Leveraging socio-ecological resilience theory to build climate resilience in transport infrastructure

ABSTRACT

Anthropogenic climate change poses risks to transport infrastructure that include disrupted operations, reduced lifespan and increased reconstruction and maintenance costs. Efforts to decrease the vulnerability of transport networks have been largely limited to understanding projected risks through governance and administrative efforts. Where physical adaptation measures have been implemented, these have typically aligned with a traditional “engineering resilience” approach of increasing the strength and rigidity of assets to withstand the impacts of climate change and maintain a stable operating state. Such systems have limited agility and are susceptible to failure from “surprise events”. Addressing these limitations, this paper considers an alternate approach to resilience, inspired by natural ecosystems that sense conditions in real-time, embrace multi-functionality and evolve in response to changing environmental conditions. Such systems embrace and thrive on unpredictability and instability. This paper synthesises key literature in climate adaptation and socio-ecological resilience theory to propose a shift in paradigm for transport infrastructure design, construction and operation, towards engineered systems that can transform, evolve and internally manage vulnerability. The authors discuss the opportunity for biomimicry (innovation inspired by nature) as an enabling discipline for supporting resilient and regenerative infrastructure, introducing three potential tools and frameworks. The authors conclude the importance of leveraging socio-ecological resilience theory, building on the achievements in engineering resilience over the past century. These findings have immediate practical applications in redefining resilience approaches for new transport infrastructure projects and transport infrastructure renewal.     

Impact analysis of climate change on rail systems for adaptation planning: A UK case

Climate change poses critical challenges for rail infrastructure and operations. However, the systematic analysis of climate risks and the associated costs of tackling them, particularly from a quantitative perspective, is still at an embryonic phase due to the kaleidoscopic nature of climate change impacts and lack of precise climatic data. To cope with such challenges, an advanced Fuzzy Bayesian Reasoning (FBR) model is applied in this paper to understand climate threats of the railway system. This model ranks climate risks under high uncertainty in data and comprehensively evaluates these risks by taking account of infrastructure resilience and specific aspects of severity of consequence. Through conducting a nationwide survey on the British railway system, it dissects the status quo of primary climate risks. The survey implies that the top potential climate threats are heavy precipitation and floods. The primary risks caused by the climate threats are bridges collapsing and bridge foundation damage due to flooding and landslips. The findings can aid transport planners to prioritise climate risks and develop rational adaptation measures and strategies.     

Implications of climate change for thermal discomfort on underground railways

Hot weather events, ventilation assets, changing passenger demand and service expectations have all caused increased attention on thermal comfort on London’s Tube. This study provides estimates of the future number of days when passengers travelling on sections of the Tube could be subjected to thermal discomfort under future scenarios of climate change, and the potential number of passengers dissatisfied. A risk based methodology is presented, integrating a spatial weather generator modified for urban areas and a thermal comfort model. The study provides an initial assessment of adaptation options by considering the implications of lowering train temperatures by 2 °C and 4 °C to represent saloon cooling. Median results under a 2050 high scenario indicate that all Tube lines assessed could experience near-complete passenger dissatisfaction with the thermal environment in trains in the unlikely event that nothing else were to change. Adaptation aimed at lowering train temperatures has the potential to provide tangible improvements in thermal comfort. However, this was not projected to be sufficient to maintain comfortable thermal conditions for many of the lines in the 2050s under high emission scenarios, requiring a combination of other infrastructure cooling measures to be implemented in parallel.     

Impact assessment of extreme weather events on transport networks: A data-driven approach

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.     

Green walking networks for climate change adaptation

Climate change (CC) potentially affects people travel behaviour, due to extreme weather conditions. This is particularly true for pedestrians, that are more exposed to weather conditions. Introducing the effect of this change in transport modelling allows to analyse and plan walking networks taking into consideration the climatic variable. The aim of this work is to develop a tool that can support planning and design of walking networks, by assessing the effects of actions oriented to increase resilience with respect to extreme weather conditions (CC adaptation).An integrated approach is used, thus combining transport and land-use planning concepts with elements of outdoor thermal comfort and network accessibility. Walking networks are analysed through centrality indexes, including thermal comfort aspects into a general cost function of links and weighted nodes. The method has been applied to the walking network inside the Campus of the University of Catania (Italy), which includes different functions and where pedestrian paths are barely used by people. Results confirm that this tool is sensitive to the variables representing weather conditions and it can measure the influence of CC adaptation measures (e.g. vegetation) on walking attitude and on the performance of the walking network.     

