expanded analysis of negative and positive ion mode PFAS in fish tissues. Eight variations of extraction solvents and clean-up protocols were first tested to recover 70 AFFF-derived PFAS from the fish matrix. Anionic, zwitterionic, and cationic PFAS displayed the best responses with methanol-based ultrasonication methods. The response of long-chain PFAS was improved for extracts submitted to graphite filtration alone compared with those involving solid-phase extraction. The validation included an assessment of linearity, absolute recovery, matrix effects, accuracy, intraday/interday precision, and trueness. The method was applied to a set of freshwater fish samples collected in 2020 in the immediate vicinity (creek, n = 15) and downstream (river, n = 15) of an active fire-training area at an international civilian airport in Ontario, Canada. While zwitterionic fluorotelomer betaines were major components of the subsurface AFFF source zone, they were rarely detected in fish, suggesting limited bioaccumulation potential. PFOS largely dominated the PFAS profile, with record-high concentrations in brook sticklebacks (Culaea inconstans) from the creek (16000–110,000 ng/g wet weight whole-body). These levels exceeded the Canadian Federal Environmental Quality Guidelines (FEQG) for PFOS pertaining to the Federal Fish Tissue Guideline (FFTG) for fish protection and Federal Wildlife Diet Guidelines (FWiDG) for the protection of mammalian and avian consumers of aquatic biota. Perfluorohexane sulfonamide and 6:2 fluorotelomer sulfonate were among the precursors detected at the highest levels (maximum of ∼340 ng/g and ∼1100 ng/g, respectively), likely reflecting extensive degradation and/or biotransformation of C6 precursors originally present in AFFF formulations.

An Investigation and Benchmarking Model for Developing Sustainable Material Use Among Turkish Airport Operators

Sustainable material use refers to the capacity of a material to be utilized in a way that does not deplete the Earth’s natural resources or harm the ecosystem. This lowering might entail employing renewable or recyclable materials and reducing the overall quantity of material utilized in airport services. Renewable materials, recyclable materials, biodegradable materials, reusable materials, low-impact materials (low-emission materials), natural materials, and non-toxic materials are sustainable materials used in airports. There are 58 civil airports operated in Turkiye. The public information on the airport operators’ websites can assess sustainable material use in these airports. Mentioned 58 airports are operated under ten different airport groups. This study offered a novel scoring system called CACS which stands for Clarity, Accessibility, Continuity, and Suitability, to retrieve sustainable material use from sustainability reports of airport operators. The model proposed in this paper will help the readers benchmark a group of airports not present in the literature. The results show that İGA airport is the highest score among the ten airports, followed by TAV airports at 820.6 and 256.3, respectively. The top five airports encapsulate 97.44% after the Normalization of passenger counts of Turkiye. Airport operators’ sustainable material usage and other sustainability benchmarking on numerous domains based on sustainability reporting systems would draw the public and increase awareness, allowing operator firms and airport authorities to concentrate on creating a more livable future.

Air transport safety in UAV operational conditions

The article presents the possibilities of using unmanned aerial vehicles in air transport. The use of UAVs in the airspace has become widespread, despite many implemented legal regulations, there are many incidents that threaten not only aircraft during the flight, but also the airport infrastructure. The potential threats and the chances of implementing remedial measures were analyzed. An attempt to evaluate the possibility of maintaining aviation safety at an appropriate level in the conditions of UAV operational conditions has been done. The main research problem was defined as follows: How would implementing unmanned aerial vehicles into the air transport system influence the acceptable level of safety? The article uses theoretical methods such as: system analysis, analysis and synthesis in the field of literature, analogy, comparative method. In terms of empirical methods, an original diagnostic survey was carried out, based on a selected group of people related to the explored topic. In addition, the observation method was used by the feedbacks and observations of the group of air traffic controllers from civil airports (located in Poland). The article describes the current transformation of air transport, taking into account the planned modernizations. It presents the PansaUTM system as one of the countermeasures, monitoring and securing the movement in the airspace. Furthermore, the transponder issue was raised in relation to the enhancement of the UAV identification system, with a detailed explanation of the importance of the TCAS (Traffic Collision Avoidance System). Referring to the prospects for the development of air transport, the latest design concepts for cargo drones were presented. The issue of full transport autonomy of UAVs was analyzed based on the requirements of legal regulations. The comparison of benefits and threats in conjunction with the conducted empirical methods allowed for the development of conclusions confirming the research hypothesis and indicating the possibility of using remedial measures in the process of UAV evolution.

