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Journal articles on the topic 'Air transportation forecasts'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Braslau, David, and Robert C. Johns. "Use of Air Transportation by Business and Industry in Minnesota." Transportation Research Record: Journal of the Transportation Research Board 1622, no. 1 (1998): 31–40. http://dx.doi.org/10.3141/1622-05.

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Current and forecasted use of air transportation by businesses in Minnesota using the Standard Industrial Classification is described. The research is based upon a study on air service and commercial and industrial activity in Minnesota required by the Minnesota legislature in 1996. Purchases from the air transportation sector that includes scheduled and nonscheduled passenger and freight services are based upon the 1993 IMPLAN input-output model for Minnesota and Bureau of Economic Analysis (BEA) and Bureau of Labor Statistics (BLS) forecasts for Minnesota. In addition to intraindustry transf

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2

Aghayev, N. B., and D. Sh Nazarli. "Modelling of non-scheduled air transportation time series based on ARIMA." Civil Aviation High Technologies 27, no. 6 (2025): 8–20. https://doi.org/10.26467/2079-0619-2024-27-6-8-20.

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Forecasting non-scheduled air transportation demand is essential for effective resource allocation, operational planning, and decision-making. In this paper, the use of the ARIMA (Auto Regressive Integrated Moving Average) model for forecasting non-scheduled air transportation is explored. The ARIMA model is a widely employed time series forecasting technique which combines autoregressive (AR), differencing (I), and moving average (MA) components. It has been successfully applied to various fields and can be adapted to capture the patterns and trends in non-scheduled air transportation data. T

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Adrianova, A. V. "ANALYSIS OF PASSENGER AIR TRANSPORTATION CHANGES UNDER THE EXTERNAL ENVIRONMENT INFLUENCE." System analysis and logistics 4, no. 26 (2020): 96–107. http://dx.doi.org/10.31799/2007-5687-2020-4-96-107.

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The article examines the external conditions that determine the processes of the air transport participants operation. The impact of the COVID-19 pandemic on civil aviation has been studied: statistics on the decline in the number of flights in the world and the passenger traffic reduction in European countries are given, their economic losses are estimated. The aviation market state in the Baltic region has been investigated. Existing forecasts for the industry recovery after the introduction of restrictions on the fight against the COVID-19 virus are outlined. Keywords: air transportation, p

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Feoktistova, O. G., and D. Yu Potapova. "Using correlation matrices in predicting airline performance." Omsk Scientific Bulletin, no. 179 (2021): 15–18. http://dx.doi.org/10.25206/1813-8225-2021-179-15-18.

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The article considers the issue of making forecasts of the main indicators of the activities of airlines for their effective functioning in the air transportation market. It describes the life cycle of airlines and provides a classification of the forecasts that are currently being made. The interrelation of correlations of the key parameters of the airline’s functioning is considered, the use of correlations in forecasting is shown, actual calculations are presented, and a significant increase in forecast accuracy when using this forecasting method is demonstrated.

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Zhu, Shoupeng, Yang Lyu, Hongbin Wang, et al. "Pavement Temperature Forecasts Based on Model Output Statistics: Experiments for Highways in Jiangsu, China." Remote Sensing 15, no. 16 (2023): 3956. http://dx.doi.org/10.3390/rs15163956.

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Forecasts on transportation meteorology, such as pavement temperature, are becoming increasingly important in the face of global warming and frequent disruptions from extreme weather and climate events. In this study, we propose a pavement temperature forecast model based on stepwise regression—model output statistics (SRMOS) at the short-term timescale, using highways in Jiangsu, China, as examples. Experiments demonstrate that the SRMOS model effectively calibrates against the benchmark of the linear regression model based on surface air temperature (LRT). The SRMOS model shows a reduction i

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Aghayev, N. B., and D. Sh Nazarli. "Hybrid forecasting model of non-scheduled passenger air transportation." Civil Aviation High Technologies 28, no. 2 (2025): 8–21. https://doi.org/10.26467/2079-0619-2025-28-2-8-21.

