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Impacts of severe weather events on high-speed rail and aviation delays

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Abstract

Transportation systems have become much more vulnerable due to the increased amount of unexpected severe weather events caused by the effects of climate change. One of the direct consequences is that the punctuality of transportation systems is severely affected and the prediction of the on-time performance of scheduled service becomes challenging due to the uncertainty of severe weather's occurrence. The objective of this paper is to investigate two fundamental questions pertaining to the operational reliability of passenger transportation systems, using high-speed rail (HSR) and aviation in China as an example: what are the impacts of severe weather events on HSR and aviation delays, and to what extent are these systems vulnerable to various types of severe weather events? To address these questions, a dataset with 350,000 detailed , on-time performance records of HSR and air services for the period October 2016-September 2017 was adopted. Based on data visualization and statistical analysis, the study reveals that the impacts of severe weather events on HSR and aviation's on-time performance vary spatially and temporally. In general, HSR is less vulnerable than aviation to most severe weather events. In terms of the spatial variation, the operation of HSR in the southeast coastal region is affected more frequently by rain and thunderstorms, whereas the system operated in central-eastern China is more vulnerable to snowstorms.

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... Nevertheless, the development of multimodal transportation systems has been generally perceived as a critical solution to enhance transportation resilience to severe weather events, given it provides people with an alternative of travel under disruptive events Chen and Rose, 2018). The massive development of HSR in Europe and China, in particular, has made modal substitution become more convenient than before, which hence, may improve the resilience of the overall transportation system (Prussi and Lonza, 2018;Chen and Wang, 2019). ...
... They also recommended a modal shift on cooperation rather than in competition between air and HSR. In the case of China, Chen and Wang (2019) investigated the impacts of severe weather events on HSR and aviation's on-time performance (OTP) based on data visualization and statistical analysis. Their study revealed that HSR is generally less vulnerable to the influence of severe weather events than aviation, although the level of influence varies among different regions. ...
... Transportation system operation is affected by various types of weather conditions, such as wind speeds, thunderstorms, lightning, heavy snow, and fog (Savonis et al., 2008;Pejovic et al., 2009;Yair, 2018;Chen and Wang, 2019). For example, Mäkelä et al. (2013) found thunderstorms have a significant impact on aviation safety, even in the cold season. ...
Article
High-speed rail (HSR) has become a competitive mode with aviation for medium-distance intercity travel, given the massive deployment of the HSR infrastructure network in China. While the travel experience with both HSR and air has become more convenient, the systems' operational reliability in terms of punctuality remains a key concern, especially during disruptive events, such as under severe weather conditions. Although previous studies have attempted to investigate the impact of severe weather events on the operational performance of transportation systems, there is still a lack of ability to forecast to what extent the performance of different transportation systems may vary under various conditions. This study develops an integrated modeling framework that allows us to predict the performance of weather-induced delays of different transportation systems, including HSR and aviation. By applying machine-learning methods to real-world transportation performance data, the study examines the robustness of the method, variations of data characteristics and the different applications of the predictive modeling system. Overall, the concept and modeling framework provide important implications for the improvement of transportation system resilience to various severe weather-related disruptions through the understanding of the impact and its predictability of the system performance.
... It took several months for stations seriously affected to be fully functional again (Zhu, Ozbay, Xie, & Yang, 2016). The direct economic costs of the 2008 ice storm in China totalled $22.3 billion (Chen & Wang, 2019). Figure 1 shows the increasing number and duration of disruptions in the past years in the Netherlands, while increasing disruption impacts can be expected in the future due to increasing transport demand (Van Aken, Bešinovic, & Goverde, 2017a) and climate changes (Dawson, Shaw, & Roland Gehrels, 2016). ...
... So far, researchers mostly focused on scenario-specific studies and looked into weatherrelated disruptions and disasters in railway networks such as earthquakes (Janić, 2018), hurricanes (Chan & Schofer, 2016;Mudigonda et al., 2019;Zhu et al., 2016, snowand rainfalls (Chan & Schofer, 2016;Chen & Wang, 2019;Diab & Shalaby, 2019) and climate change events like sea-level rise (Dawson et al., 2016) and heat-related failures (Ferranti et al., 2016). Studies often estimate temporal and spatial distribution of disruptions (Chen & Wang, 2019;Ferranti et al., 2016) and also the spatiotemporal variations of system recovery behaviour (Zhu et al., 2016. ...
... So far, researchers mostly focused on scenario-specific studies and looked into weatherrelated disruptions and disasters in railway networks such as earthquakes (Janić, 2018), hurricanes (Chan & Schofer, 2016;Mudigonda et al., 2019;Zhu et al., 2016, snowand rainfalls (Chan & Schofer, 2016;Chen & Wang, 2019;Diab & Shalaby, 2019) and climate change events like sea-level rise (Dawson et al., 2016) and heat-related failures (Ferranti et al., 2016). Studies often estimate temporal and spatial distribution of disruptions (Chen & Wang, 2019;Ferranti et al., 2016) and also the spatiotemporal variations of system recovery behaviour (Zhu et al., 2016. ...
Article
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Critical infrastructure networks, such as transport and power networks, are essential for the functioning of a society and economy. The rising transport demand increases the congestion in railway networks and thus they become more interdependent and more complex to operate. Also, an increasing number of disruptions due to system failures as well as climate changes can be expected in the future. As a consequence, many trains are cancelled and excessively delayed, and thus, many passengers are not reaching their destinations which compromises customers need for mobility. Currently, there is a rising need to quantify impacts of disruptions and the evolution of system performance. This review paper aims to set-up a field-specific definition of resilience in railway transport and gives a comprehensive, up-to-date review of railway resilience papers. The focus is on quantitative approaches. The review analyses peer-reviewed papers in Web of Science and Scopus from January 2008 to August 2019. The results show a steady increase of the number of published papers in recent years. The review classifies resilience metrics and approaches. It has been recognised that system-based metrics tend to better capture effects on transport services and transport demand. Also, mathematical optimization shows a great potential to assess and improve resilience of railway systems. Alternatively, data-driven approaches could be potentially used for detailed ex-post analysis of past disruptions. Finally, several rising future scientific topics are identified, spanning from learning from historical data, to considering interdependent critical systems and community resilience. Practitioners can also benefit from the review to understand a common terminology, recognise possible applications for assessing and designing resilient railway transport systems.
... Without making a precise definition of a developing country, we note that most references focused on developed countries in North America and Europe. The four case study references outside these areas are studies on: tourism in Caribbean island states (Pentelow and Scott, 2011), the impact of weather at New Delhi airport (Jenamani et al., 2009), the exposure of Chinese infrastructure to flooding and drought (Hu et al., 2016) and the weather vulnerability of aviation and High Speed Rail in China (Chen and Wang, 2019). ...
... As reported within the sample publications, the adaptation concept for aviation can be categorised into three elements. Firstly, air travel faces climate change disruptions at airports due to greater and more frequent temperature extremes and changes in precipitation and wind, as well as rising sea levels (Burbidge, 2018;Chen and Wang, 2019;Yair, 2018). Secondly, disruptions occur in the air due to changing atmospheric patterns and less predictable extreme weather events (Cooper et al., 2018;Lee et al., 2019;Storer et al., 2019b). ...
... The European study found that HSR is expected to be less affected by climate change and recommends a modal shift on routes where airlines currently compete with HSR, under a collaborative approach between air and rail (Prussi and Lonza, 2018). In contrast, the Chinese study (Chen and Wang, 2019) found that aviation and HSR are both affected by climate change, but in different ways, so interruptions might not appear simultaneously. Therefore, the study recommends that when one travel mode is interrupted, a modal shift should be made easier for passengers to switch their transport options. ...
Article
While the aviation sector has long been referenced as contributing to the causes of climate change, the need for aviation to adapt to the consequences of climate change has not been as well researched or considered. The paper is a systematic quantitative literature review on climate change and aviation, which aims to explicate significant issues affecting aviation in a changing climate and to identify the aviation industry responses on climate change and adaptation. There are 46 references involved in the detailed assessment, selected according to variables such as methodology, paper outcomes and industry stakeholder. This emergent aviation and climate change adaptation literature could be broadened to cover more disciplines and approaches, an increased range of aviation stakeholders and go further beyond the larger airport case studies in developed countries. Further practical and policy developments are needed, particularly surrounding adaptation planning in aviation and the social justice implications of associated policies.
... The relationship between HSR and civil aviation has been extensively studied [9][10][11][12][13][14][15]. For example, HSR has an advantage over aviation in short-haul travel [11]. ...
... Modal substitution as an essential resilience strategy could make transportation more adaptive during disruptive events, such as terrorist attacks [10]. In addition, some studies have examined complementary or alternative relationships of HSR and aviation during extreme weather [12,15]. Furthermore, effective transportation planning can be helpful for sustainable supply chain performance [16]. ...
... In the case of China, with strong and continuous support from the central government, it developed a national HSR system with more than 38,000 km by the end of 2020. The development of HSR has substantially improved the intercity travel experience on account of the improved onboard amenity and travel time savings; the system has been extensively utilized since its operation [12,25]. For instance, HSR now serves more than 60% of all rail passengers in China [26]. ...
Article
Full-text available
Intercity transportation systems have experienced severe disruptions since the outbreak of COVID-19. However, it remains unclear how the operations of different systems were affected and whether the pandemic has influenced modal interaction. This paper provides an empirical assessment to address these questions using high-speed rail (HSR) and aviation in China as an example. The impact of COVID-19 on aviation and HSR operations was examined both temporally and spatially using a high-dimensional fixed-effect panel model. Using the big data with daily operational frequency for the period of January–June 2020, the study shows that the lockdown of Wuhan had varying effects on the operations of HSR and aviation. In addition, the correlation of operational services between HSR and aviation was found to vary both spatially and temporally during the pandemic. These research findings provide important implications for improving the adaptability of transportation systems and operational resilience.
... The regional dummy variables were introduced to control for the effect of different regional environmental characteristics on airport resilience performance. These variables were selected based on Chen and Wang (2019), which revealed that the on-time performance (OTP) of HSR and aviation operation in China were often dissimilar spatially due to the influences of the heterogeneous characteristics in different regions. Hence, it is worthwhile investigating whether airport resilience performance tends to be spatially different in China. ...
... In addition, the empirical evaluation of such a topic is particularly relevant for countries, such as China, where massive HSR network systems have been developed, which creates fierce competition for the aviation system (Chen, 2017). Since HSR was found to be less vulnerable than aviation under most severe weather events (Chen and Wang, 2019), it is valuable to examine whether the quality of rail service has any influence on the resilience performance of airports under severe weather events. ...