Energy Harvesting on Airport Pavements Ambient Dependent: Ponta Delgada Airport Case Study

Energy transition is an important issue for countries trying to meet their greenhouse gas (GHG) emission targets. To achieve this reduction, the Portuguese government has budgeted a total of EUR 116 M to aid energy transition in the Autonomous Region of the Azores by 2029. This work presents a solution for producing electricity using photovoltaic panels (PV) to settle in the top of the airport pavement. In addition to producing sustainable electricity, the implementation of panels in the civil airport infrastructure allows us to address the reduction of emissions in the ICAO’s Carbon Offsetting and the Reduction Scheme for International Aviation (CORSIA) program. Currently, PV panels are unable to support the weight of aircraft so the installation must be in the areas of the pavement where there is no regular aircraft traffic. As a result of the study, a production of about 9 GWh/year was achieved with an LCOE of 143 EUR/MWh, reducing emissions to about 6-ton CO2/year.

Территориальная структура сети аэропортов Индии

The growth of air transportation in India, caused by the economic boom in the 2010s, led to the need for the reconstruction of old (brownfield) and the construction of new (greenfield) airports. In accordance with the UDAN regional air connectivity improvement program, implemented since 2017, it is planned to build 70 airports in new locations. There are 109 civil airports of common use. Information about airports that have already been built, are under construction and are being designed is provided. Despite the implementation of part of the UDAN program, it turned out that a number of newly built airports were insufficiently loaded, new ghost airports appeared that are not in demand among air passengers. The features of the location of the country‘s airport network, its density (the number of operating passenger airports per 100 thousand square kilometers) are analyzed. Differences in the size of the Umland of airports (the ground gravity zone of one airport; calculated as the area of the territory in thousand square meters km divided by the number of passenger airports with regular traffic) and the potential air passenger capacity of the territory gravitating towards them (the number of residents of the territory per 1 operating airport). According to these three parameters (the density of the network, the size of the Umland, the air passenger capacity of the territory), a comparison was made with the network of airports in Indonesia.

An Attention-Based Deep Convolution Network for Mining Airport Delay Propagation Causality

The airport network is a highly dynamic and complex network connected by air routes, and it is difficult to study the impact of delays at one airport on another airport by means of human intervention. Due to the delay propagation law contained in the delay time series, some studies have used Granger causality and transfer entropy to explore whether there is a causal relationship between any two airports. However, no research has yet established a delay causal network from the perspective of the airport network as a whole. To this end, an attention mechanism is introduced into the deep convolutional network architecture, and a deep temporal convolution prediction model considering the attention mechanism is proposed, so as to establish the relationship between different airport delay time series under the same network architecture. According to the attention factor score, the delay propagation causality between airports is preliminarily screened, and the direct causality is verified based on a t-test and propagation delay analysis. Taking China’s civil airport network as an example, the method proposed in this paper can not only discover the causal relationship of delays between airports but also characterize the strength of the relationship. Further analysis found that each airport is affected by an average of six airports, and airports with small delays are more likely to be affected by other airports.

Thermal anti-cracking investigation of asphalt-based seal technology for airport base layer in frozen ground region

In frozen ground regions, the problems of subgrade frost damage and slab cavity were common distresses of cement concrete pavement in civil airports, causing the major safety hazard during the daily operation of airport. It was necessary to explore prevention technology of airport pavement subgrade due to frost damage. This research investigated the anti-cracking and thermal properties of asphalt-based composite seal as intermediately isolated airport base layer in cold regions. The stiffness and stress relaxation behaviors of binders were evaluated at low temperatures by bending beam rheometer test, in terms of various modifiers with styrene-butadiene rubber and liquid nitrile rubber. Based on the dissipation energy method, the viscoelastic characteristics of asphalt materials were analyzed with Burgers model. Additionally, the response regions of low-temperature rheology were expanded through the master curve establishment of flexural creep compliance. The thermal properties of binder were characterized by thermal gravity analysis and differential scanning calorimetry test. Finally, the relationships between various indices were conducted to release the polymer modification impacts on thermal cracking resistance of asphalt-based seal technology through statistical analysis. This study revealed that the cracking resistance and thermal properties of asphalt-based composite seal at low temperature was essential and efficient and should be recommended the consideration for airport pavement in cold regions.

An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements.