Impact of weather on urban transit ridership

Utilizing daily ridership data, literature has shown that adverse weather conditions have a negative impact on transit ridership and in turn, result in revenue loss for the transit agencies. This paper extends this discussion by using more detailed hourly ridership data to model the weather effects. For this purpose, the daily and hourly subway ridership from New York City Transit for the years 2010–2011 is utilized. The paper compares the weather impacts on ridership based on day of week and time of day combinations and further demonstrates that the weather’s impact on transit ridership varies based on the time period and location. The separation of ridership models based on time of day provides a deeper understanding of the relationship between trip purpose and weather for transit riders. The paper investigates the role of station characteristics such as weather protection, accessibility, proximity and the connecting bus services by developing models based on station types. The findings indicate substantial differences in the extent to which the daily and hourly models and the individual weather elements are able to explain the ridership variability and travel behavior of transit riders. By utilizing the time of day and station based models, the paper demonstrates the potential sources of weather impact on transit infrastructure, transit service and trip characteristics. The results suggest the development of specific policy measures which can help the transit agencies to mitigate the ridership differences due to adverse weather conditions.     

Estimating changes in transport CO2 emissions due to changes in weather and climate in Sweden

There is a considerable body of studies on the relationship between daily transport activities and CO₂ emissions. However, how these emissions vary in different weather conditions within and between the seasons of the year is largely unknown. Because individual activity–travel patterns are not static but vary in different weather conditions, it is immensely important to understand how CO₂ emissions vary due to the change of weather. Using Swedish National Travel Survey data, with emission factors calculated through the European emission factor model ARTEMIS, this study is a first attempt to derive the amount of CO₂ emission changes subject to the change of weather conditions. A series of econometric models was used to model travel behaviour variables that are crucial for influencing individual CO₂ emissions. The marginal effects of weather variables on travel behaviour variables were derived. The results show an increase of individual CO₂ emissions in a warmer climate and in more extreme temperature conditions, whereas increasing precipitation amounts and snow depths show limited effects on individual CO₂ emissions. It is worth noting that the change in CO₂ emissions in the scenario of a warmer climate and a more extreme temperature tends to be greater than the sum of changes in CO₂ emissions in each individual scenario. Given that a warmer climate and more extreme weather could co-occur more frequently in the future, this result suggests even greater individual CO₂ emissions than expected in such a future climate.     

State-of-the-practice assessment of climate change adaptation practices across metropolitan planning organizations pre- and post-Hurricane Sandy

Metropolitan Planning Organizations (MPOs) throughout the United States are identifying goals and implementation strategies to reduce the impacts of climate change through transportation adaptation initiatives. Using vulnerability assessments as well as adaptation practices that support mitigation, MPOs are beginning to integrate climate change planning into the long range planning process. Evaluating the state-of-the-practice of adaptation planning and adaptation in support of mitigation is useful in that it helps identify gaps and areas of improvement. Therefore, this research investigates the state-of-the-practice of MPO adaptation planning using the Mid-Atlantic region as a case study. Surveys, administered in 2012 and 2014, are used to identify the level of progress of MPOs with regard to climate change adaptation practices as well as barriers before and after Hurricane Sandy. A cross-sectional analysis using GIS (Geographic Information Systems) maps the results of the surveys and spatially compares regional trends. The results of the case study suggest growing interest in adaptation efforts such as floodplain area designations and efforts to enhance coordination and collaboration as transportation jurisdictions respond to the potential climate change impacts. In addition, MPOs with dense, smaller geographic areas prioritize inter-jurisdictional collaboration as high, suggesting that they are more reliant on other agencies to maintain inter-connectivity of transportation networks and further implement adaptation planning practices.     

Impacts of weather on public transport ridership: Results from mining data from different sources

The existing studies concerning the influence of weather on public transport have mainly focused on the impacts of average weather conditions on the aggregate ridership of public transit. Not much research has examined these impacts at disaggregate levels. This study aims to fill this gap by accounting for intra-day variations in weather as well as public transport ridership and investigating the effect of weather on the travel behavior of individual public transit users. We have collected smart card data for public transit and meteorological records from Shenzhen, China for the entire month of September 2014. The data allow us to establish association between the system-wide public transit ridership and weather condition on not only daily, but also hourly basis and for each metro station. In addition, with the detailed trip records of individual card holders, the travel pattern by public transit are constructed for card holders and this pattern is linked to the weather conditions he/she has experienced. Multivariate modeling approach is applied to analyze the influence of weather on public transit ridership and the travel behavior of regular transit users. Results show that some weather elements have more influence than others on public transportation. Metro stations located in urban areas are more vulnerable to outdoor weather in regard to ridership. Regular transit users are found to be rather resilient to changes in weather conditions. Findings contribute to a more in-depth understanding of the relationship between everyday weather and public transit travels and also provide valuable information for short-term scheduling in transit management.     