... Second, given that the performance of HSR is less sensitive to the weather events at mild and medium level of severity than that of the aviation system (Chen and Wang, 2019), it is reasonable to believe that travelers are generally more willing to switch to a highspeed train for a short and medium-haul trip if the air service is disrupted. Therefore, it is possible that air passengers are more Source: Authors' summary. ...
Article
The increased severe weather events in recent years as a result of global climate change has created a substantial challenge for aviation system operation. Although transportation engineers and planners have attempted to improve system resilience through the adaptation of new technologies and the implementation of various strategies to achieve effective risk management, it remains unclear how resilience performance (measured by the speed of recovery) of airports varies in different severe weather events and what factors may explain such variations. This paper addresses these fundamental questions using the aviation system in China as an example. A resilience metric, which reflects the speed of recovery (bounce back) from a shock, was developed to measure the performance of airport resilience under various severe weather conditions. In addition, an empirical econometric analysis was conducted based on a dataset that includes both detailed aviation performance and weather conditions for the period of October 2016 – September 2017. The research findings show that airport resilience to severe weather events does vary substantially based on factors, such as weather conditions, airport capacity, and the level of modal substitution. In particular, the recovery time of air services in central and south China tends to be relatively longer in thunderstorms than other weather conditions. The study also confirms that modal substitution is a very effective resilience tactic of the transportation system as the recovery speed of air service was found to be faster by 22.9% if an alternative mode, such as high-speed rail (HSR) service was also available in the city.
... Moreover, in order to give values to the environmental feedback parameter, two studies for increased costs related to climate change were considered (Kreuz & Nokkala, 2013;Chen & Wang, 2019). According to these, the increase in extreme climate events will not only increase the maintenance costs but also the management costs. ...
... The question whether any one of the specific measures, among those proposed for the reduction of air traffic emissions seems to be crucial (Ackerman, 2005;Macintosh & Wallace, 2009;Chen & Wang, 2019). Recently, CH2013 have investigated this issue, using a sophisticated statistical model. ...
... It was modeled here as consisting of two contributions. The first one accounts for the effect of the increased flight costs as a consequence of the increase in fuel and airport taxes (as a consequence of climate change) (Kreuz & Nokkala, 2013;Chen & Wang, 2019). The second part in the cancelation effect is due to the 'environmental consciousness' of the passengers. ...
Article
Greenhouse gases emissions modify the radiative balance of the Earth, causing changes in its climate. Climate Change is considered one of the greatest threats to economic and social stability. Aviation is responsible for around a 2.5% of greenhouse gases emissions. This contribution is steadily increasing, thus the interest of assessing the impacts that different policies might have on it. The simple feedback model proposed here was intended as a tool in order to investigate the stabilization issue. The model was based on the relationship between the number of air traffic passengers and the associated CO2 emissions. It incorporated a representation of the feedback of the technological innovation on the emissions rate and of those of the socioeconomic response to the climatic impact on the passengers number. The model parameters were estimated using data from a variety of robust air traffic sources. However, it was found that neither of the feedback terms succeeded at stabilizing the emissions, although they might slow down their growth. In addition, there is also a nonlinear version of the model that includes a representation of the passengers perception of insecurity, similar to the one experienced in the current pandemic. This model favors the stability of both, the number of passengers and CO2 emissions, as it would also be able to control unprecedented situations.
... To date, the individual characteristics [1][2][3][4], accessibility to transportation hubs [3][4][5][6][7][8], travel demand characteristics [2,9], and travel mode characteristics [1,2,4,5,9] were found to have significant impacts on the intercity travel mode choice. Although some studies have explored the effect of weather on passengers' traffic mode choice in cities [10][11][12][13][14] and a few scholars have focused on the possible effects of weather characteristics on intercity transportation in the Netherlands, USA, and Spain [12,13,[15][16][17]; the impact of weather on travelers' intercity mode choices has been ignored, especially in the case of Chinese cities. ...
... Previous studies have revealed the impact of weather conditions on the choice of urban transportation modes, including the season [10][11][12]18], humidity [10][11][12][13][14][15], temperature [11][12][13][14][15][16][17], wind speed [10,[13][14][15][16][17], snow [10,11,16,17], fog [10,16], rain [15][16][17], the air quality index (AQI) [14], and extreme weather [18,19]. For example, Böcker et al. [12] found car use seemed to be less attractive in spring, and travel by walking and cycling was less common in winter than in spring during 2004-2009 in the Randstad Holland. ...
... Previous studies have revealed the impact of weather conditions on the choice of urban transportation modes, including the season [10][11][12]18], humidity [10][11][12][13][14][15], temperature [11][12][13][14][15][16][17], wind speed [10,[13][14][15][16][17], snow [10,11,16,17], fog [10,16], rain [15][16][17], the air quality index (AQI) [14], and extreme weather [18,19]. For example, Böcker et al. [12] found car use seemed to be less attractive in spring, and travel by walking and cycling was less common in winter than in spring during 2004-2009 in the Randstad Holland. ...
Article
Full-text available
To explore the influence of weather conditions on the choice of the intercity travel mode of travelers, four modes of traveler transportation were studied in Xi'an, China, in March 2019: airplane, high-speed rail, conventional train, and express bus. The individual characteristics of travelers and intercity travel activity data were obtained, and they were matched with the weather characteristics at the departure time of the travelers. The Bayesian multinomial logit regression was employed to explore the relationship between the travel mode choice and weather characteristics. The results showed that temperature, relative humidity, rainfall, wind, air quality index, and visibility had significant effects on the travel mode selection of travelers, and the addition of these variables could improve the model's predictive performance. The research results can provide a scientific decision basis for traveler flow transfer and the prediction of traffic modes choice due to the effects of climate change.
... The urban built environment is facing an increasing number of various disruptions, ranging from natural hazards and disasters such as earthquakes, extreme weather events [1], and rising sea levels in coastal cities, to man-made stresses and deliberate vandalisms such as severe congestion and terrorist attacks [2]. For the year 2020, we all have witnessed that the on-going global COVID-19 crisis can profoundly impact the way people travel and how cities are running [3]. ...
... Last but not the least, we also acknowledge the following limitations in this study: (1) The design of the disruption-recovery scenarios can be expanded by incorporating more detailed and practical factors. For example, the system resilience under cascading failures of the platforms with different failure and recovery rates can be further explored; (2) Due to the issue of data availability, this study is a theoretically numerical investigation, which might need to be further compared with empirical data. ...
Article
This paper studies the resilient performance of urban rail transit systems by extending a linear programming optimization model, which can provide optimized commuter flows with contingency routing under multiple disruptions. The rail transit systems in Singapore and Chongqing (China) are selected as case studies, and the system resilience and the effectiveness of providing bus-bridging services are comparatively studied. Intuitively, failures of the interchange stations would inevitably lead to a significant loss of resilience due to deteriorated network connectivity. However, the Singapore case shows that attacking those interchange stations does not always result in an extensive resilience loss. Comparing with the Chongqing case, it is discernible that the position of interchange stations would affect the system resilience. The numerical simulations reveal that the positive effect of providing bus-bridging strategy, in terms of improving the system resilience, is heterogeneous in different systems, which varies from 14% to 30% on average. As demonstrated in the sensitivity on travel demands, this positive effect is robust, yet dynamic, indicating that there is no one-size-fits-all solution for designing transfer-based recovery strategies in disruption management of rail transit systems. The managerial implications for decision makers are also provided and discussed in terms of infrastructure planning.
... Air transport plays a key role in, among others, tourism, trade and the accessibility of regions. Disruptions within the air transport system therefore lead to substantial economic costs, affecting not only passenger travel but also supply chain performance (see, e.g., Wilson, 2007;Borsky and Unterberger, 2019;Chen and Wang, 2019). 1 Industrial action (i.e., strikes) by air traffic controllers are among the most frequent causes of air transport disruption in Europe. Over the 2004-2016 period, air traffic control strikes disrupted Europe's airspace on average once in every two weeks (Horton and Congdon, 2017). ...
... To the best of our knowledge, our study is the first to analyse the trajectory efficiency implications of air transport network disruptions. Our findings are complementary to existing studies on air transport disruption (e.g., Koetse and Rietveld, 2009;Janić, 2015;Borsky and Unterberger, 2019;Chen and Wang, 2019), as well as to an emerging literature on the (environmental) efficiency of flight trajectories and the role that air traffic control can play in reducing fuel consumption and CO 2 -emissions (e.g., Button and Neiva, 2013;Reynolds, 2014;Ryerson et al., 2014). Although we focus on disruptions caused by strikes, our methodology can be applied to analyse the efficiency losses due to different types of airspace disruptions including bad weather, natural disasters, understaffing, etc. ...
Article
When airspace sectors are disrupted airlines have the decision to either cancel, delay or reroute scheduled flights. The aim of this paper is to estimate the additional kilometres flown due to rerouted flights during air traffic control strikes. We use detailed flight-level data and information on over sixty strikes in European airspace between 2015 and 2017. We combine a difference-in-difference approach with statistical matching procedures to address that strikes do not occur randomly over time. Our estimates show that strikes significantly decrease the horizontal trajectory efficiency of operated flights, aggregating to 4.7 million additional aircraft kilometres over the sample period. This equals about 13.4 kilotonnes of additional fuel consumption and 42.2 kilotonnes of CO2-emissions. Further results suggest that these inefficiencies can be mitigated by measures that preserve continuity of service for overflights during disruptions.
... Transportation networks provide critical socio-economic services at local and regional scales. However, demographic and economic growth, rapid urbanization, increasing infrastructure interdependency, and natural hazards -due to the worsening effects of climate change -are putting physical transportation systems under increasing pressure (Chen & Wang, 2019;Schreider et al., 2000). This is particularly evident in urban areas where transport networks are especially vulnerable to weather-related hazards (Pregnolato, Ford, Glenis, et al., 2017;Singh et al., 2018;Yin et al., 2016). ...
Article
Full-text available
Transportation networks underpin socioeconomic development by enabling the movement of goods and people. However, little is known about how flooding disrupts transportation systems in urban areas in developing country cities, despite these natural disasters occurring frequently. This study documents the channels through which regular flooding in Kinshasa, the Democratic Republic of Congo, impacts transport services, commuters' ability to reach their jobs, and the associated economic opportunity costs from travel delays. This assessment is based on transit feed specification data sets collected specifically for this analysis under normal and flooded conditions. These data sets were combined with travel survey data containing travelers' socioeconomic attributes and trip parameters, as well as high-resolution flood maps. The results show that (1) flood disruptions cause increases in public transit headways and transit re-routing, decreases in travel speeds, and thus travel time delays, which translate into substantial economic costs to local commuters; (2) accessibility to jobs decreases under flooded conditions, hindering the establishment of an integrated citywide labor market; (3) there are spatial clusters where some of the poorest commuters experience among the highest travel delays, highlighting socio-spatial equity aspects of floods; (4) certain road segments are critical for the transport network and should be prioritized for resilience measures; and (5) the estimated daily cost of flood disruption to commuters’ trips in Kinshasa is $1,166,000. The findings of this assessment provide disaster mitigation guidance to the Office des Voiries et Drainage under the Ministry of Infrastructure, as well as strategic investment recommendations to the Ministry of Housing and Planning.