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In the article, an ARIMA-Fuzzy-based hybrid model is proposed for forecasting time series of non-scheduled passenger air transportation. As it is known, the ARIMA model is applied to identify linear trends and regularities within time series data as well as for forecasting. The study of scientific research literature shows that the ARIMA model has its own limitations in managing non-linearity and random changes during forecasting. Since the process of non-scheduled air transportation depends on random changes as a stochastic process, the mentioned model does not cover the whole process. For th

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Wu, Xiangli, and Shan Man. "Air transportation in China: Temporal and spatial evolution and development forecasts." Journal of Geographical Sciences 28, no. 10 (2018): 1485–99. http://dx.doi.org/10.1007/s11442-018-1557-y.

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Nurlanuly, Abdul-Khassen, Nazym Akhmetzhanova, Oxana Kirichok, Ardakh Azimkhan, and Nailya Abdildinova. "Assessment of the air transportation market in the economies of newly independent states and forecast of its development." International Journal of Innovative Research and Scientific Studies 8, no. 3 (2025): 3843–51. https://doi.org/10.53894/ijirss.v8i3.7396.

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The air transportation market in the newly independent states is a dynamically developing sector that significantly influences economic growth and the integration of these countries into the global economy. The aim of this study is to assess the relationship between air transportation indicators and economic indicators, including GDP per capita. A comparative analysis was conducted across three periods: pre-pandemic (2016–2019), during the COVID-19 pandemic (2020–2021), and post-pandemic (2022–2024), using correlation and regression analysis, as well as the ARIMA time series forecasting model.

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Kuzmina, Lyudmila V., та Alexandra S. Merzlikina. "«Сlosed sky» shock: trends and forecasts". Vestnik of Samara University. Economics and Management 13, № 2 (2022): 63–70. http://dx.doi.org/10.18287/2542-0461-2022-13-2-63-70.

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The article deals with situations related to the closure of airspace and a significant decrease in the number of air traffic, which we have observed twice in recent history. For the first time in 2020, due to the spread of the new COVID-19 coronavirus infection, there was a powerful wave of closure of air traffic between the countries. For the second time, in 2022, there was a similar closure of airspace, but for other reasons of a station nature that arose due to the introduction of a number of sanctions and restrictive measures (a ban on landing, taking off and flying over the territory) fro

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Benjamin, Stanley G., Stephen S. Weygandt, John M. Brown, et al. "A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh." Monthly Weather Review 144, no. 4 (2016): 1669–94. http://dx.doi.org/10.1175/mwr-d-15-0242.1.

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Abstract The Rapid Refresh (RAP), an hourly updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA/National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the prev

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Sushko, O. P. "Modelling of Air Passenger Transportation in Russia." World of Transport and Transportation 20, no. 6 (2023): 64–71. http://dx.doi.org/10.30932/1992-3252-2022-20-6-7.

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The use of economic and mathematical methods of forecasting the results of activities of civil aviation organisations, and in particular assessment of the volume of air passenger traffic is quite relevant due to the importance of operational planning of air transport processes, development of strategic directions, technological and technical renewal of air enterprises.The objective of the study is to plan the traffic flow of air passengers using a regression model, considering the results of multifactorial selection of determinants, particularly distinguishing fundamental macro indicators are

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Sharma, Dr Shweta. "Machine Learning-Based Prediction of PM2.5 and PM10 Levels in Raipur’s Air Quality." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50284.

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Abstract: Urban air quality is becoming an increasingly critical issue in India due to rapid urban and industrial growth. Raipur, the capital of Chhattisgarh, faces worsening air quality driven by transportation, construction, and industrial emissions. This paper investigates PM2.5 and PM10 pollutant trends and applies machine learning techniques to forecast short-term air quality using meteorological and environmental inputs. Historical air quality data spanning January 2018 to March 2024 was sourced from the Central Pollution Control Board (CPCB) and OpenAQ. After rigorous preprocessing, mac

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Çatuk, Cüneyt. "Forecasting Turkey’s Air Cargo Tonnage: A Comparative Analysis of Statistical Techniques and Machine Learning Methods." Journal of Aviation 9, no. 1 (2025): 109–17. https://doi.org/10.30518/jav.1582814.

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With the expanding global economy, the demand for air logistics continues to grow, further emphasizing its significance. However, this increased demand also presents a barrier to the growth of the air transportation sector, which is marked by a high degree of vulnerability. This study aims to forecast cargo volumes in the air logistics sector, which holds considerable growth potential. To achieve this, two statistical models (SARIMA and ARIMAX) and three machine learning methods (Gradient Boosting Regression Tree, Random Forest, and Support Vector Regression) were utilized in a comparative ana

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Kim, T., and O. Kryvtsov. "Possibilities and prospects for airport revenue recovery by applying international strategies of economic development." Bulletin of V. N. Karazin Kharkiv National University Economic Series, no. 104 (June 30, 2023): 37–44. http://dx.doi.org/10.26565/2311-2379-2023-104-05.