In view of the time series update of airport runway health status detection data, the Markov chain of stochastic process theory was adopted. Considering the influence of aircraft traffic load, age, and pavement structure surface-layer thickness on the performance deterioration process of airport runways, the method of survival analysis was used. The parameter model of survival analysis was used to establish the duration function model of the four condition states of the airport runway PCI (pavement condition index). The Markov transition matrix for the performance prediction of airport runways was constructed. In order to evaluate the ability of the Markov transition matrix method to predict the trend of deterioration for PCI of the airport runway under different conditions of aircraft traffic volume and thickness of the runway pavement surface, a data set was constructed with the actual inspection data of the airport runway, and the corresponding samples were selected for analysis. The results showed that a Markov transition matrix for airport runway performance prediction, constructed based on survival analysis theory, can combine discontinuous inspection data or monitoring data with Weibull function survival curves. The method proposed in this paper can quantitatively predict the remaining service life of airport runways and provide support for cost-effective decisions about airport pavement maintenance and rehabilitation.

Aircarft Signal Feature Extraction and Recognition Based on Deep Learning

Radio signal recognition has a wide application in future communication systems and the vehicular communication, whose core is the extraction of signal features such as electromagnetic fingerprints. With the rapid development of artificial intelligence technology, deep learning has made amazing breakthroughs in image recognition, speech recognition and other fields. Deep learning is applied to electromagnetic fingerprint extraction in this paper. Firstly, thousands of the downlink aircraft communications addressing and reporting system (ACARS) signals used for communication between civil aircraft and airport tower are collected and generated. Then a pre-transformation network suitable for electromagnetic signals is constructed to convert one-dimensional signals into two-dimensional feature maps, and afterwards the feature maps are input into the convolutional neural network (CNN) for classification. By adopting the attention modules, the classification results were improved by a few percentage points over the baseline with a little cost. The method proposed in this paper achieves an accuracy rate of 94.1% and can obtain the aircraft type in a shorter time than traditional method. Moreover, the robustness of the proposed model in response to additive Gaussian white noise (AWGN) and phase deviation is studied and tested.

Marginal reduction in surface NO2 attributable to airport shutdown: A machine learning regression-based approach

Emissions from aviation and airport-related activities degrade surface air quality but received limited attention relative to regular transportation sectors like road traffic and waterborne vessels. Statistically, assessing the impact of airport-related emissions remains a challenge due to the fact that its signal in the air quality time series data is largely dwarfed by meteorology and other emissions. Flight-ban policy has been implemented in a number of cities in response to the COVID-19 spread since early 2020, which provides an unprecedented opportunity to examine the changes in air quality attributable to airport closure. It would also be interesting to know whether such an intervention produces extra marginal air quality benefits, in addition to road traffic. Here we investigated the impact of airport-related emissions from a civil airport on nearby NO2 air quality by applying machine learning predictive model to observational data collected from this unique quasi-natural experiment. The whole lockdown-attributable change in NO2 was 16.7 μg/m3, equals to a drop of 73% in NO2 with respect to the business-as-usual level. Meanwhile, the airport flight-ban aviation-attributable NO2 was 3.1 μg/m3, accounting for a marginal reduction of 18.6% of the overall NO2 change that driven by the whole lockdown effect. The airport-related emissions contributed up to 24% of the local ambient NO2 under normal conditions. Additionally, the average impact of airport-related emissions on the nearby air quality was ∼0.01 ± 0.001 μg/m3 NO2 per air-flight. Our results highlight that attention needs to be paid to such a considerable emission source in many places where regular air quality regulatory measures were insufficient to bring NO2 concentration into compliance with the health-based limit.

Airport capacity constraints and air traffic demand in China

This paper analyzes the degree of airport capacity utilization of 239 China's civil airports in 2019. Our database is unique and very detailed in that we combine actual operation and scheduled flight data. We are particularly interested in the list of capacity constrained airports, their characteristics, and future development. To this end, we develop a classification matrix to investigate capacity constrained airports. We then forecast the demand and capacity of these airports under three scenarios and use the data as inputs for Monte Carlo simulation, to predict the capacity utilization trends of these airports in 2025 and 2035. Our research shows that: (1) There are significant differences between airports in terms of airport congestion status, and over 85% of airports in China experience no overload; (2) Big spatial differences are observed in the distribution of airports with less spare capacity and can be summarized as “more in eastern China and less in western China”; (3) Ten airports stand out as seriously capacity constrained and all of them serves as international or regional hubs; (4) Airport location, airport orientation, and linkage to the local economy are closely related to airport capacity constraints; (5) As most constrained airports are going to increase capacity in the future, as well as the outbreak of COVID-19 negatively affected aviation demand, most airports will have sufficient capacity reserves in the future. However, Shenzhen Bao'an and Xi'an Xianyang International Airport will face heavy capacity pressure. We also provide several recommendations to improve airport capacity utilization and relieve capacity shortages.

National emissions inventory and future trends in greenhouse gases and other air pollutants from civil airports in China.