... Canada and VIA Rail have an airline-rail re-protection agreement, which is an emergency backup service for airline cancelations, providing train tickets in lieu of flights to get passengers to their destination (Jiang et al., 2017;Li et al., 2018). Some studies have compared and evaluated the vulnerability of HSR and air transport (Li et al., 2019;Chen and Wang, 2019) and the influence of HSR lines on the demand, price, and supply of air transport (Fu et al., 2012;Jiang and Zhang, 2014;Wan et al., 2016;Zhang et al., 2018Zhang et al., , 2019Wang et al., 2020). However, little attention has been paid to the vulnerability of HSR and air transport from both spatially-and temporally-variant perspectives and the impacts of HSR on the vulnerability of the aviation service network. ...
Preprint
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Most studies on the robustness of high-speed rail (HSR) network examine the issue at the aggregate level and consider a fixed period (e.g., a day or a month), regardless of when and where the disruption occurs. This study proposes a holistic framework of assessing the impact of node cascading disruptions in HSR network considering different affected times-of-day and geographic regions. A weighted network efficiency metric is proposed to assess network performance considering both travel time and train frequency along the topological shortest path. Analysis of China's HSR finds that 1) the network is less robust to disruptions occurring in East China or along the Harbin-Hong Kong corridor; 2) Disruptions during 10:00-15:00 have the largest impact; 3) lockdowns during COVID-19 outbreak in Jan-Feb 2020 led to 14.5% reduction in overall network efficiency. The results generate insights into further development of the HSR network and provide policy support for HSR resilience-enhancing strategies.
... For example, Air Canada and VIA Rail have an airline-rail re-protection agreement, which is an emergency backup service for airline cancelations, providing train tickets in lieu of flights to get passengers to their destination (Jiang et al., 2017;Li et al., 2018). Some studies have compared and evaluated the vulnerability of HSR and air transport (Li et al., 2019;Chen and Wang, 2019) and the influence of HSR lines on the demand, price, and supply of air transport (Fu et al., 2012;Jiang and Zhang, 2014;Wan et al., 2016;Zhang et al., 2018Zhang et al., , 2019Wang et al., 2020). However, little attention has been paid to the vulnerability of HSR and air transport from both spatially-and temporally-variant perspectives and the impacts of HSR on the vulnerability of the aviation service network. ...
Article
Full-text available
Most studies on the robustness of high-speed rail (HSR) network examine the issue at the aggregate level and consider a fixed period (e.g., a day or a month), regardless of when and where the disruption occurs. This study proposes a holistic framework of assessing the impact of node cascading disruptions in HSR network considering different affected times-of-day and geographic regions. A weighted network efficiency metric is proposed to assess network performance considering both travel time and train frequency along the topological shortest path. Analysis of China’s HSR finds that (1) the network is less robust to disruptions occurring in East China or along the Harbin-Hong Kong corridor; (2) Disruptions during 10:00–15:00 have the largest impact; (3) lockdowns during COVID-19 outbreak in Jan-Feb 2020 led to 14.5% reduction in overall network efficiency. The results generate insights into further development of the HSR network and provide policy support for HSR resilience-enhancing strategies.
... HSR has become an important choice in inter-city transportation. Based on HSR, air flight, and weather data from 2016 to 2017 in China, Chen and Wang [45] found HSR was more reliable than air flight when facing severe weather conditions. Chen [46] pointed out that HSR had partly replaced some air flights in inter-city trips, especially within the distance from 500 to 800 km. ...
Article
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This paper aims to fill the research gap of the relationship between the access travel time (ATT) estimation and the accessibility to high speed railway (HSR) station. A regression analysis was developed on the basis of risk-return model to analyze the access travel time estimation error (ATTEE). The data sources were 1595 valid interview survey data at Beijing South Railway Station (BSRS), China in October 2016. The factors and scenarios included travel mode, departure time, and travel date, etc. The coefficients of ATT estimation were obtained by different travel modes. The results showed that the expected access travel time (EATT) has positive linear correlation with the actual access travel time (AATT). Accessibility was calculated by the ratio of AATT to EATT. The accessibility coefficients ranged from 0.89 to 1.38 in different travel modes, departure time, and travel dates. A smaller coefficient indicates better travel time reliability and accessibility. This study not only provides a useful tool to estimate the travel time budget required for access to HSR station, but also establishes a connection with the accessibility and ATTEE. It offers an opportunity to estimate ATT to HSR stations by different modes of transport, which can help to better understand how the accessibility of the feeder transport changes at different time periods.
... Transportation networks provide critical socio-economic services at local and regional scales. However, demographic and economic growth, urbanization, increasing infrastructure interdependency, and natural hazardsnot least due to the worsening effects of climate changeare putting physical transportation systems under increasing pressure (Chen & Wang, 2019;Schreider et al., 2000). This is particularly evident in urban areas where transport networks are especially concentrated and vulnerable to weather-related hazards (Pregnolato et al., 2017a;Singh et al., 2018;Yin et al., 2016). ...
Article
Full-text available
Transportation networks underpin socioeconomic development by enabling the movement of goods and people. However, despite their frequency, little is known about how floods disrupt transportation systems in developing country cities. We collect an innovative dual-condition transit feed specification dataset, and combine it with a travel survey and high-resolution flood maps to examine how regular floods in Kinshasa impact transport services, job accessibility, and the associated economic opportunity costs from travel delays. Our results show that flood disruptions cause increases in public transit headways, transit rerouting, decreases in travel speeds, which translate into travel delays and loss of job accessibility. This induces substantial economic costs to local commuters – about $1.2 million daily – and hinders the establishment of an integrated citywide labor market. In addition, we reveal sizeable socio-spatial heterogeneities, with clusters of low-income residents incurring a large share of the travel delays and identify critical network segments that should be prioritized for resilience interventions.
... In recent years, some prior studies focus on discussing the influence of HSR to the economy and society, such as the regional economy (Dong, 2018;Bracaglia et al., 2020;Guirao et al., 2020), the aviation industry (Chen and Wang, 2019;Li et al., 2019;Wang et al., 2019b), the road and maritime transport (Calatayud et al., 2017;Aydin et al., 2018;Amin et al., 2019), the traveling time (Albalate & Fageda, 2016), and so on. Moreover, a growing number of studies explore the effect of transportation on innovation (de la Tour et al., 2011;Dong, 2018). ...
Article
As a critical infrastructure, the development of high-speed rail (HSR) inevitably exerts a marked impact on economic growth and sets the stage for different industrial revolutions. In this study, we set out an estimation framework designed to explore whether the spatial-temporal compression effect of HSR has paved the way for the Fourth Industrial Revolution characterized by urban technological innovation and whether HSR has strengthened the technology spillovers from venture capital (VC). The principal findings are as follows: First, the opening of HSR can strengthen urban technological performance, and compared with non-HSR cities, the number of patent applications is higher in HSR cities. Second, considering the heterogeneity of technological innovation, and the results show that the opening of HSR can significantly promote the breakthrough innovation and incremental innovation of cities, and has a more significant impact on the breakthrough innovation. Finally, VC has a highly significant and positive effect on urban technological performance. More notably, our findings suggest that the opening of HSR has a considerable shock effect on the technology spillovers from VC. This study has great practical significance for analyzing the impact of HSR on the transformation of the Fourth Industrial Revolution characterized by urban technological performance.
... The train can automatically depart, operate between stations and adjust its operation status to meet the precise timetable without human drivers. However, the increasing frequency and intensity of extreme weather events will bring new challenges to the operation and control of HSR [55]. Further research is needed to evaluate the impacts of weather conditions on the train operation and punctuality of the HSR system under different probabilities of unexpected events. ...
Article
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High-speed rail (HSR) has brought a number of social and economic benefits, such as shorter trip times for journeys of between one and five hours; safety, security, comfort and on-time commuting for passengers; energy saving and environmental protection; job creation; and encouraging sustainable use of renewable energy and land. The recent development in HSR has seen the pervasive applications of artificial intelligence (AI). This paper first briefly reviews the related disciplines in HSR where AI may play an important role, such as civil engineering, mechanical engineering, electrical engineering and signalling and control. Then, an overview of current AI techniques is presented in the context of smart planning, intelligent control and intelligent maintenance of HSR systems. Finally, a framework of future HSR systems where AI is expected to play a key role is provided.
... For example, Tsionas et al. (2017) suggest that Chinese airlines' OTP is positively correlated to airline technical efficiency. A recent study by Chen and Wang (2019) examines how OTP of airlines and high-speed rail (HSR) in China are differently affected by extreme weather events. They find Chinese airlines are more vulnerable to severe weather events than HSR. ...
Article
Delay propagation is the flight departure delay caused by the arrival delay of pre-segment flight. Chinese airline market has suffered very poor on-time performance (OTP) in recent years. It is, however, unclear whether delay propagation prevails as one major source for such problem. This study first aims to empirically quantify delay propagation in the Chinese airline market. Specifically, we shed light on heterogenous levels of delay propagations across different airports and airlines. Then, the distinct delay propagation patterns in China are also discussed and compared with other developed airline markets (e.g., the US and Europe). Our estimation is based on OTP data for over 12 million Chinese flights covering the 2015–2017 period. Specifically, it is found that 10 min arrival delay of pre-segment flight within 1 hr before the departure lead to an average of 7.49 mins delay propagation for subsequent departure flight. Arrival delay of earlier pre-segments (1–2 and 2–3 hr before the departure) leads to much less delay propagation, due to longer ground buffer. Chinese airlines arrange longer ground and flight buffer than that of the US airlines to prevent the delay propagation from accumulating along the subsequent flights in a day. Thus, unlike the US market, delay propagation is not the major reason for poor OTP in China. In addition, delay propagation is less prevailing at the Chinese hub airport. This is because China has relied on point-to-point network, which does not require sophisticated schedule coordination. And the local passengers at these Chinese hub airports have higher time value such that the Chinese airlines also try to improve OTP at these hub airports to better serve these lucrative but time-sensitive local passengers. Unlike the European LCCs, Spring Airlines, the largest low-cost carrier (LCC) in China, outperforms major full-service carriers (FSCs) in controlling delay propagation. This finding may also apply to other Northeast Asian LCCs sharing common operational characteristics as Spring Airlines. Last, we find that airlines purposely tolerate moderate departure delays of up to 15 min, which is the threshold that defines delays, no matter whether the pre-segment flight arrives late or on-time. The relevant policy and managerial implications are also discussed.