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The global air transportation market has tremendously changed over the past three years. Worldwide quarantine restrictions complicated the process of aeronautical communication both at the domestic and international levels. Lockdown resulted in a sharp decrease in the volume of world passenger traffic - a vital source of airport revenues. This article studied global airport revenues and classified airport services by type and revenues according to the sources of their receipt. The structure of aeronautical and non-aeronautical revenues was given, and the most common airport charges were charac

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Kotegawa, Tatsuya, Daniel A. DeLaurentis, and Aaron Sengstacken. "Development of network restructuring models for improved air traffic forecasts." Transportation Research Part C: Emerging Technologies 18, no. 6 (2010): 937–49. http://dx.doi.org/10.1016/j.trc.2010.03.004.

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Kshirsagar, Pravin R., Hariprasath Manoharan, Shitharth Selvarajan, et al. "A Radical Safety Measure for Identifying Environmental Changes Using Machine Learning Algorithms." Electronics 11, no. 13 (2022): 1950. http://dx.doi.org/10.3390/electronics11131950.

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Due to air pollution, pollutants that harm humans and other species, as well as the environment and natural resources, can be detected in the atmosphere. In real-world applications, the following impurities that are caused due to smog, nicotine, bacteria, yeast, biogas, and carbon dioxide occur uninterruptedly and give rise to unavoidable pollutants. Weather, transportation, and the combustion of fossil fuels are all factors that contribute to air pollution. Uncontrolled fire in parts of grasslands and unmanaged construction projects are two factors that contribute to air pollution. The challe

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Deng, Muge. "Time Series Analysis of China’s Air Passenger Traffic Amid the COVID-19 Pandemic." BCP Business & Management 34 (December 14, 2022): 1168–78. http://dx.doi.org/10.54691/bcpbm.v34i.3155.

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China’s air transportation industry has a great development in recent decades along with economic growth and liberalization. However, the impact of COVID-19 pandemic on China’s civil aviation industry is severe and persistent. The paper discusses the development of China’s air transportation and examines the impact of the pandemic on airline industry. The Autoregressive Distributed Lag (ADL) Model and Granger Causality test will be used to investigate the relationships between China’s air passenger traffic and its potential factors including the new COVID-19 cases in China, the Consumer Price

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18

Molodets, B., Т. Bulana, and D. Boldyriev. "Analysis of existing architectures for the development of an information system of air quality assessment." System technologies 5, no. 160 (2025): 3–10. https://doi.org/10.34185/1562-9945-5-160-2025-01.

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The paper focuses on the development of information technology for weather modeling and forecasting using modern deep learning methods. The relevance of the topic is driven by growing climate risks, an increase in the frequency of extreme weather events, and the need for highly accurate meteorological analytics for the agricultural sector, transportation, en-ergy, and civil defense systems. FourCastNet, a modern architecture based on deep neural networks and transformers that combines high performance with the ability to process large-scale historical meteorological data, was chosen as the mai

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19

Guan, Yiyang. "A Comprehensive Analysis of Santiago's Air Quality Forecasts Using SARIMA Model." Theoretical and Natural Science 42, no. 1 (2024): 95–104. http://dx.doi.org/10.54254/2753-8818/42/2024ch0218.

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Abstract. This study analyses Santiagos air quality by forecasting key pollutant concentrations- PM2.5, PM10, NO, and O-over June 2024 to May 2025 using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Historical data from 2016 to 2024 shows seasonal peaks, particularly in winter, driven by residential heating and atmospheric conditions. A notable decrease in annual peak NO level, from 71 g/m in 2019 to 23 g/m in 2020, likely due to the COVID-19 pandemic and air quality initiatives. The SARIMA forecasts indicate that PM2.5 levels could reach up to 80 g/m, NO around 28 g/m,

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Mumtaz, Rafia, Arslan Amin, Muhammad Ajmal Khan, Muhammad Daud Abdullah Asif, Zahid Anwar, and Muhammad Jawad Bashir. "Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques." Energies 16, no. 16 (2023): 6087. http://dx.doi.org/10.3390/en16166087.

