Using a Monte Carlo framework for assessing future costs of major transport disruptions from seldom occurring natural hazards

A prototype tool (DynEcon) for dynamic societal cost benefit analyses was used to produce simple estimates of future costs of traffic disruption caused by one or more rail and road bridge failures from 100-year flooding(s) in the Santarem Region. The focus was on quantification of different types of consequences. A project period until year 2100 was chosen to include adverse events in the far future. Future private and professional vehicle flows before and after disruptions were calculated for 36 scenarios considering declining rural and semi-rural populations destinations and increasing GDP over time. Potential cascading effects from detours and mode transfer at future time points were estimated. The additional fuel and vehicle costs for personal cars and trucks, time losses for professional and private drivers, and external costs for rural and semi-rural population subjected to increased traffic were estimated. The sizes of these costs, depend on the size and composition of the vehicle fleets at time of each disruption. Local and global emissions from fossil fuels the next twenty years will be reduced as the older most polluting vehicles in the vehicle fleets are phased out and newer vehicles must satisfy even more stringent emission and design standards. In addition, EC greening policies and electrification will reduce the amounts of combustion related pollutants dramatically. Prices of Diesel and Petrol were assumed to increase over time. The costs of accidents have decreased due to improved protection from the vehicles and is predicted to continue to decrease due to more intelligent vehicles and smart road infra-structure. Noise, air-pollution due to road wear, and road maintenance costs per km were assumed to remain stable. Costs of CO2-emissions and time delay costs of private and professional drivers were modelled as increasing over time. The additional disability-adjusted life years(DALYs) from local air pollution and noise, were estimated using exposure effect relationships and DALY impact estimates from WHO. A monetary DALY-value was assigned, and the sum costs calculated. To harmonize cost estimates for Portugal having a lower GDP than Norway, costs were scaled down.

The dynamic cost benefit tool applies Monte Carlo simulations in a two-step procedure. In the first step a population of e.g. 1000 sets of 100-year flooding events occurring between 2021 and 2100 are generated using knowledge on climate change, flooding characteristics, scour etc. Future annual costs until 2100 are generated using growth models. Since all parameters and growth models are associated with uncertainties, the second step derives the uncertainty distribution of economic result indicators and confidence intervals. An online web-based Monte Carlo framework such as DynEcon could enable researchers to cooperate on different parts of the patchwork necessary for analyses of resilience policies that include hazards occurring late century.