Civil aviation is an important source of air pollutants, but this field has received insufficient attention in China. Based on the standard emissions model of the International Civil Aviation Organization (ICAO) and actual flight information from 241 airports, this study estimated a comprehensive emissions inventory for 2010–2020 by considering the impacts of mixing layer height. The results showed that annual pollutant emissions rapidly trended upward along with population and economic growth; however, the emissions decreased owing to the impacts of the COVID-19 pandemic. In 2020, the emissions of carbon monoxide (CO), nitrogen oxides (NOX), particulate matter (PM), methane (CH4), nitrous oxide (N2O), carbon dioxide (CO2), and water vapor (H2O) were 34.34, 65.73, 0.10, 0.34, 0.40, 14,706.26, and 5733.11 Gg, respectively. The emissions of total volatile organic compounds (VOCs) from China’s civil airports in 2020 were estimated at 17.20 Gg; the major components were formic acid (1.70 Gg), acetic acid (1.62 Gg), 1-butylene (1.03 Gg), acetone (0.96 Gg), and acetaldehyde (0.93 Gg). The distribution of pollutant emissions was consistent with the level of economic development, mainly in Beijing, Guangzhou, and Shanghai. In addition, we estimated future pollution trends for the aviation industry under four scenarios. Under the comprehensive scenario, which considered the impacts of economic growth, passenger turnover, cargo turnover, COVID-19, and technological efficiency, the levels of typical pollutants were expected to increase by nearly 1.51-fold from 2010 to 2035.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-022-21425-1.

Mixed analysis-synthesis approach for estimating airport noise from civil air traffic

This paper presents an important upgrade of a modelling tool devised by the authors for estimating aircraft noise around civil airports, which is based on a best-practice noise computation method and flight tracking data collected from the Internet and complemented by datasets of aircraft models, runways, and terrain elevation. Targeting more accurate noise predictions , the upgraded model introduces reasoned degrees of freedom in the standard flight procedures, and the tracked altitudes and speeds of each flight event are used to fit these modified procedures, which leads to an original mixed analysis-synthesis approach. Additional improvements include better runway assignment and consideration of actual weather conditions. Comparison of July 2019 results with official data for Heathrow, Gatwick and Schiphol airports shows an improved noise prediction, with an average underestimation lowered to 1.5 dB(A) for exposure-based metrics. Therefore, this upgraded modelling tool can be a reliable support to civil aviation authorities and policy-makers.

Attacks Against Civilian Objects: An Analysis Under International Humanitarian Law

Civilian airports in recent internal armed conflict are being affected by the military operations of state armed forces and non-state armed groups. A review of the recent internal armed conflict in the middle east shows increase attacks on airports, which often disrupts, altogether halts civilian navigation, and increase the risk of being affected despite the fact that international humanitarian law (IHL) does prohibit such civilian objects attack that violates humanitarian law except in certain situations when it became military objectives. Moreover, military use of airport, may not justify any attack and remains prohibited by other IHL principles. Despite the negative use of civilian airports by the military as a justification to legalize attacking airports, IHL framework restricts this practice. States did not enact national prohibitions or restrictions of military use or limit attacks against civilian airports. However, recent armed conflict indicates that states can counter violation of the protections provided to civilian objects while military use by prohibiting military use of civilian airport. This article argues that states should enact and implement the exceptional rules to attack civilian buildings and forbid military use of civilian airports.

Design parameter and method for airport asphalt mixture based on high-temperature performance

The objective of this study is to establish a design system oriented towards the rutting resistance of paving asphalt mixture. To achieve this goal, a series of experiments and analyses were conducted, including the selection of design parameter, the establishment of design method and the verification of design system. Test results indicated that in comparison with uniaxial penetration strength (UPS) and Marshall stability (MS), uniaxial compression strength (UCS) had a higher sensitivity to asphalt content and was thus suitable as a design parameter. Correlation analysis showed that linear correlation between UCS and dynamic stability was more significant with Pearson correlation coefficient (PCC) exceeding 0.8 for various types of asphalt mix, exhibiting an accurate characterization to the anti-rutting ability of asphalt mix. Moreover, 2.94 MPa was proposed as the design critical value based on fitting equation. Compared to conventional design method, the asphalt mixture from proposed method possessed a better high-temperature performance, especially under severe in-service condition where flow number increased by 27.5% to 37.1% in repeated load permanent deformation (RLPD) test and impression depth decreased by 18.3% to 19.7% in Hamburg wheel tracking (HWT) test. This research provided a new idea for anti-rutting technology innovation of asphalt pavement in civil airport field from the aspect of paving materials design.