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Transitioning to green energy transport systems, notably electric vehicles, is crucial to both combat climate change and enhance urban air quality in developing nations. Urban air quality is pivotal, given its impact on health, necessitating accurate pollutant forecasting and emission reduction strategies to ensure overall well-being. This study forecasts the influence of green energy transport systems on the air quality in Lahore and Islamabad, Pakistan, while noting the projected surge in electric vehicle adoption from less than 1% to 10% within three years. Predicting the impact of this cha

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Thompson, Douglas, Michael Baker, and Dennis Wade. "Conformity: Long-Term Prognoses for Selected Ozone Nonattainment Areas in California." Transportation Research Record: Journal of the Transportation Research Board 1587, no. 1 (1997): 44–51. http://dx.doi.org/10.3141/1587-06.

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The Clean Air Act requires that long-range transportation plans conform to emissions budgets established for nearer-term attainment years in state implementation plans (SIPs). This poses the question of whether travel growth in the intervening period may overwhelm the benefits of fleet turnover and adopted control strategies, with adverse implications for air quality and for conformity. Emissions trends are examined for three planning areas in California that are nonattainment for ozone. Forecasted emissions of ozone precursors for attainment years are compared with projected emissions for 202

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22

Garnov, A. P. "Trends in Russian Logistics Development: Forecasts and Reality." Vestnik of the Plekhanov Russian University of Economics 20, no. 5 (2023): 187–94. http://dx.doi.org/10.21686/2413-2829-2023-187-194.

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The goal of the article is to analyze forecasts and actual development of Russian logistics on the basis of concrete example, figures, quotations and references to research. Today Russian logistics is passing the stage of active development, however, there are a lot of challenges and problems that should be overcome. A key trend in Russian logistics development is digitalization and introduction of new technologies. According to the research conducted by the Committee on Logistics Development, in 2020 about 78% of logistical market participants in Russia supported introduction of digital innov

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Noreiga, Quentin, and Mark McDonald. "Parsimonious Modeling and Uncertainty Quantification for Transportation Systems Planning Applied to California High-Speed Rail." Transportation Research Record: Journal of the Transportation Research Board 2266, no. 1 (2012): 49–59. http://dx.doi.org/10.3141/2266-06.

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This paper presents a parsimonious travel demand model (PTDM) derived from a proprietary parent travel demand model developed by Cambridge Systematics (CS) for the California high-speed rail system. The purpose of the PTDM is to reduce computational expense for model simulations, optimization and sensitivity analyses, and other repetitive analyses. The PTDM is used to quantify the significance of parameter uncertainties with the use of mean value first-order second moment methods for uncertainty quantification and sensitivity analysis. The PTDM changes the model resolution of the parent travel

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Kim and Lee. "Development of a Cost Forecasting Model for Air Cargo Service Delay Due to Low Visibility." Sustainability 11, no. 16 (2019): 4390. http://dx.doi.org/10.3390/su11164390.

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The air cargo market is growing due to the spread of information technology (IT) products, the expansion of e-commerce, and high value-added products. Weather deterioration is one factor with a substantial impact on cargo transportation. If the arrival of cargo is delayed, supply chain delays occur. Because delays are directly linked to costs, companies need precise predictions of cargo transportation. This study develops a forecasting model to predict delay times and costs caused by the delayed arrival of cargo due to severe weather in the air cargo service environment. A seasonal autoregress

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Imanov, Tapdig. "Urban Air Mobility (UAM) Network. Case Study: Baku Metropolitan Area." Volume 05 Issue 01 vm05, is01 (2024): 53–74. http://dx.doi.org/10.23890/ijast.vm05is01.0105.

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The development and implementation of the Urban Air Mobility transportation system, using electric vertical takeoff and landing (e-VTOL) aircrafts are the most promising solutions to mitigate growing congestion in big cities. The multiple studies and assumed forecasts indicate a transformation of urban and regional transportation infrastructure while applying the air mobility concept. This study analyzes the feasibility of UAM operations focused on the selection of service segmentation with relevant use cases, which allows for define suitable air vehicle configurations for optimization of poss

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O'Neal, Thomas R., John M. Dickens, Lance E. Champagne, Aaron V. Glassburner, Jason R. Anderson, and Timothy W. Breitbach. "Sortie-based aircraft component demand rate to predict requirements." Journal of Defense Analytics and Logistics 5, no. 2 (2021): 214–23. http://dx.doi.org/10.1108/jdal-10-2021-0009.