... Extreme weather events interrupt the operations of the UAM system and cause massive economic losses. Highintensity rainfall, hurricane, heavy snow and fog, and strong wind events lead to the suggestion of canceling or delaying the operations of UAM under safety issues [6][7][8]. Aviation studies face the challenge of incorporating more than 20 weather factors into evaluating aircraft flying conditions and suffer from the incapability of deciding the extreme weather events without a unified evaluation system [9]. This study presents a quantification system of weather conditions to unify the impact among all factors at once. ...
Conference Paper
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View Video Presentation: https://doi.org/10.2514/6.2022-4081.vid Local weather patterns can pose a significant barrier to the feasibility of realizing advanced air mobility systems in urban areas. Changes in the local climate conditions can significantly affect future urban air mobility viability, possibly restricting operations even further. This study aims to assess the impacts of changing climate conditions on a hypothetical urban air mobility network in Chicago to determine the network's sensitivity to changes in climate. The proposed data-driven approach identifies the extreme weather days for Urban Air Mobility operations from the 2006 to 2020 NOAA Integrated Surface Database. We further assess the sensitivity by increasing the rate of extreme weather events and calculating the impact of these changes on the Chicago metropolitan area. Via this analysis, we found that an increase in extreme weather days from 5% to 10% frequency reduced the percentage of viable UAM trips from 62% to 48% in winter.
... However, the authors argued that the impact of HSR frequency on airfare is much weaker than the impact of HSR travel time. HSR services are more punctual than airline services and are less likely to be affected by bad weather conditions (see also Chen and Wang, 2018). Zhang et al. (2014) used the Lerner index to measure the market power of Chinese airlines and found that HSR is one of the most important determinants of airline market power. ...
Article
This paper first reviews studies on the impacts of air-HSR competition on airlines, focusing on the overall effects of parallel HSR services on passengers' mode choice as well as on airlines’ flight frequency, traffic volume, fares, service quality and market power. The modal complementarity and air-HSR intermodal services, together with the network feature of airline business, are also examined. The paper then reviews theoretical and empirical findings on the impacts of HSR on airports and regional economies. Here, the main insights include: First, HSR can have a traffic redistribution effect on airport traffic; in particular, some primary hub airports with good air connectivity may gain traffic while others may lose traffic. Second, to mitigate congestion at hub airports, policy makers may consider diverting some traffic to regional airports by promoting air-HSR intermodal services. Third, as HSR may stimulate long-haul/international air traffic, its overall impact on emission reduction remains unclear. Finally, similar to the impacts on airport traffic, spatial disparity of economic activities may also rise after the introduction of HSR. In general, the disparity tends to rise between the cities with HSR and those without HSR, as the former gets better accessibility. However, among the cities with HSR services, the disparity between the large and small cities could increase or decrease depending on several factors.
... An ATS consists of several sub-systems, including airlines, air traffic control units, airports, contributing to the multilayer structure of the air transport network (ATN) [9]. Recently, with the rapid development of high-speed rail, the combined effects of multiple transport modes have attracted attention from both industry and academia [10]. A complex network offers a relatively simple but informative approach by modeling the system's components as nodes and interactions between components as links. ...
Conference Paper
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Incorporating resilience into the airline's network planning and assessment prepares the airline for disruptive events. To measure and improve the resilience of an airline's network, quantitative or qualitative metrics are required. In this work, we first propose a novel modeling approach by the leverage of temporal network theory to analyze the resilience of an airline's operation network. A two-layer network is generated from an airline's scheduling data and operation data using the proposed approach. By taking interactions of the network's components and time-attributed information into consideration, the instantaneous network efficiency is defined to measure the performance of the network. We then develop a new resilience metric, average efficiency loss ratio (AELR), for airline's operation network based on the instantaneous network efficiency. The proposed approach and metric are applied to four major U.S. airlines' networks, including AA, UA, DL and WN using a publicly accessible dataset. Results show that Delta airlines has the highest resilience, but is more susceptible to severe flight delay and cancellation. The flight delay and cancellation effects on Southwest and American airlines operation network are similar. Our work may open an avenue for managing the resilience of airline's networks.
... The function can make predictions on new data, based on changes in the variables that "explain" the spread in the data. [23,24,32,35,40,42,44,55,60,[63][64][65][66]68,[72][73][74][75][76][77] Simulations ...
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Countries considering high-speed rail (HSR) developments face enormous challenges because of their high deployment cost, environmental obstacles, political opposition, and their potentially adverse effects on society. Nevertheless, HSR services are importantly sustainable that can have positive and transformative effects on the economic growth of a nation. This paper systematically reviews and classifies impact areas of HSR deployments around the world as well as the analytical methods used to evaluate those impacts. We have utilized the scholarly scientific database to find articles in HSR systems. By defining some rules, we select 116 articles between 1997 and March 2020. The approach revealed interesting patterns and trends in space, time, and sentiment of the analyzed impacts on society, the economy, and the environment. The findings can inform decision-making about HSR developments and deployments, and the gaps identified in the literature can propose new research opportunities for future studies.
... Human-made structures and development may alter the paths, depths, and velocities of flood flow, and add debris to floodwaters, so humanmade development can exacerbate the magnitude of the damage [22]. Transport infrastructure has become much more vulnerable to unexpected severe weather events caused by the effects of climate change such as cyclones, storms, and floods [23][24][25]. ...
Article
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Most of the previous research has tended to focus on the impact of flood characteristics on built infrastructure damage rather than to investigate the condition of the infrastructure and stakeholders’ capacity to manage flood risks. The role of stakeholder attributes, such as the power, legitimacy, and urgency of local governments, in reducing the impact of disasters on built infrastructure remains ambiguous. Stakeholders’ organizational attributes, together with socio-economic and built infrastructure conditions, need to be considered to provide a better understanding of how to reduce disaster risk. The main aim of this research was to empirically investigate the mediating role of socio-economic and infrastructure conditions in the direct relationship between stakeholders’ attributes and economic damage to road infrastructure from flooding. Survey data collected from local governments in New South Wales, Australia and historical data for over 20 years from archive databases were analyzed using structural equation modeling with the partial least squares estimation approach. The results showed that socio-economic and infrastructure conditions have significant mediating effects on the direct relationship between stakeholders’ attributes and flood damage. Engaging stakeholders proactively empowers legitimate stakeholders in urgent conditions, and this is essential to reduce the economic impact of flood disasters and to better manage road infrastructure. Finally, to better manage flood risks, local governments need to improve their capacity of power, legitimacy, and urgency; state and federal governments need to improve the socio-economic conditions of the communities; and the transport infrastructure authorities need to develop long-term solutions for resilient roads and bridges.
Chapter
The aviation industry remains on the global radar regarding its contribution to greenhouse gas (GHG) emissions that lead to global warming and ultimately climate change. With the world agreeing on the 2030 Agenda for Sustainable Development (AfSD) that embeds 17 sustainable development goals (SDGs), it is inevitable that research is being done to determine how this sector is responding to the SDGs, especially aircraft manufacturing companies. Most, if not all, of the 17 SDGs challenge the aviation industry to do something to ensure sustainable development. This chapter applies critical document analysis in tracing how aircraft manufacturers are embracing SDGs. The findings are that two companies, namely, Airbus and Boeing, have localised at least 10 of the 17 SDGs including SDGs 4, 5, 9, 12, 13 and 17. The study shows that the industry can still do more to add to current success stories given their resource capacity. The work recommends a streamlining of the reporting system on SDGs to allow internal and external monitoring, reporting and verification now and for future initiatives.
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A number of recent disasters have challenged the functionality of transport networks. The significance of road transport infrastructure to the functioning means that systems need to be able to operate under undesirable conditions, and quickly return to acceptable levels of service. The objective of the study is to analyze real-world networks speed fluctuation and evaluate the quantitative relationship between resilience and graph-based metrics, and link attributes using crowd-sourced data. We measure resilience in terms of the rate (vehicle speed) at which the road network recovers from a disruptive event and define five metrics to quantify network resilience. We analyze more than 500 links affected by disruptions in multiple cities with more than millions of crowd-sourced data. Using changes in link speed before, during, and after the disruption, the resilience metrics are applied to three case studies that are categorized as no-notice disruption, notice disruption, and disruption caused by continuous events. The results indicate that link graph-based metrics and attributes have a high impact on network resilience. However, the relevance of different metrics and attributes to the link resilience is different. Population density, predictability of disasters, and human factors have a significant impact on the reduction and recovery phases.
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The installation of high-speed rail in the world during the last two decades resulted in significant socioeconomic and environmental changes. The U.S. has the longest rail network in the world, but the focus is on carrying a wide variety of loads including coal, farm crops, industrial products, commercial goods, and miscellaneous mixed shipments. Freight and passenger services in the U.S. dates to 1970, with both carried out by private railway companies. Railways were the main means of transport between cities from the late 19th century through the middle of the 20th century. However, rapid growth in production and improvements in technologies changed those dynamics. The fierce competition for comfortability and pleasantness in passenger travel and the proliferation of aviation services in the U.S. channeled federal and state budgets towards motor vehicle infrastructure, which brought demand for railroads to a halt in the 1950s. Presently, the U.S. has no high-speed trains, aside from sections of Amtrak s Acela line in the Northeast Corridor that can reach 150 mph for only 34 miles of its 457-mile span. The average speed between New York and Boston is about 65 mph. On the other hand, China has the world s fastest and largest high-speed rail network, with more than 19,000 miles, of which the vast majority was built in the past decade. Japan s bullet trains can reach nearly 200 miles per hour and dates to the 1960s. That system moved more than 9 billion people without a single passenger casualty. In this systematic review, we studied the effect of High-Speed Rail (HSR) on the U.S. and other countries including France, Japan, Germany, Italy, and China in terms of energy consumption, land use, economic development, travel behavior, time use, human health, and quality of life.
Article
High-speed rail (HSR), as an efficient and environmentally sustainable mode of transportation mode, has received increasing attention in many countries over the past decades. While the literature on HSR's technology development and the assessment of the socioeconomic impact of the system has increased substantially in recent years, it remains unclear how the understanding of the socioeconomic impact system has evolved, and what the characteristics of various research focuses are. The objective of this study is to provide a comprehensive examination of the evolution of the high-speed rail literature, with a focus on socioeconomic impact analysis. Specifically, the following research questions are addressed: what is the global trend of scientific publication on the socioeconomic impact analysis of HSR? What specific focuses are uncovered from this trend? And what are the future directions of research in this field? A thorough understanding of the literature helps scholars better identify the research gaps, needs and directions for future research endeavors. In addition, it may also facilitate the decision-making for future investment in HSR through a better understanding of the potential impacts of the system.
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The chapter talks about the challenges & way forward in developing capacity among Indian construction workforce in the context of handling megaprojects such as High-Speed Rail.
