Quantifying the Economic Losses From Transport Demand Disruption Due to Climate Change

The increasing frequency and severity of weather events shaped by climate change are expected to have an escalating impact on the operation and, in turn, the generalised costs of the transportation system in the coming decades. This disruption will be caused by a plethora of both direct and indirect impacts of worsening climate measures on transport supply and demand. Direct impacts take the form of climate extremes which have an immediate impact on the ability of the transport network to serve demand, such as excessive rainfall reducing visibility and slowing travel speeds, infrastructure failures from excessively hot temperatures (e.g., rail buckling) or river and coastal flooding preventing travel along certain critical routes. Indirect measures are a step removed from their direct counterparts and disrupt demand due to issues such as agricultural produce changing the origin of supply, or changes in tourist destinations resulting in a shift in transport demand. Focusing on transport supply, these types of weather events which render infrastructures unusable will induce added travel time through rerouting, thus increasing the cost of freight goods due to an additional cost to transport, and increasing the cost to passengers through additional fuel costs and lost time. There have been a number of studies projecting the effects of future adverse climate conditions on transportation infrastructure (Cochran 2009; Nemry and Demirel 2012; Schweikert, Chinowsky et al. 2014), although few studies have analysed the increased generalised costs due to the causal effects of modal shifting and increased travel time on the transport system from these direct and indirect impacts. This study aims to bridge this gap in the literature by quantifying the economic impact of adverse climate change measures on transport demand under a range of climate scenarios using a multi-model approach. Firstly, detailed climate and physical impacts data from projected extreme events are taken from individual impact models under the Joint Research Centre's PESETA project. These impacts quantify extreme events such as sea level rise, river flooding, and droughts performed under climate projections consistent with the high-end emission scenario (Representative Concentration Pathway RCP8.5). Next, these impacts are overlaid on the transport network to identify the damage to the transport system – this step, together with data from demand (by origin-destination pairs and by mode), allows the authors to carry out a transport assignment and evaluate the disruptions to the transport system relative to a baseline due to these climate impacts. For example, a rising sea level may inundate a critical coastal road requiring a modal shift to an unaffected transport mode or, alternatively, a rerouting of transport. Indirect climate related impacts on the transport system, such as shifts in the origin of agricultural produce, are also taken from an impact assessment model to analyse the disturbance to the transport system. The authors quantify the generalised cost of these climate events across all modes of transport, (i.e., road, rail, navigation, and aviation) for 6 European countries covering a range of different typologies (UK, Netherlands, Germany, Austria, Italy, Slovenia) over a time horizon of 2015 to 2050.

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  • Supplemental Notes:
    • Abstract used by permission of Association for European Transport.
  • Corporate Authors:

    Association for European Transport (AET)

    1 Vernon Mews, Vernon Street, West Kensington
    London W14 0RL,    
  • Authors:
    • Mulholland, Eamonn
    • Navajas-Cawood, Elena
    • Christodoulou, Aris
    • Feyen, Luc
    • Ciscar-Martinez, Juan Carlos
  • Conference:
  • Publication Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Pagination: 15p
  • Monograph Title: European Transport Conference 2019

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Filing Info

  • Accession Number: 01751290
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 20 2020 3:22PM