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PurposeForecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs.Desi

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Jorquera, Mario E. "Use of Episodic Controls to Reduce Frequency and Severity of Air Pollution Events." Transportation Research Record: Journal of the Transportation Research Board 1587, no. 1 (1997): 35–43. http://dx.doi.org/10.3141/1587-05.

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Most common urban air pollution episodes occur during readily identifiable meteorological conditions that contribute to the problem. In contrast, most air pollution controls concentrate on permanent curtailments of emissions. The argument is put forth that episodic emission control strategies can be an effective supplement to traditional measures, at a fraction of the cost. Questions regarding the legality of episodic controls have been the main barrier to their implementation. These legal issues are discussed. In addition, the forecasting and modeling implications of episodic controls are con

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Delgado, Luis, Gérald Gurtner, Andrew Cook, Jorge Martín, and Samuel Cristóbal. "A multi-layer model for long-term KPI alignment forecasts for the air transportation system." Journal of Air Transport Management 89 (October 2020): 101905. http://dx.doi.org/10.1016/j.jairtraman.2020.101905.

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Chupin, Alexander, Dmitry Morkovkin, Marina Bolsunovskaya, Anna Boyko, and Alexander Leksashov. "Techno-Economic Sustainability Potential of Large-Scale Systems: Forecasting Intermodal Freight Transportation Volumes." Sustainability 16, no. 3 (2024): 1265. http://dx.doi.org/10.3390/su16031265.

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The sustainability of large economies is one of the most important challenges in today’s world. As the world strives to create a greener and more efficient future, it becomes necessary to accurately analyze and forecast freight volumes. By developing a reliable freight transportation forecasting model, the authors will be able to gain valuable insights into the trends and patterns that determine the development of economic systems. This will enable informed decisions on resource allocation, infrastructure development, and environmental impact mitigation. Such a model takes into account various

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Kochkina, Elena, Elena Radkovskaya, and Kseniya Denezhkina. "Analysis and forecasting of performance indicators of air transport facilities." E3S Web of Conferences 291 (2021): 08009. http://dx.doi.org/10.1051/e3sconf/202129108009.

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Aviation is one of the most significant growth drivers not only for the transportation infrastructure, but also for country’s economy as it contributes to both industrial and social progress of society. The paper focuses on Sheremetyevo International Airport, one of the largest Russian airports and analyzes it in terms of short-term and long-term perspectives. Using real statistical data, the article presents the models for forecasting essential performance indicators of airports, namely, passenger traffic and revenue. By comparing quality characteristics, most suitable models were selected an

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Dermadi, Yedi, Shinta Devi Lukitasari, and Annisaa Nurhayati. "Weather Analysis of Flight Delay at Husein Sastranegara Airport." ITEJ (Information Technology Engineering Journals) 4, no. 2 (2019): 89–98. http://dx.doi.org/10.24235/itej.v4i2.31.

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Flight is an activity that is very vulnerable to weather conditions. The accuracy of weather information strongly supports flight activities. The effects of bad weather on flights include flight delays and flight cancellations. Based on data on flight delays from the Directorate General of Air Transportation of the Ministry of Transportation from January to March 2019 at Husein Sastranegara Airport, it is known that 20-30% of flight delays are caused by weather constraints. To estimate flight delays based on weather forecasts, weather data analysis is carried out to determine the type of weath

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Serafin, Marek, and Ryszard Zaremba. "Introduction to forecasts for the "great CPC" - demand approach." Transportation Overview - Przeglad Komunikacyjny 2019, no. 9 (2019): 19–28. http://dx.doi.org/10.35117/a_eng_19_09_03.

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The creation of the „Polish Great Central Transportation Port” (CPK) is considered already justified despite the fact that no detailed traffic forecast for different scenarios of market development has been created and presented. They are to be prepared in the future. In our Report, we created traffic forecasts for the CPK based on the key market and business assumptions. The airport will focus on transit traffic carried by network carriers. The proper and attractive conditions to serve low cost and charter airlines will not be created. Almost the entire transit traffic from Polish regions wil

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Endiz, Mustafa Sacid. "A Comparison of Battery and Hydrogen Fuel Cell Electric Vehicles for Clean Transportation." Orclever Proceedings of Research and Development 2, no. 1 (2023): 10–17. http://dx.doi.org/10.56038/oprd.v2i1.230.

