Estimating the carbon footprint of post-flood urban road network restoration: A case study in Carlisle

Climate change and urbanization are expected to increase the risk of flood disasters in vulnerable areas. Urban road infrastructure can be affected by flooding, and subsequent restoration creates an additional carbon emission burden. These emissions are likely to compromise local decarbonization efforts, but there remains a lack of tools for quantifying the environmental impact of reconstruction projects after disasters. This study aims to develop an assessment framework to reveal the carbon footprint of post-flood road network restoration projects. The model integrates flood simulation, pavement damage evaluation, and carbon footprint calculation modules. This paper introduces nine flood scenarios ranging from 2-year to 1000-year events and a case study in Carlisle, UK, to test the integrated model. Results of the scenario simulation indicate that the carbon emissions from restoring per unit length of pavement as the flood magnitude increases for both main roads (10.46-19.21 kgCO₂e) and low-volume roads (5.34-10.17 kgCO₂e). Moreover, the case study indicates that the urban road network layout may significantly influence the general carbon footprint of post-flood pavement restoration. The carbon emissions from only restoring the main body of damaged pavements after this 70-hour disaster are estimated to offset almost 1% of the local decarbonization achievement for a month. Indirect carbon footprints from material production (67%) and delivery (29%) are much higher than direct emissions from on-site tasks (4%). Measures such as optimizing pavement materials, reusing wastes, rationalizing delivery routes, and improving the city layout help alleviate the burden of recovery. This study reflects on the environmental costs of disaster recovery processes, with a view to supporting improved mitigation strategies. The integrated modeling framework can also be applied to cities in different contexts to enrich reference for decision-making.