Article
The existing literature has confirmed that extreme weather such as wind, rain, and snow have a negative impact on cross-sectional traffic flow. However, travel activities with different destination regions, travel distances and vehicle types may have different responses to severe weather. We employ the multilevel mixed-effects negative binomial (MENB) model to explore the interaction effect of severe weather and non-weather factors on intercity origin-destination (OD) demand, based on the data from freeway toll stations in Shandong Province from March 2011 to February 2012. The MENB model is superior to the SNB model in that the former has both smaller AIC (456,645.4 < 4,586,877.2) and BIC (456,963.4 < 458,975.8) values and log-likelihood ratio tests. The results indicate that weather impact on freeway travel to the same metropolitan area is homogeneous, and the impact in different metropolitan areas is heterogeneous. Besides, there is an interaction effect between severe weather (strong wind, fog, heavy rain, snow) and travel distance on freeway OD volume. With increasing travel distance, the impact of both strong wind and heavy rain decreases gradually, while the impact of both fog and snow increases. In addition, heat (0.0351 > 0.0201), strong wind (0.0930 > 0.0454), and heavy rain (0.1245 > 0.1044) have a greater impact on passenger car volume than on truck volume, while fog (0.4340 < 0.4802) and snow (0.4383 < 0.4884) have a less significant impact on passenger car volume. The findings of this study provide some deep insights into the relationship between severe weather factors and intercity travel demand, which suggests that different strategies of travel demand management should be adopted for different travel distances and different vehicle types under various weather conditions.
Article
Although previous studies explored the relationship between high-speed rail (HSR) and civil aviation, most of them focus on the negative effects of HSR on civil aviation, including the competition between them. However, studies exploring the positive effects of HSR on civil aviation remain limited. This study demonstrates that a high-speed rail network (HSRN) has a spatiotemporally complementary effect (CE) on the robustness of aviation networks (ANs) against different types of hazards. First, we describe the AN as a multiple weighted network with the CE of HSRN based on the operating routes of flights and trains, instead of an independent network. Then, a novel framework for assessing the robustness of AN is developed considering travel time and service frequency as its metrics and considering the coverage distance of the CE. We find that the CE can obviously reduce the loss of the AN’s performance under various disaster scenarios by analyzing the robustness of the AN of Mainland China complemented by HSRN; different levels of CE have different effects on the robustness of AN. Besides the airports located in Eastern China, some non-hub airports such as Changzhou, Wuxi, and Shaorao, are easily complemented by the HSRN. Further, the CE at different times exerts different effects on the robustness of AN, which reach a peak at 16:00 and 07:00. These findings can help broaden the ideas and approaches for enhancing the robustness of the AN.
Article
While researchers analyze the vulnerability of high-speed rail network (HSRN), they rarely consider its service feature. Notably, one of the key features of HSRN is offering passengers fast travel services. This study selects passenger flow and travel time to describe the service feature of HSRN, and constructs a multiple-weight HSRN. Then, service performance is taken as the indicator of HSRN’s vulnerability by innovatively integrating complex network theory and reliability theory. Using the daily operation data of China’s HSRN (CHSRN) merged with coordinate data and statistics data in November 2018, this study assesses its vulnerability under natural hazards and manmade accidents. Afterwards, the critical component and critical area within CHSRN are identified by the spatially localized failures (SLFs) model. Comparing with the results obtained by previous methods, this study finds that the vulnerability of CHSRN is always overestimated and several critical components are overlooked regardless of its service feature. Furthermore, we also find that the critical areas within CHSRN mostly lie in the Yangtze River Delta considering the service feature while they are scattered along Beijing-Guangzhou railway line or Beijing-Shanghai railway line ignoring the feature. These findings can help administrators develop different strategies to better prioritize the allocation of limited maintenance resources and mitigate the vulnerability of HSRN.
Article
Flight delays have become a widespread phenomenon in many parts of the world, especially in China. Few studies have investigated the effect of high flight delays on the competition between high-speed rail (HSR) and air transport (AT). A model based on the applied game theory is developed to obtain the optimal strategies of the two players in equilibrium. Results reveal that the revenue created by HSR and AT have gradually decreased as the flight delay rate increases. Moreover, if the flight delay rate exceeds 30%, the HSR operator will receive more revenue by implementing fare discounts strategies.
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Air traffic operations are significantly impacted by weather conditions. These external factors may impose operational constraints and generate demand-capacity imbalances, leading to reduced on-time performance, additional airline costs and inconveniences to passengers. Efficient management of such disruptions requires an understanding of the main causes of flight delays towards increasing their predictability. In this study, we investigate the impacts of airport surface weather conditions on the likelihood of flight delays for the Brazilian domestic air transportation system. We use historical flight schedule, on-time performance and weather data and estimate a logit model to analyze how different meteorological variables at the airport of destination affect the probability of a delayed arrival. We obtain empirical evidence for the impacts of low ceiling and visibility conditions, precipitation and wind gusts on the likelihood of arrival delays for the set of Brazilian airports analyzed.
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Weather conditions in the city of Mataram tend to be erratic and difficult to predict, such as the condition of rainfall data in 2018 which changes over a certain period of time so that the weather is difficult to predict accurately. In this study, we propose the Exponential Smoothing Holt-Winter method to forecast rainfall in the city of Mataram, so that it can be a decision support for various interested sectors. This method has been tested using secondary data from the Mataram City Central Bureau of Statistics for the period January 2014 to 2018 and evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results of this study indicate that using the Exponential Smoothing Holt-Winter method yields better results, each of which is MAPE 142.3, MAD 95.6 and MSD value 24988.7 and the data smoothing value is obtained for the smallest combination value of α 0.2, β 0.1, and γ 0.1. It can be concluded that the proposed method can provide better information and can be used to predict rainfall in Mataram City for the next 12 periods.
Article
This paper develops a theoretical framework containing the methodology for assessing resilience of the ATC (Air Traffic Control) sectors affected by the impact of a given disruptive event. The resilience is considered as ability of these sectors to retain a certain level of the regular/nominal performance during the impact and fully recover relatively fast afterwards. The actually rear disruptive event is considered to be the large-scale failure of a component of the ATC facilities and equipment supporting safe, efficient, and effective air traffic. Under such conditions, different mitigating contingency measures are generally applied resulting in deteriorating the operational, economic, and environmental performance of the affected sectors while maintaining the required level of safety. This performance is represented by the indicators such as demand, capacity, traffic complexity, the ATC controller workload, aircraft/flight delays and their costs, and additional fuel consumption and related emissions of GHG (Green House Gases). The proposed methodology consists of the generic model of resilience, the analytical models for estimating the indictors of ATC sectors’ performance, and the analytical models of resilience based the indicators as figures-of-merit for assessing resilience. These models are based on the practice-close mitigating contingency measures applied to the ATC sectors affected by a given disruptive event. The possible application of the proposed methodology is also elaborated.
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The hygroscopic property of particulate matter (PM) influencing light scattering and absorption is vital for determining visibility and accurate sensing of PM using a low-cost sensor. In this study, we examined the hygroscopic properties of coarse PM (CPM) and fine PM (FPM; PM2.5) and the effects of their interactions with weather factors on visibility. A censored regression model was built to investigate the relationships between CPM and PM2.5 concentrations and weather observations. Based on the observed and modeled visibility, we computed the optical hygroscopic growth factor, fRH, and the hygroscopic mass growth, GMVIS, which were applied to PM2.5 field measurement using a low-cost PM sensor in two different regions. The results revealed that the CPM and PM2.5 concentrations negatively affect visibility according to the weather type, with substantial modulation of the interaction between the relative humidity (RH) and PM2.5. The modeled fRH agreed well with the observed fRH in the RH range of the haze and mist. Finally, the RH-adjusted PM2.5 concentrations based on the visibility-derived hygroscopic mass growth showed the accuracy of the low-cost PM sensor improved. These findings demonstrate that in addition to visibility prediction, relationships between PMs and meteorological variables influence light scattering PM sensing.
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Understanding the consequences of the bulk of investment in transport and communication remains a growing concern for policy makers and academics due to limited studies from a macro perspective. Thus, this study empirically investigates the effects of transport investment and other factors on the quality of life and its various components. [Kindly check Chapter number 17, page 434-454]
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With the development of integrated and intelligent transportation systems, the stability and security of system performance are highly emphasized. Resilience and vulnerability are representative indicators in the performance analysis of transportation systems. A large number of related studies have emerged in recent years. Therefore, this paper reviews the recent progress in the study of vulnerability and resilience. Specific definitions of resilience and vulnerability are first given from the perspective of transportation system's supply and demand. Other related concepts of transportation system performance(TSP) are also discussed including reliability , robustness, survivability and risk. The existing studies can be divided into two aspects, i.e., the traditional topological structure and system structure analysis. The study of topology structure mainly revolves around graph theory, which is also the cornerstone of TSP research. In recent years, advances in data analysis and model simulation technology have led to an increasing number of studies considering the overall transportation system structure. The related metrics and research methods are carefully analyzed and summarized from qualitative and quantitative perspectives. Research challenges are discussed, and future directions are presented.
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The high complexity of the system topology and the uncertainty of threats necessitate the consideration of the resilience of high-speed electric multiple units (EMUs). This paper first gives a definition of high-speed EMU resilience. Then, the structure of a high-speed EMU is described in the form of a network to enable the application of network science for resilience evaluation based on corresponding mathematical expressions. Afterward, a measure of system performance (MSP) is constructed that considers the influence of the high-speed EMU topology and performance data. According to the definition of resilience of a high-speed EMU, a system resilience measurement (SRM) is proposed that comprehensively considers the degree and time of the change in system performance. The validity of our method is then illustrated by applying it to the system topology and performance data associated with the Chinese standard electric multiple units (CEMUs) that serve on high-speed railways in China. Experiments are reported to illustrate the concept of resilience and the procedure for its measurement and to present comparisons with an existing resilience index. Our results indicate that the SRM proposed here can capture the sensitivity of the response of high-speed EMUs to the disturbances, thereby supporting the optimal design and risk management.
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The rollout of 5G wireless service has been much anticipated by consumers across the U.S. since it will bring faster data download speeds and expanded service; however, the impact to aviation and air travel are as a major issue and the potential impact to aviation has not been estimated or assessed. This paper fills that gap and provides the first analysis of the potential number of flights impacted by 5G at ten of the busiest airports in the U.S. Using detailed historical weather and flight data in 2019 at 10 large hub airports, we find that nearly 15,700 flight arrivals could be directly impacted annually, at the ten airports considered. The geographical and seasonal impact varies significantly with more flights affected by the potential for 5G interference at airports in Seattle and Dallas Fort-Worth and relatively few flights affected at airports in Phoenix and Las Vegas. A case study examining ten years of data at Chicago O’Hare International, a hub for two major airlines, suggests that over 2,400 flights every year could be impacted by 5G interference. Fortunately, there has been increasing cooperation between the cell phone industry and aviation stakeholders to ensure a safe rollout of 5G C-band; this paper provides a significant contribution by documenting the issues and context for aviation operations.