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Burning fossil fuels for transportation is a major source of greenhouse gas emissions, which contribute to global warming, air pollution, and health problems. Research estimates that cars alone emit more than 300 million tons of carbon dioxide into the atmosphere each year due to the internal combustion engines that use fossil fuels. In contrast to fossil fuel vehicles, electric vehicles have zero tailpipe emissions. Therefore, countries around the world are making efforts to use electric vehicles instead of fossil fuels. Two of the available alternatives to internal-combustion engines are bat

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COLIZZA, V., A. BARRAT, M. BARTHÉLEMY, and A. VESPIGNANI. "EPIDEMIC PREDICTABILITY IN META-POPULATION MODELS WITH HETEROGENEOUS COUPLINGS: THE IMPACT OF DISEASE PARAMETER VALUES." International Journal of Bifurcation and Chaos 17, no. 07 (2007): 2491–500. http://dx.doi.org/10.1142/s0218127407018567.

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We study the predictability of epidemic forecasts in a data-driven meta-population model considering the complete air transportation system and the associated urban areas. We define the predictability as the robustness of the system evolution with respect to the stochastic fluctuations. As a quantitative measure of predictability we consider the information similarity of the time series characterizing different epidemic outbreaks with the same initial conditions. We study the predictability as a function of the parameters describing the basic susceptible-latent-infected and recovered disease d

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Sun, Wenzhi. "A case study on the potential impact of a private vehicles switch to electric vehicles in Lagos, Nigeria." Applied and Computational Engineering 62, no. 1 (2024): 185–91. http://dx.doi.org/10.54254/2755-2721/62/20240425.

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Lagos is a major city in Africa that faces environmental challenges such as carbon emissions and air pollution. With the rising cost of fossil fuels and increasing environmental awareness, the movement of private vehicles to electric vehicles is worth discussing. This paper explores the potential impacts of switching private vehicles to electric vehicles in Lagos, including the impacts on air quality, carbon emissions, and energy infrastructure. The paper analyses the data by analysing the current state of transportation in Lagos, current energy demand and supply. It also discusses the future

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Balkan, Dursun, and Goknur Arzu Akyuz. "Logistics Sector Turnover: Forecasting for Turkey, EU27 and EA19 under Effects of COVID-19." Logistics 7, no. 2 (2023): 23. http://dx.doi.org/10.3390/logistics7020023.

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Background: The logistics sector is the backbone of today’s global trade, and is vital for the continuity of goods and services. The sector is gaining increased importance as logistics operate under the extreme conditions the world is passing through (COVID-19, earthquakes, wars). Methods: A comparative study is offered for Turkey and the EU27 and EA19 countries utilizing Eurostat database time series data for logistics turnover, based on regression analysis with and without COVID-19-affected data. General trends are identified regarding the logistics turnover and average turnover by different

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Cline, Richard C., Terry A. Ruhl, Geoffrey D. Gosling, and David W. Gillen. "Air transportation demand forecasts in emerging market economies: a case study of the Kyrgyz Republic in the former Soviet Union." Journal of Air Transport Management 4, no. 1 (1998): 11–23. http://dx.doi.org/10.1016/s0969-6997(97)00012-4.

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Soulie, Antonin, Claire Granier, Sabine Darras, et al. "Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses." Earth System Science Data 16, no. 5 (2024): 2261–79. http://dx.doi.org/10.5194/essd-16-2261-2024.

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Abstract. Anthropogenic emissions are the result of many different economic sectors, including transportation, power generation, industrial, residential and commercial activities, waste treatment and agricultural practices. Air quality models are used to forecast the atmospheric composition, analyze observations and reconstruct the chemical composition of the atmosphere during the previous decades. In order to drive these models, gridded emissions of all compounds need to be provided. This paper describes a new global inventory of emissions called CAMS-GLOB-ANT, developed as part of the Copern

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Chai, Wenguang, Qingfeng Luo, Zhizhe Lin, Jingwen Yan, Jinglin Zhou, and Teng Zhou. "Spatiotemporal Dynamic Multi-Hop Network for Traffic Flow Forecasting." Sustainability 16, no. 14 (2024): 5860. http://dx.doi.org/10.3390/su16145860.

