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Transport disruption through heat - damage costs

Figure 1 shows the estimated loss in million Euros due to heat related transport disruption for a set of 16 scenarios, ranked by order of magnitude (scenarios A-P, from least to most severe).
Explanation of the scenarios:

Jenkins et al. (2012) use the UKCP09 High Emissions scenario to perform 100 x 30 year runs for daily data for the 2040-2069 time period. These are binned into magnitude order - from least severe to most severe heat events - and one heat event is selected at random from each bin. This gives rise to 16 scenarios, ranked by order of magnitude as measured by the number of grid cells in the Greater London area which exceed the temperature threshold for a speed restriction to be applied (scenarios A-P, from least to most severe).

Figure 2 depicts estimated losses in million Euros due to heat related transport disruption for scenario P, the most severe, resolved by sectors.
Figure 3 presents net present value of losses, with a discount rate (i) varying between zero and 0.02 and a number of years until heat event (n) varying between 25 and 45, to account for the fact that the heat event can occur in any year between 2040 and 2069, roughly between 25 and 45 years from now.
General description:

We develop an economic cost methodology to assess the impact of specific climate change hazards through different channels of urban productive activity. We use the methodology to examine the impact of urban heat waves on transport disruptions leading to production losses across sectors of the city economy.

We define labour in terms of total quantity supplied per sector, where transport disruptions imply a decrease in time spent working. We define constant elasticity of substitution (CES) production functions for each sector that specifically encompass our estimated losses in total labour due to transport disruptions. The production functions are calibrated and aggregated at the city level according to specific weights given to each sector.

Transport disruption estimations for the UKCP09 High Emissions scenario to perform 100 x 30 year runs for daily data for the 2040-2069 time period are taken from Jenkins et al. (2012) and use information from the current transport configuration of rail, Tube, and DLR networks and 2001 Census. We evaluate the impact of one day of transport disruption on yearly GVA.