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The interest in the socioeconomic impact assessments of the high-speed rail (HSR) system is burgeoning as many countries are considering investing in such a system. While extensive studies have provided a wide range of evaluations of HSR on the socioeconomic impact, primarily from an ex-post perspective, it remains unclear how reliable the evaluation outcomes were, given the variety of data, method and research framework being adopted. This paper provides a comprehensive review of the socioeconomic impact studies of high-speed rail (HSR), based on 242 academic publications. In particular, we examined to what extent the impact outcome is influenced by various modelling factors, such as data, model, and research design, using meta-analysis based on 368 empirical estimates derived from 45 empirical studies. Our analysis confirms that the factors of research design (e.g. variables, data, and modelling method) do have various influences on the empirical estimates of HSR project appraisals. In the end, the paper discusses the implications for future infrastructure project appraisals.
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This study investigates the storm surge caused by Typhoon Hato, which severely affected Macau, Hong Kong, and other coastal cities in China on 23 August 2017. A typhoon and storm surge coupling model demonstrated that the maximum storm surge height reached nearly 2.5 m along the coast of Macau, while that in Hong Kong was slightly below 2 m. Furthermore, a field survey of urban flooding revealed evidence of a 2.25-m inundation in downtown Macau and a 0.55-m inundation on Lantau Island, Hong Kong, which were likely exacerbated by a combination of storm surge, heavy rainfall, and surface water runoff over a complex hilly terrain. Significant wave overtopping and runup also occurred in beach and port areas. A typhoon track analysis confirmed that several comparably strong typhoons have followed similar ESE to WNW trajectories and made landfall in the Pearl River Delta in the last few decades. Although Hato was not the strongest of these storms, its forward speed of about 32.5 km/h was remarkably faster than those of other comparable typhoons. Higher levels of storm signal warnings were issued earlier in Hong Kong than in Macau, raising questions about the appropriate timing of warnings in these two nearby areas. Our analysis of the storm's pattern suggests that both regions' decisions regarding signal issuance could be considered reasonable or at least cannot be simply blamed, given the rapid motion and intensification of Hato and the associated economic risks at stake.
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This study develops and applies a multimodal computable general equilibrium (CGE) framework to investigate the role of resilience in the economic consequences of transportation system failures. Vulnerability and economic resilience of different modes of transportation infrastructure, including air, road, rail, water and local transit, are assessed using a CGE model that incorporates various resilience tactics including modal substitution, trip conservation, excess capacity, relocation/rerouting, and service recapture. The linkages between accessibility, vulnerability, and resilience are analyzed. The model is applied to the transportation system failures in the aftermath of Hurricane Katrina to illustrate its capabilities. The analytical framework, however, has broader applications and can provide insights for resource allocations to enhance emergent responses to unexpected events and to improve resilient design of transportation infrastructure systems.
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We study the high-speed rail (HSR) substitution for air travel through the demand shocks triggered by two HSR events: the launch of Beijing-Shanghai high-speed rails (the “Jing-hu” HSRs) and the Wenzhou train accident. One novelty of our data is that the HSR events are exogenous to the airline industry, alleviating the common endogeneity concern. Using a difference-in-difference approach, we find some evidence of substitution based on the pattern of airfare adjustments during the sample period. Specifically, compared to those in the control group, mean airfares for routes along the Jing-hu HSRs decline by 30.4 per cent upon the launch, but rebound by 27.4 per cent following the accident. Furthermore, the two events have a larger impact on low-cost carriers (LCCs) and regional airlines, on tourism routes, and on flights that depart during evening hours than their counterparts, respectively. Thus, we claim that the HSRs mainly serve as a low-end substitution for air travel in China.
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Extreme weather is creating a growing challenge for disaster managers and transportation planners. The Tennessee Department of Transportation (TDOT) recently completed a study sponsored in part by the U.S. Federal Highway Administration (FHWA) to conduct an assessment of critical transportation assets in the state that are most vulnerable to plausible extreme weather events out to 2040. This vulnerability assessment required building an asset inventory, determining which of those assets should be considered critical, identifying various types of extreme weather events to which the critical assets may be exposed, and quantifying the potential asset damage and system disruption for the selected extreme weather event types and critical asset combinations. Combining this information then provided an overall vulnerability rating for the critical transportation assets in the state.
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This paper develops a mixed method approach to infrastructure planning through a United Kingdom (UK) case study examining the impact of a changing climate on long distance travel and mobility between London and Glasgow. A novel combination of a qualitative method - Systematic Qualitative Foresight (SQF) - and quantitative simulation using discrete choice stated preference methods is applied. The main dataset is a travel behaviour survey of over 2000 residents of London and Glasgow. Three illustrative SQF-based scenarios are developed incorporating society, technology and climate dimensions. For each scenario, the choice of long-distance travel mode by two groups of respondents generated by cluster analysis is simulated using stated preference survey data to describe the choices likely to be made by actors within each scenario. We demonstrate the importance of considering a wide range of variables when creating instruments for infrastructure planning decisions. Our results show that weather-related disruption has consequences for travel behaviour, with a considerable number of travellers deciding not to travel despite the importance of their trip. However, the vast majority of travellers would still travel. This should be considered by policy makers, and those responsible for transport infrastructure, in order to increase its resilience to extreme weather and demand, and better devise contingency plans to contain, and minimise, the effect of the disruptions on the users. The method described has wider implications for infrastructure planning, particularly in its ability to engage a broader range of stakeholders and to avoid linear models of prediction. By emphasising the creation of a plausible decision space, it offers the possibility of increased robustness and resilience in infrastructure planning.
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Across the Mediterranean region, extreme weather events (EWE), such as high-intensity storms causing flooding in small river basins, are one of the most common types of hydro-meteorological hazards. Flooding has been associated with severe effects on road networks and a significant number of vehicle-related fatalities, raising concerns regarding the performance of transportation infrastructure during EWEs. Given the expected increase in frequency of such events within the context of climate change, an assessment of its vulnerability is particularly crucial. The work presented herein evaluates the performance of transportation infrastructure during high-intensity storms. This research focuses on small rural catchments, examining the impact of five extreme storm events in five rural basins in Greece. Post-flood surveys were conducted, to record the impact of inundation on each infrastructure element in the five catchments. Overall, findings showed that road infrastructure, especially river crossings, performed poorly, restricting access to large areas during and after the events, affecting the safety of commuters and sustaining extensive damages. On average, it was found that 73% of the river crossings and 11.5% of the total length of the road network were inundated or damaged, while a total of 12 individuals died during the events. The results revealed that the impact of flooding in the transportation infrastructure of small rural basins was severe and a threat to human life. The findings of this study indicate that authorities should consider taking measures during EWEs, re-examine the safety features of the relevant infrastructure and assess the risk related to its failure.
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Rapid warming in the Arctic could influence mid-latitude circulation by reducing the poleward temperature gradient. The largest changes are generally expected in autumn or winter but whether significant changes have occurred is debated. Here we report significant weakening of summer circulation detected in three key dynamical quantities: (i) the zonal-mean zonal wind, (ii) the eddy kinetic energy (EKE) and (iii) the amplitude of fast-moving Rossby waves. Weakening of the zonal wind is explained by a reduction in poleward temperature gradient. Changes in Rossby waves and EKE are consistent with regression analyses of climate model projections and changes over the seasonal cycle. Monthly heat extremes are associated with low EKE and thus the observed weakening might have contributed to more persistent heat waves in recent summers. Copyright © 2015, American Association for the Advancement of Science.
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Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of weather conditions depended on trip purpose—was assayed. A stated adaptation study was conducted in Flanders (the Dutch-speaking region of Belgium). A survey, completed by 586 respondents, was administered both on the Internet and as a traditional paper-and-pencil questionnaire. To ensure optimal correspondence between the survey sample composition and the Flemish population, observations in the sample were weighted. To test the main hypotheses, Pearson chi-square independence tests were performed. Results from both the descriptive analysis and the independence tests confirm that the type of weather matters and that changes in travel behavior in response to these weather conditions are highly dependent on trip purpose. This dependence of behavioral adjustments on trip purpose provides policy makers with a deeper understanding of how weather conditions affect traffic. Further generalizations of the findings are possible by shifting the scope toward revealed travel behavior. Triangulation of both stated and revealed travel behavior on the one hand and traffic intensities on the other hand is a key challenge for further research.
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This paper deals with the 2007 wildfires that hit Peloponnesus, the southern peninsula of Greece, presenting an overview of the impacts in terms of infrastructural damages and human injuries and losses. Network performance and components’ criticality analyses are used to assess the effects of the fires in vehicular traffic and the overall transport network. The crisis and emergency management of the event are discussed in depth, highlighting potential gaps and possibilities for future improvement. The paper concludes with a presentation of the adaptation measures that succeeded the event in terms of recovery plans, national efforts on fire prevention programs and wildfire management.
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Weather conditions may significantly impact a series of everyday human decisions and activities. As a result, engineers seek to integrate weather-related data into traffic operations in order to improve the current state of practice. Travel times and speeds are two of the elements of a transportation system that may be greatly affected by the weather resulting in deterioration of roadway network performance. This study aims to investigate the impact of different intensities of rain, snow and temperature levels on macroscopic travel times in the Greater London area (UK) during the period 1 October–10 December 2009. The analysis was carried out for three 2-h periods on weekdays during the morning, afternoon and evening periods. Automatic Number Plate Recognition (ANPR) data obtained from more than 380 travel links are used in the analysis. The main finding is that the impact of rain and snow is a function of their intensity. Specifically, the ranges of the total travel time increase due to light, moderate and heavy rain are: 0.1–2.1%, 1.5–3.8%, and 4.0–6.0% respectively. Light snow results in travel time increases of 5.5–7.6%, whilst heavy snow causes the highest percentage delays spanning from 7.4% to 11.4%. Temperature has nearly negligible effects on travel times. It was also found that the longer links within outer London generally yield greater travel time decreases than those in inner London, and even higher decreases than the shortest links in central London. This research provides planners with additional information that can be used in traffic management to modify planning decisions and improve the transportation system control on a network scale under different weather conditions. In order to determine whether the weather effects are region-specific, continued research is needed to replicate this study in other areas that exhibit different characteristics.
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The assessment of climate change impact is a fundamental step in highlighting the likely costs of inaction on mitigation policies and providing a guide of how to adapt to the potential impacts. This paper highlights the need to use an interdisciplinary approach to climate change impact assessment. This approach would take into account both climate and socioeconomic scenarios. It would also be mindful that the even the hard infrastructure may change dramatically in a sector as complex and reactive as transportation. In assessing climate change impact, it may be necessary to repeat the analysis for a number of scenarios in order to address this uncertainty.