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Accurate traffic flow forecasting is vital for intelligent transportation systems, especially with urbanization worsening traffic congestion, which affects daily life, economic growth, and the environment. Precise forecasts aid in managing and optimizing transportation systems, reducing congestion, and improving air quality by cutting emissions. However, predicting outcomes is difficult due to intricate spatial relationships, nonlinear temporal patterns, and the challenges associated with long-term forecasting. Current research often uses static graph structures, overlooking dynamic and long-r

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Valeev, Sagit, and Natalya Kondratyeva. "The Air Transportation System as a Subsystem of Modern Communication Space: Analysis Based on Transfer Entropy Graphs." Applied Sciences 14, no. 23 (2024): 11291. https://doi.org/10.3390/app142311291.

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The processes of information exchange and the movement of material flows form a communication space that reflects the relationship of complex intersystem interactions in various spheres of our life within the framework of the concepts of information-theoretical theory. One of these concepts, reflecting the mutual influence between processes at a qualitative level, is the transfer of entropy. The direction and intensity of these flows reflect the main social and economic processes. As it is known, air transport is one of the most reliable and high-speed modes of transport, influencing the proce

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Hustenko, Oleksii S., and Inna A. Khomenko. "Fog and overcast low-level stratiform cloud characteristics at the airport of Lviv from surface observations." Physical Geography and Geomorphology 47, no. 1 (2024): 14–22. http://dx.doi.org/10.17721/phgg.2024.1-2.02.

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Fog and low-level stratiform clouds have been identified as hazardous weather phenomena, resulting in various losses, including time, money, and, most importantly, human lives in aviation transportation. Fog and low-level stratus pose substantial risks to aviation, especially during takeoff, landing, and low-level flying, due to conditions of reduced visibility. Forecasting low-level stratiform clouds and fog is a challenging aspect of aviation meteorology due to the similarity in the mechanisms of their formation, complex and non-deterministic processes in the atmospheric boundary layer, and

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Mao, Kewen, Hiu fung Liang, Yanxi Wu, and Ruixuan Shi. "Engineering a Sustainable Future: Evaluating the Multifaceted Impacts of Transitioning to All-Electric Bus Fleets in Urban Areas." Highlights in Science, Engineering and Technology 108 (August 13, 2024): 69–81. http://dx.doi.org/10.54097/kx63cs47.

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The global shift towards electric buses in urban transportation, driven by growing concerns over air pollution and climate change, represents a significant departure from the traditional reliance on diesel buses. However, the transition from fossil fuel-powered to electric buses is a complex process that, if not properly managed, could lead to unintended ecological consequences. To comprehensively assess the environmental impact of transitioning to an all-electric bus fleet, we developed an innovative environmental index model that goes beyond the conventional well-to-wheel (WTW) analysis of p

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Sperber, Dario, and Klaus Gierens. "Towards a more reliable forecast of ice supersaturation: concept of a one-moment ice-cloud scheme that avoids saturation adjustment." Atmospheric Chemistry and Physics 23, no. 24 (2023): 15609–27. http://dx.doi.org/10.5194/acp-23-15609-2023.

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Abstract. A significant share of aviation's climate impact is due to persistent contrails. Thus, avoiding the creation of contrails that exert a warming impact is a crucial step in approaching the goal of sustainable air transportation. For this purpose, a reliable forecast of when and where persistent contrails are expected to form is needed (i.e. a reliable prediction of ice supersaturation). With such a forecast at hand, it would be possible to plan aircraft routes on which the formation of persistent contrails can be avoided. One problem on the way to these forecasts is the current systema

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Thepchalerm, Teeris, and Phutawan Ho. "Impacts of COVID-19 on Airline Business: An Overview." 11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 11, no. 1 (2020): 130. http://dx.doi.org/10.35609/gcbssproceeding.2020.11(130).