The impact of extreme weather conditions on long distance travel behaviour

This paper examines traveller attitudes and responses towards disruption from weather and natural events. An internet-based travel behaviour survey was conducted with more than 2000 respondents in London and Glasgow. Of these respondents, 740 reported information on over 1000 long distance trips affected by extreme weather and natural events over the previous three years. Results show respondents are generally cautious towards travelling during extreme weather events. For a slight majority in the case of air and public transport, and a greater one in the case of car, travellers did not considerably alter their travel plan following the disruption. This was explained not only by less disruptive weather conditions (with heavy snow and volcanic ash being the most disruptive) and impact, but also by the relative importance of their trips. Differences between transport modes were not substantial. Business trips sometimes appeared to give travellers more flexibility, some other times not. Origin and destination did have an impact on reaction, as well as the presence of children whilst travelling. Mixed results were obtained about socio-economic and attitudinal variables. Age in particular did not appear to have a significant effect. Whilst most respondents did acknowledge no external influence in their decision, results showed an important contribution of transport organisation staff, as well as home and mobile internet technology. A limited but still considerable number of respondents indicated their closest friends/relatives as the main influence of their decisions. The results will help planners deploy strategies to mitigate the negative effects of weather related disruptions.     

Modeling isoexposure to transit users for market potential analysis

Transit operators face a difficult fiscal environment and an imperative to contribute to urban sustainability. Under these circumstances, operators must find innovative ways to make public transportation attractive to broader segments of the public, while simultaneously trying to raise revenue to reduce reliance on public subsidies. Development of commercial partnerships is seen as a promising way to achieve these goals. Previous research has examined the potential of using geodemographics to assist transit agencies in the task of identifying potential partners for developing mutually beneficial commercial agreements. In this paper we describe an approach to model isoexposure to transit users as a tool to assess market potential. The approach is based on the analysis of walking behavior of transit users, and specifically distance walked at the end of their transit trip. Spatial modeling is used to geographically project estimates of walking distance for a desired demographic profile at a specific transit facility. After expanding the estimates using sample weights, overlays of these estimates can be used to generate variations in exposure to transit travelers at different locations in space. The approach is demonstrated using the case of Metro users in Montreal, Canada. The case study demonstrates the use of isoexposure profiles as a novel approach to generate marketing intelligence. This should be of interest to transit agencies and businesses interested in developing partnerships.     

Quantifying the climate impact of emissions from land-based transport in Germany

Although climate change is a global problem, specific mitigation measures are frequently applied on regional or national scales only. This is the case in particular for measures to reduce the emissions of land-based transport, which is largely characterized by regional or national systems with independent infrastructure, organization, and regulation. The climate perturbations caused by regional transport emissions are small compared to those resulting from global emissions. Consequently, they can be smaller than the detection limits in global three-dimensional chemistry-climate model simulations, hampering the evaluation of the climate benefit of mitigation strategies. Hence, we developed a new approach to solve this problem. The approach is based on a combination of a detailed three-dimensional global chemistry-climate model system, aerosol-climate response functions, and a zero-dimensional climate response model. For demonstration purposes, the approach was applied to results from a transport and emission modeling suite, which was designed to quantify the present-day and possible future transport activities in Germany and the resulting emissions. The results show that, in a baseline scenario, German transport emissions result in an increase in global mean surface temperature of the order of 0.01 K during the 21st century. This effect is dominated by the CO₂ emissions, in contrast to the impact of global transport emissions, where non-CO₂ species make a larger relative contribution to transport-induced climate change than in the case of German emissions. Our new approach is ready for operational use to evaluate the climate benefit of mitigation strategies to reduce the impact of transport emissions.     

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.     

Measuring the performance of airport resilience to severe weather events

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.     

Scientific research about climate change mitigation in transport: A critical review

This paper seeks to develop a deeper understanding of the research on climate change mitigation in transport. We suggest that work to date has focused on the effects of improvements in transport technologies, changes in the price of transport, physical infrastructure provision, behavioural change and alternative institutional arrangements for governing transport systems. In terms of research methodologies, positivist and quantitative analysis prevails, although there are signs of experimentation with non-positivist epistemologies and participatory methods. These particular engagements with climate change mitigation reflect mutually reinforcing tendencies within and beyond the academic transport community. We first draw on a revised version of Thomas Kuhn’s philosophy of science to explore the path dependencies within transport studies, which are at least partly responsible for the predisposition towards quantitative modelling and technology, pricing and infrastructure oriented interventions in transport systems. We then employ the governmentality perspective to examine how transport academics’ engagements with climate change mitigation depend on and align with more general understandings of climate change in UK society and beyond. The analysis makes clear that ecological modernisation and neo-liberal governmentality more generally provide the context for the current focus on and belief in technological, behaviour change, and especially market-based mitigation strategies. While current research trajectories are important and insightful, we believe that a deeper engagement with theoretical insights from the social sciences will produce richer understandings of transport mitigation in transport and briefly outline some of the contributions thinking on socio-technical transitions and practice theories can make.     