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Temperature and precipitation extremes and their potential future changes are evaluated in an ensemble of global coupled climate models participating in the Intergovernmental Panel on Climate Change (IPCC) diagnostic exercise for the Fourth Assessment Report (AR4). Climate extremes are expressed in terms of 20-yr return values of annual extremes of near-surface temperature and 24-h precipitation amounts. The simulated changes in extremes are documented for years 2046–65 and 2081–2100 relative to 1981–2000 in experiments with the Special Report on Emissions Scenarios (SRES) B1, A1B, and A2 emission scenarios. Overall, the climate models simulate present-day warm extremes reasonably well on the global scale, as compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes, especially in sea ice–covered areas. Simulated present-day precipitation extremes are plausible in the extratropics, but uncertainties in extreme precipitation in the Tropics are very large, both in the models and the available observationally based datasets. Changes in warm extremes generally follow changes in the mean summertime temperature. Cold extremes warm faster than warm extremes by about 30%–40%, globally averaged. The excessive warming of cold extremes is generally confined to regions where snow and sea ice retreat with global warming. With the exception of northern polar latitudes, relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation, particularly in tropical and subtropical regions. Consistent with the increased intensity of precipitation extremes, waiting times for late-twentieth-century extreme precipitation events are reduced almost everywhere, with the exception of a few subtropical regions. The multimodel multiscenario consensus on the projected change in the globally averaged 20-yr return values of annual extremes of 24-h precipitation amounts is that there will be an increase of about 6% with each kelvin of global warming, with the bulk of models simulating values in the range of 4%–10% K−1. The very large intermodel disagreements in the Tropics suggest that some physical processes associated with extreme precipitation are not well represented in models. This reduces confidence in the projected changes in extreme precipitation.
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Technologically driven transport systems are characterized by a networked structure connecting operation centers and by a dynamics ruled by pre-established schedules. Schedules impose serious constraints on the timing of the operations, condition the allocation of resources and define a baseline to assess system performance. Here we study the performance of an air transportation system in terms of delays. Technical, operational or meteorological issues affecting some flights give rise to primary delays. When operations continue, such delays can propagate, magnify and eventually involve a significant part of the network. We define metrics able to quantify the level of network congestion and introduce a model that reproduces the delay propagation patterns observed in the U.S. performance data. Our results indicate that there is a non-negligible risk of systemic instability even under normal operating conditions. We also identify passenger and crew connectivity as the most relevant internal factor contributing to delay spreading.
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This paper reviews land based transport related issues from considerations of climate change adaptation in Australia. The two main issues for climate change adaptation are sea level rise and the increased frequency and intensity of extreme weather events. These issues are considered in the paper. It considers the risks to existing transport infrastructure and the resulting considerations necessary in planning new infrastructure, transport systems operations under changing climatic conditions, and potential changes in travel behaviour. The use and capability of regional rural networks in emergency evacuation planning emerges as one particular area for further research. More generally, recognition of the risks associated with climate change is required for better planning of new infrastructure and mitigating potential damage to existing infrastructure. Climate change poses a significant risk to infrastructure and its owners, managers and operators. There is a need to undertake research into the likely impacts of climate change on Australia's transport infrastructure, establish the categories of infrastructure most at risk and outline opportunities for adaptation responses, and examine the current governance structures. Then the administrative, legal and other issues that may impact on climate change adaptation can be identified.
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We examined the number of tropical cyclones and cyclone days as well as tropical cyclone intensity over the past 35 years, in an environment of increasing sea surface temperature. A large increase was seen in the number and proportion of hurricanes reaching categories 4 and 5. The largest increase occurred in the North Pacific, Indian, and Southwest Pacific Oceans, and the smallest percentage increase occurred in the North Atlantic Ocean. These increases have taken place while the number of cyclones and cyclone days has decreased in all basins except the North Atlantic during the past decade.
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Airlines typically construct their schedules assuming that every flight leg will depart and arrive as planned. Because this optimistic scenario rarely occurs, these plans are frequently disrupted and airlines often incur significant costs in addition to those originally planned. Flight delays and schedule disruptions also cause passenger delays and disruptions. A more robust plan can reduce the occurrence and impact of these delays, thereby reducing costs. In this paper, we present two new approaches to minimize passenger disruptions and achieve robust airline schedule plans. The first approach involves routing aircraft, and the second involves retiming flight departure times. Because each airplane usually flies a sequence of flight legs, delay of one flight leg might propagate along the aircraft route to downstream flight legs and cause further delays and disruptions. We propose a new approach to reduce delay propagation by intelligently routing aircraft. We formulate this problem as a mixedinteger programming problem with stochastically generated inputs. An algorithmic solution approach is presented. Computational results obtained using data from a major U.S. airline show that our approach can reduce delay propagation significantly, thus improving on-time performance and reducing the numbers of passengers disrupted. Our second area of research considers passengers who miss their flight legs due to insufficient connection time. We develop a new approach to minimize the number of passenger misconnections by retiming the departure times of flight legs within a small time window. We formulate the problem and an algorithmic solution approach is presented. Computational results obtained using data from a major U.S. airline show that this approach can substantially reduce the number of passenger misconnections without significantly increasing operational costs.
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Whether the characteristics of tropical cyclones have changed or will change in a warming climate - and if so, how - has been the subject of considerable investigation, often with conflicting results. Large amplitude fluctuations in the frequency and intensity of tropical cyclones greatly complicate both the detection of long-term trends and their attribution to rising levels of atmospheric greenhouse gases. Trend detection is further impeded by substantial limitations in the availability and quality of global historical records of tropical cyclones. Therefore, it remains uncertain whether past changes in tropical cyclone activity have exceeded the variability expected from natural causes. However, future projections based on theory and high-resolution dynamical models consistently indicate that greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms, with intensity increases of 2-11% by 2100. Existing modelling studies also consistently project decreases in the globally averaged frequency of tropical cyclones, by 6-34%. Balanced against this, higher resolution modelling studies typically project substantial increases in the frequency of the most intense cyclones, and increases of the order of 20% in the precipitation rate within 100 km of the storm centre. For all cyclone parameters, projected changes for individual basins show large variations between different modelling studies.
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Global warming is expected to lead to a large increase in atmospheric water vapor content and to changes in the hydrological cycle, which include an intensification of precipitation extremes. The intensity of precipitation extremes is widely held to increase proportionately to the increase in atmospheric water vapor content. Here, we show that this is not the case in 21st-century climate change scenarios simulated with climate models. In the tropics, precipitation extremes are not simulated reliably and do not change consistently among climate models; in the extratropics, they consistently increase more slowly than atmospheric water vapor content. We give a physical basis for how precipitation extremes change with climate and show that their changes depend on changes in the moist-adiabatic temperature lapse rate, in the upward velocity, and in the temperature when precipitation extremes occur. For the tropics, the theory suggests that improving the simulation of upward velocities in climate models is essential for improving predictions of precipitation extremes; for the extratropics, agreement with theory and the consistency among climate models increase confidence in the robustness of predictions of precipitation extremes under climate change.
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This study investigates the impacts of high-speed rail (HSR) on domestic air transportation in China using a new comprehensive modeling framework utilizing both demand and supply perspectives. For the first time the assessment was conducted using an improved panel regression model by taking into account of the detailed opening schedules of various HSR services during the period 2001–2014. The research findings reveal that the deployed HSR services have a significant substitutional effect on domestic air transportation in China, but the effect varies across different HSR routes, travel distance and city type. Specifically, the research found a decrease in domestic passengers of 28.2%, in flights of 24.6% and in seat capacity of 27.9% after the introduction of HSR services. The impacts are found much stronger among those air routes that connect major hub within a distance range of 500 to 800 km. The uneven nature of the impact can be seen in the different experiences of selected cities. For example, air travel declined approximately 45% after commencement of the Wuhan-Guangzhou HSR, whereas it fell by 34% after the opening of the Beijing-Shanghai HSR.
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This paper reviews the development of China’s air transport policy and examines the determinants of Chinese city-pair air passenger flows using a gravity model approach accounting for the effects of multilateral resistance. We find enormous positive impacts of both the continuing liberalisation of this industry and the low cost carriers (LCCs) in promoting bilateral traffic flows in China’s domestic aviation market. Local industry structures and high-speed rail (HSR) services also influence the volume of passenger movement. The challenge from HSR will be greater in the near future after the fast-expanding HSR network has connected most of the major cities.
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We investigate the impact of the commencement of high-speed rail (HSR) services on airlines’ domestic available seats on affected routes in China, Japan, and South Korea. The study is based on a dataset covering the 1994–2012 period. We use the propensity score matching method to pair HSR affected routes with routes without HSR services. The difference-in-difference approach is used to estimate the impact of HSR entry. We find that HSR entries may, on average, lead to a more significant drop in airlines’ seat capacity in China than in Japan and Korea given similar HSR service speed. In China, HSR services with a maximum speed about 200 km/h can produce strong negative impacts on medium-haul air routes but induce more air seat capacity on long-haul routes. HSR services with a maximum speed of 300 km/h have little extra impact on medium-haul routes but a strong negative impact on long-haul routes. Finally, although HSR has a strong negative impact in Japan’s short-haul and medium-haul air markets, little impact is observed in its long-haul markets.
Conference Paper
Observed records provide clear evidence of global climate change, especially for severe weather events. The study presented addressed strategies for safety management of road infrastructure under Severe Weather Conditions (SWC), aims to consolidate transportation infrastructures' adaptation to severe weather change. On the basis of reviewing security and management strategy, we analyze the impact of Road Transportation Infrastructure (RTI) in severe weathers. Moreover, strategy development for managing highway safety under SWC is discussed based on the risk assessment, the precaution mechanisms, the emergency rescue and the traffic organization. Lastly, we briefly discusses guarantee measures for implementation. The study demonstrated that the reasonable adaptation strategy for safety management of RTI under SWC can effectively enhance the responsiveness of the traffic administrative department, in addition, which is of great social significance to reduce the loss of accidents to SWC, to maintain social stability and the protection of people's life and property safety.
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Expanding employment opportunities for citizens has become an increasingly central goal of public policy in the United States. Prior work has considered that the inability of households to spatially access jobs may be a driver of unemployment. The provision of public transportation provides a viable policy lever to increase the number of job opportunities available to households. Previous research has yielded mixed results regarding whether household location is an important factor in determining employment status. Several papers have identified mobility as a limiting factor for obtaining a job, particularly in regards to private vehicle ownership. The location of economically developed neighbourhoods and the citing of public transportation are conceivably codetermined, presenting an endogenous relationship. It is therefore unclear if public transportation access is actually contributing to neighbourhood job market outcomes. This paper will use the incidence of Hurricane Sandy striking New York City on 29 October 2012 and the resulting exogenous reduction in public transit access to particular neighbourhoods as a natural experiment to test for the effect of public transportation on employment outcomes. This study identifies a significant causal effect linking public transportation access to neighbourhood unemployment rates, particularly amongst subgroups dependent on public transit.