The evaluation of operational efficiencies of Turkish airports: An integrated spherical fuzzy AHP/DEA approach

The demand for air transport services has significantly increased around the globe, which has brought new investments in airports, which, in turn, requires in-depth efficiency analysis of these capital-intensive endeavors. This study examines the operational efficiencies of 46 Turkish civil airports from 2015 to 2018. We employ a novel hybrid methodology that combines Spherical Fuzzy Sets based Analytic Hierarchy Process (SFS-AHP) and Data Envelopment Analysis (DEA), which provides a solid basis for efficiency analysis. To this end, it can handle the hesitancy and uncertainty that the subjective evaluation process of input and output factors possess. Then, we use Self Organizing Maps (SOM), a machine learning method for clustering, to examine the effect of outlier airports on the efficiency scores. Finally, a posthoc analysis is conducted with Tobit regression model to assess the explanatory power of external factors on the efficiency scores, i.e., tourism potential, number of international flights, distance to the city center, population, public/private ownership, and age of airport. The findings show that 67.2% of the Turkish airports operate below the optimal efficiency level, and 93.5% of them should make considerable efforts to refine their operations by implementing managerial and structural changes to reduce input factors. The results also suggest that the airports located in high-density touristic areas achieve higher efficiency levels. Those relatively closer to the city center lead to more airport traffic, generating more revenues. Thus, both factors have a significant impact on efficiency scores. The study provides a novel efficiency analysis framework for airport operators and policy makers that helps them make informed decisions.

Policies and Toxicological Screenings for No Drug Addiction: An Example from the Civil Aviation Workforce.

Introduction: Since 2008, Italian legislators, with the aim of ensuring public safety, have made it mandatory for an occupational doctor (OD) to assess specific categories of workers to exclude those who may have consumed drugs of abuse. Due to the relevance of work activities relating to the civil aviation and airport sector, a policy based on the use of training and information tools, as well as a health surveillance protocol, has been undertaken since 2009. Materials and methods: A total of 61,008 workers at a commercial airline underwent health surveillance between 2009 and 2019. Following ≤24 h notification, their urine was screened for opiates, cocaine, cannabinoids, amphetamines, methamphetamines, and methylenedioxymethamphetamine (MDMA) using an immunochemical test. Positive results were confirmed using Gas Chromatography-Mass Spectrometry (GC/MS) or Liquid Chromatography -Mass Spectrometry (LC/MS). In confirmed cases, the workers were declared unfit and sent to a specialized laboratory for a second level analysis. Results: Positive results, initially >1%, have halved in the last four years (<0.5%). The percentage of positive results was consistently very low among pilots and, moreover, the rare positive cases detected were due to a cross-reactivity phenomena. The highest and most discontinuous percentages seen occurred in the population undergoing a pre-employment examination. Regarding the types of substance used, a prevalence of cannabis (58.52%) and cocaine (35.2%) use was observed. Conclusions: The data presented indicate that the air transport sector, in all its components (ground workers and air crews), has a very limited number of substance abusers, and this number tends to decrease over time and with work seniority. Another aspect of particular interest, and which is more specific to toxicology, concerns the detection of cross-reactivity in urinary immunochemical screening between the antibodies to drugs of abuse and certain other drugs, such as anti-inflammatories or antibiotics; as well as foods, and other commonly used substances.

Predicting the Remaining Service Life of Civil Airport Runway considering Reliability and Damage Accumulation

Based on the MEPDG method, the operation process of MEPDG was analyzed and the MEPDG correction method applied to the remaining life prediction of airport pavement was obtained. According to the theory of structural reliability, the performance function of airport pavement was obtained based on the limit state equation represented by flexural stress. Considering the characteristics of airport cement concrete pavement design, the calculation formula of the number of allowable load actions was obtained based on reliability by NCHRP126 fatigue equation without considering the temperature stress when the flexural fatigue strength of pavement plate cement concrete was less than 1.25 times of the design strength. Based on the actual situation of local civil airport runways in Henan Province, the proposed MEPDG correction method was used to analyze the flexural stress of the actual operating airport runway pavement at 95% reliability level based on the mechanical numerical model of airport runway, and the number of allowable load actions of three aircraft models was obtained. Given the impact of pass-to-coverage ratio P/C, the cumulative damage factor CDF of the major aircraft models was calculated; the annual average growth rate of different aircraft models in the airport pavement evaluation stage was obtained based on the trend extension method. According to the predicted average annual cumulative damage, the remaining life of pavement was predicted. Compared with the actual conditions of the airport, the remaining life predicted in this paper was consistent with the actual life, which verifies the effect of the prediction of the remaining life of airport runway considering the impact of reliability and damage accumulation.