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Corona Virus Disease 2019 or COVID-19 has spread globally and been concerned as a pandemic by the World Health Organization (WHO, 2020a). The virus has an enormous social and economic impact. United Nations Industrial Development Organization (2020) expects that the 2020 global GDP shall range between -8% to 1% depended on the situation during the last six months of 2020. Various businesses – tourism, hospitality, restaurant and transportation get affected by this pandemic. The airline business is one of the most vulnerable business since it is highly sensitive to change in the market environm

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Cutler, Marc, Lance Grenzeback, Alice Cheng, and Richard Roberts. "Assessment of Market Demand for Cross-Harbor Rail Freight Service in the New York Metropolitan Region." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (2000): 17–26. http://dx.doi.org/10.3141/1719-03.

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An investment study sponsored by the New York City Economic Development Corporation with Intermodal Surface Transportation Efficiency Act of 1991 funds evaluated strategies for improving the movement of freight by rail to an 11-county subregion (including New York City) of the New York and northern New Jersey metropolitan area located east of the Hudson River. The major achievements of the process were the use of choice modeling techniques to understand the decision making of shippers and, in combination with other data sources, forecasting the demand for freight infrastructure investments. Th

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Zaitseva, Irina V., and Ekaterna G. Sycheva. "SUSTAINABILITY OF CIVIL AVIATION DEVELOPMENT IN THE ARCTIC REGIONS ON THE BASIS OF AN ENVIRONMENTAL AND RESOURCE APPROACH." Economy of the North-West: problems and prospects of development 4, no. 79 (2024): 125–36. https://doi.org/10.52897/2411-4588-2024-4-125-136.

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Problems of development of the Arctic are relevant in terms of effective resource supply and improving environmental safety. The implementation of the concept of sustainable development is possible with the integrated development of the Arctic and requires the development of an environmental and resource approach. Strategic documents for the development of the Arctic 2020–2024 define, that improving transport infrastructure should preserve the ecosystem and reduce air pollution. Trends in aviation ecology improvement according to ICAO forecasts are analyzed, operation of cross-polar routes, nu

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Vaughan, G., J. Methven, D. Anderson, et al. "Cloud Banding and Winds in Intense European Cyclones: Results from the DIAMET Project." Bulletin of the American Meteorological Society 96, no. 2 (2015): 249–65. http://dx.doi.org/10.1175/bams-d-13-00238.1.

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Abstract The Diabatic Influences on Mesoscale Structures in Extratropical Storms (DIAMET) project aims to improve forecasts of high-impact weather in extratropical cyclones through field measurements, high-resolution numerical modeling, and improved design of ensemble forecasting and data assimilation systems. This article introduces DIAMET and presents some of the first results. Four field campaigns were conducted by the project, one of which, in late 2011, coincided with an exceptionally stormy period marked by an unusually strong, zonal North Atlantic jet stream and a succession of severe w

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Frnda, Jaroslav, Marek Durica, Jan Nedoma, Stanislav Zabka, Radek Martinek, and Michal Kostelansky. "A Weather Forecast Model Accuracy Analysis and ECMWF Enhancement Proposal by Neural Network." Sensors 19, no. 23 (2019): 5144. http://dx.doi.org/10.3390/s19235144.

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This paper presents a neural network approach for weather forecast improvement. Predicted parameters, such as air temperature or precipitation, play a crucial role not only in the transportation sector but they also influence people’s everyday activities. Numerical weather models require real measured data for the correct forecast run. This data is obtained from automatic weather stations by intelligent sensors. Sensor data collection and its processing is a necessity for finding the optimal weather conditions estimation. The European Centre for Medium-Range Weather Forecasts (ECMWF) model ser

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Rivera, Antonio, Pedro Ponce, Omar Mata, Arturo Molina, and Alan Meier. "Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing." Sensors 23, no. 22 (2023): 9060. http://dx.doi.org/10.3390/s23229060.

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Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide conc

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Lee, Jane, Lavanya Marla, and Alexandre Jacquillat. "Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty." Transportation Science 54, no. 4 (2020): 973–97. http://dx.doi.org/10.1287/trsc.2020.0983.

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Air traffic disruptions result in flight delays, cancellations, passenger misconnections, and ultimately high costs to aviation stakeholders. This paper proposes a jointly reactive and proactive approach to airline disruption management, which optimizes recovery decisions in response to realized disruptions and in anticipation of future disruptions. The approach forecasts future disruptions partially and probabilistically by estimating systemic delays at hub airports (and the uncertainty thereof) and ignoring other contingent disruptions. It formulates a dynamic stochastic integer programming

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