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The present paper presents a data-driven method for assessing the resilience of the European passenger transport network during extreme weather events. The method aims to fill in the gap of current research efforts regarding the quantification of impacts attributed to climate change and the identification of substitutability opportunities between transport modes in case of extreme weather events (EWE). The proposed method consists of three steps concerning the probability estimation of an EWE occurring within a transportation network, the assessment of its impacts and the passengers’ flow shift between various transport modes. A mathematical formulation for the proposed data-driven method is provided and applied in an indicative European small-scale network, in order to assess the impacts of EWE on modal choice. Results are expressed in passenger differentiated flows and the paper concludes with future research steps and directions.
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A consistent poleward and upward shift and intensification of the storm tracks is found in an ensemble of 21st century climate simulations performed by 15 coupled climate models. The shift of the storm tracks is accompanied by a poleward shift and upward expansion of the midlatitude baroclinic regions associated with enhanced warming in the tropical upper troposphere and increased tropopause height. The poleward shift in baroclinicity is augmented in the Southern Hemisphere and partially offset in the Northern Hemisphere by changes in the surface meridional temperature gradient. The poleward shift of the storm tracks also tends to be accompanied by poleward shifts in surface wind stress and precipitation, and a shift towards the high index state of the annular modes. These results highlight the integral role that the storm tracks play in the climate system, and the importance of understanding how and why they will change in the future.
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Transportation officials are increasingly faced with challenging decisions about how to design, plan, and manage infrastructure to confront changes in climate and extreme weather events. An understanding of which impacts affect infrastructure and at what point damage begins to occur is a critical step toward assessing overall vulnerability and risk. However, few resources exist to help managers and designers identify key thresholds and indicators of sensitivity to weather and climate impacts. This paper introduces a sensitivity matrix, a tool developed for the U.S. Department of Transportation's Gulf Coast Study, Phase 2, adaptation pilot project in Mobile, Alabama. This matrix is an important step toward a more comprehensive understanding of relationships between climate and transportation. Transportation planners can use this matrix to screen for assets that are particularly sensitive and, therefore, potentially vulnerable to climate change. Where possible, the matrix includes key thresholds at which damage may be observed. This resource can assist the transportation community in conducting climate vulnerability and risk assessments. This sensitivity matrix reveals three main conclusions about the sensitivity of the transportation system to climate stressors. First, transportation assets tend to be more sensitive to extreme events than to incremental changes in the mean of climate variables. Second, services such as maintenance, traffic conveyance, and safety often are more sensitive to climate stressors than are physical assets. Finally, an asset is often sensitive to stressors whose occurrence is relatively unlikely in comparison with typical weather variability.
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Extreme events often expose vulnerabilities of socioeconomic infrastructures and point to directions of much-needed policy change. Integrated impact assessment of such events can lead to finding of sustainability principles. Southern and central China has for decades been undergoing a breakneck pace of socioeconomic development. In early 2008, a massive ice storm struck this region, immobilizing millions of people. The storm was a consequence of sustained convergence between tropical maritime and continental polar air masses, caused by an anomalously stable atmospheric general circulation pattern in both low and high latitudes. Successive waves of freezing rain occurred during a month period, coating southern and central China with a layer of ice 50 to 160mm in thickness. We conducted an integrated impact assessment of this event to determine whether and how the context of socioeconomic and human-disturbed natural systems may affect the transition of natural events into human disasters. We found: 1) without contingency plans, advanced technologies dependent on interrelated energy supplies can create worse problems during extreme events, 2) the weakest link in disaster response lies between science and decision making, 3) biodiversity is a form of long-term insurance for sustainable forestry against extreme events, 4) sustainable extraction of non-timber goods and services is essential to risk planning for extreme events in forest resources use, 5) extreme events can cause food shortage directly by destroying crops and indirectly by disrupting food distribution channels, 6) concentrated economic development increases societal vulnerability to extreme events, and 7) formalized institutional mechanisms are needed to ensure that unexpected opportunities to learn lessons from weather disasters are not lost in distracting circumstances.
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The investigation of weather effects on traffic intensity is important from a road safety point of view, because traffic intensity is noted as the first and primary determinant of traffic safety. Next to traffic safety, weather conditions affect to other predominant traffic variables, namely traffic demand and traffic flow. Therefore the main objective of this study is the identification and comparison of weather effects on traffic intensity at different site locations. To assess the impact of weather conditions on traffic intensity, the upstream and downstream traffic of four traffic count locations are considered. The traffic intensity data originate from minute data coming from single inductive loop detectors, collected by the Flemish Traffic Control Center. Data concerning weather events were recorded by the Royal Meteorological Institute. The main modeling philosophy envisaged in this study to identify and quantify weather effects is the linear regression approach. Most appealing result of this study for policy makers, is the heterogeneity of the weather effects between different traffic count locations, and the homogeneity of the weather effects on upstream and downstream traffic at a certain location. The results also indicated that snowfall, rainfall and wind speed have a clear diminishing effect on traffic intensity, while maximum temperature significantly increases traffic intensity. Further generalizations of the findings are possible by studying weather effects on local roads and by shifting the scope towards travel behavior. Simultaneously modeling of weather conditions, traffic intensity rates, collision risk and activity travel behavior is certainly a key challenge for further research.
Article
Weather affects many aspects of transportation, but three dimensions of weather impact on highway traffic are predominant and measureable. Inclement weather affects traffic demand, traffic safety, and traffic flow relationships. Understanding these relationships will help highway agencies select better management strategies and create more efficient operating policies. For example, it was found that severe winter storms bring a higher risk of being involved in a crash by as much as 25 times - much higher than the increased risk brought by behaviors that state governments already have placed sanctions against, such as speeding or drunk driving. Given the heightened risk of drivers' involvement in a crash, highway agencies might wish to manage better and restrict use of highways during times of extreme weather, to reduce safety costs and costs associated with rescuing stranded and injured motorists in the worst weather conditions. However, the first step in managing the transportation systems to minimize the weather impact is to quantify its impact on traffic. This paper reviews the literature and recent research work conducted by the Center for Transportation Research and Education on the impact of weather on traffic demand, traffic safety, and traffic flow relationships. Included are new estimates of capacity and speed reduction due to rain, snow, fog, cold, and wind by weather intensity levels (e.g., snowfall rate per hour).
Article
The European 7th Framework Programme project Extreme Weather impacts on European Networks of Transport devised a holistic analysis of extreme weather risks for the transport system. The analysis provided an overview of extreme weather risks, or a risk panorama. The risk panorama was built on a probabilistic approach to extreme weather phenomena occurrences and on vulnerability analysis based on selected macro-level economic and transport system indicators of the member states of EU-27. The panorama covers all transport modes and views infrastructure-related risks, time delay risks, and accidents risks. In addition to climatic circumstances, the devised risk indicator is also dependent on regional circumstances, such as population and transport density and income level. This paper describes the construct and application of an extreme weather risk indicator (EWRI). EWRIs are counted for each country and each transport mode separately. Furthermore, this paper also presents the most significant extreme weather events in different parts of Europe and on the transport modes they affect the most.
Article
This paper presents a survey of the empirical literature on the effects of climate change and weather conditions on the transport sector. Despite mixed evidence on many issues, several patterns can be ob-served. On a global scale especially shifts in tourism and agricultural production due to increased tem-peratures may lead to shifts in passenger and freight transport. The predicted rise in sea levels and the associated increase in frequency and intensity of storm surges and flooding incidences may further-more be some of the most worrying consequences of climate change, especially for coastal areas. Cli-mate change related shifts in weather patterns may also affect infrastructure disruptions. Clear patterns are that precipitation affects road safety; it increases accident frequency but decreases accident severi-ty. Precipitation also increases congestion, especially during peak hours. Furthermore, an increased frequency of low water levels may considerably increase costs of inland waterway transport. Despite these valuable insights, the net impact of climate change on generalised costs of the various transport modes are uncertain and ambiguous, with a possible exception for inland waterway transport.
Article
Global climate change is likely to affect urban infrastructure through sea level rise and increased frequency of extreme events. This paper assesses the potential impact of climate change on the system-wide performance of transportation networks using the Boston Metro Area as a case study. The methodology integrates projected changes in land use, demographic and climatic conditions into the urban transportation modeling system in order to explore the relative impacts of global warming on the system performance due to additional riverine and coastal flooding. Results indicate almost a doubling in delays and lost trips. These impacts are significant, but probably not large enough to justify a major effort for adapting the physical infrastructure to expected climatic conditions, except for some key links.
An empirical study on the indirect impact of flight delay on China's economy
  • Y Chen
  • J Yu
  • S B Tsai
  • J Zhu
  • E D Coffel
  • T R Thompson
  • R M Horton
Chen, Y., Yu, J., Tsai, S.B., Zhu, J., 2018. An empirical study on the indirect impact of flight delay on China's economy. Sustainability 10 (2), 357. Coffel, E.D., Thompson, T.R., Horton, R.M., 2017. The impacts of rising temperatures on aircraft takeoff performance. Clim. Change 144 (2), 381-388.
The impact of climate change and weather on transport: an overview of empirical findings
  • T R Knutson
  • J L Mcbride
  • J Chan
  • K Emanuel
  • G Holland
  • C Landsea
  • M Sugi
  • M J Koetse
  • P Rietveld
Knutson, T.R., McBride, J.L., Chan, J., Emanuel, K., Holland, G., Landsea, C., Sugi, M., 2010. Tropical cyclones and climate change. Nat. Geosci. 3 (3), 157. Koetse, M.J., Rietveld, P., 2009. The impact of climate change and weather on transport: an overview of empirical findings. Transport. Res. Part D: Transport Environ. 14 (3), 205-221.
Integrating Extreme Weather Risk into Transportation Asset Management
  • M D Meyer
  • E Rowan
  • M J Savonis
  • A Choate
Meyer, M.D., Rowan, E., Savonis, M.J., Choate, A., 2012. Integrating Extreme Weather Risk into Transportation Asset Management. American Association of State Highway and Transportation Officials Report, Washington, D.C.
A review on climate change adaptation policies for the transportation sector. MPRA Working paper
  • I Stamos
  • E Mitsakis
Stamos, I., Mitsakis, E., 2014. A review on climate change adaptation policies for the transportation sector. MPRA Working paper. https://mpra.ub.uni-muenchen.de/ 61535/.
What is the largest cause of delay in the National Airspace System?
Federal Aviation Administration, 2018. What is the largest cause of delay in the National Airspace System? https://www.faa.gov/nextgen/programs/weather/faq/# faq1.