Climate change modeling and the weather-related road accidents in Canada

The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents in the New Brunswick, Canada. We develop an Exposure to Weather-Accident Severity (EWAS) index multiplying accident and weather severity. The Negative Binomial Regression and Poisson regression models are applied to estimate the spatial–temporal relationship between the EWAS index and weather-related explanatory variables of road accidents. The regression results show that the surface-weather condition, weather, driver’s gender, weather-driver’s age, weather-driver’s experience, and weather-vehicle’s age have strong positive correlation with the EWAS index, while the surface-road alignment and surface-road characteristics have negative relationship with the EWAS index. The climate change model also indicates that the number of accidents declines during snowy and freezing days—most people stay at home and those who travel extra cautious—accidents do occur. The study suggests that the Road Safety Strategy 2015 of the Transport Canada should take a holistic approach to help minimize the incidences of severe road accident during the normal as well as hazardous weather conditions.     

Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks

Reliable and accurate short-term subway passenger flow prediction is important for passengers, transit operators, and public agencies. Traditional studies focus on regular demand forecasting and have inherent disadvantages in predicting passenger flows under special events scenarios. These special events may have a disruptive impact on public transportation systems, and should thus be given more attention for proactive management and timely information dissemination. This study proposes a novel multiscale radial basis function (MSRBF) network for forecasting the irregular fluctuation of subway passenger flows. This model is simplified using a matching pursuit orthogonal least squares algorithm through the selection of significant model terms to produce a parsimonious MSRBF model. Combined with transit smart card data, this approach not only exhibits superior predictive performance over prevailing computational intelligence methods for non-regular demand forecasting at least 30 min prior, but also leverages network knowledge to enhance prediction capability and pinpoint vulnerable subway stations for crowd control measures. Three empirical studies with special events in Beijing demonstrate that the proposed algorithm can effectively predict the emergence of passenger flow bursts.     

Accounting for emissions in the measurement of transit agency efficiency: A directional distance function approach

This paper uses a directional distance function approach to demonstrate the importance of considering a transit agency’s goal of reducing vehicular emissions as well as production of passenger or vehicle-miles, when measuring agency efficiency. This is especially critical given the increased emphasis policymakers may place on efficiency in the allocation of scarce public resources. The analysis includes 43 single mode US bus transit agencies for the year 2000. Results show only five agencies performing efficiently when emission abatement is not included in the analysis, but 22 firms are identified as efficient once emission abatement is considered. Consistent with previous studies, public agencies are found to be less efficient than private agencies, regardless of the efficiency measure used.     

Weather,transport mode choices and emotional travel experiences

With climate change high on the political agenda, weather has emerged as an important issue in travel behavioural research and urban planning. While various studies demonstrate profound effects of weather on travel behaviours, limited attention has been paid to subjective weather experiences and the psychological mechanisms that may (partially) underlie these effects. This paper integrates theoretical insights on outdoor thermal comfort, weather perceptions and emotional experiences in the context of travel behaviour. Drawing on unique panel travel diary data for 945 Greater Rotterdam respondents (The Netherlands), this paper aims to investigate how and to what extent weather conditions affect transport mode choices, outdoor thermal perceptions and emotional travel experiences. Our findings point out that observed dry, calm, sunny and warm but not too hot weather conditions stimulate cycling over other transport modes and – via mechanisms of thermal and mechanical comfort – lead to more pleasant emotions during travel. Overall, public transport users have less pleasant emotional experiences than users of other transport modes, while active mode users appear most weather sensitive. The theoretical contributions and empirical findings are discussed in the context of climate change and climate-sensitive urban planning.     

Understanding the Relationship Between Physical and Virtual Representations of Transit Agencies

Abstract

This study examines whether physical attributes of transit agencies, such as agency size, make a difference in how transit websites are designed, and how transit information is distributed. The objective of this study is to see if there is a relationship between physical and virtual representations of transit agencies. A rating instrument is developed for evaluating the quality of transit websites. Our findings suggest that transit agency size plays a key role in determining website quality: When the size of transit system is large, the information about the agency is too complex to be effectively presented on web pages. Thus, the quality of the large agencies’ websites is lower than medium-sized agencies. Instead, we find that large agencies attempt to design more user-friendly sites, and provide advanced information searching tools to compensate for low information quality. Policy implications for transit agencies are discussed.