Distribution of economic damages due to climate-driven sea-level rise across European regions and sectors – Scientific Reports

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Report on Economic Impacts of Climate-Driven Sea-Level Rise (SLR) in Europe

Abstract

This report investigates the economic consequences of sea-level rise (SLR) in Europe, focusing on regional and sectoral impacts. Utilizing a dynamic computable general equilibrium model and novel datasets, we estimate the distribution of economic losses and gains across various regions and sectors. A high-end SLR scenario suggests a GDP loss of 1.26% (€871.8 billion) for the EU and UK. However, some coastal regions may experience GDP losses of 9.56–20.84%, highlighting significant regional disparities. Inland regions might see small GDP gains (0–1.13%) due to displaced demand from coastal areas. The construction sector benefits from recovery efforts, while public services and industry face downturns. Prioritizing the recovery of critical sectors locally can mitigate massive regional GDP losses at negligible costs to the overall European economy. This analysis underscores the necessity for region-specific adaptation policies to address uneven geographic impacts and unique sectoral profiles.

Introduction

Climate change poses a global threat to economic development, with sea-level rise (SLR) being a significant concern due to its potential to impact coastal cities and regions where productive capital and populations are concentrated. In Europe, over 200 million people live within 50 km of the coastline, making them vulnerable to coastal flooding and economic disruption. Coastal regions contribute nearly 40% of the European GDP and handle 75% of Europe’s international trade volume through maritime routes. However, the exposure and vulnerability of these regions vary significantly, leading to asymmetric economic losses and indirect effects across the European economy.

Advanced assessments of SLR’s macroeconomic costs have predominantly been performed at aggregated levels, while local decisions on investments and climate change adaptation are crucial. This report goes beyond conventional analyses to explore direct and indirect economic consequences of SLR for EU and UK regions, differentiating between coastal and inland areas. We provide sector-specific damage estimates based on novel regional-level data, highlighting the importance of regionalized assessments for designing effective climate adaptation policies.

Methods

Model: EU-EMS

The EU Economic Modelling System (EU-EMS), developed by PBL Netherlands Environmental Assessment Agency, is a Spatial Computable General Equilibrium (SCGE) model that incorporates New Economic Geography (NEG) theory. It includes 62 global countries and 271 NUTS2 regions within the EU27 Member States plus the UK, covering 63 NACE Rev.2 economic sectors. The model captures spatial interactions like trade, factor mobility, and knowledge spillovers, making it suitable for assessing region-specific and sector-specific economic impacts of SLR.

Sectors in the Model

The model’s sectoral aggregation is based on the NACE Rev.2 classification, distinguishing between sectors directly impacted by SLR (e.g., agriculture, construction, transport) and those likely to incur indirect effects (e.g., industry, services). The analysis focuses on nine aggregated sectors: Agriculture, Industry (Capital), Industry (Rest), Construction, Utilities, Logistics, Transport, Private Services, and Public Services.

Asset-Based Distribution of Direct Damages Due to SLR

The ESPON-TITAN dataset provides NUTS3 level insights on direct and indirect economic losses due to natural hazards, including floods. We use this data to estimate damage distribution matrices (DDMs) for various asset classes (Residential, Commercial, Industry, Transport and Infrastructure, Arable Land) at the NUTS2 level. These DDMs are mapped to sectors in the CGE model to estimate direct damages to capital stock in each region.

Determining Sectoral Direct Damages Due to SLR

Direct damages to capital stock are calculated by applying DDMs to sector-specific capital stocks in each region. These damages are introduced as additional depreciation in the capital accumulation process, affecting available capital for production in subsequent periods.

Modelling Recovery Efforts Following SLR

The model includes an investment bank that allocates investment among sectors based on their relative returns to capital. Following SLR damages, investments are prioritized for recovering critical sectors (Public Services, Utilities, Transport, Logistics) to replicate real-world prioritization of critical infrastructure recovery.

Results

Regional Losses at the Coast Can Be an Order of Magnitude Larger Than National Losses

The high-end SLR scenario indicates a cumulative GDP loss of €871.8 billion by 2100 for the EU&UK, representing a 1.26% GDP loss compared with the baseline. Coastal regions face significant GDP losses (up to 20.84%), while inland regions may see small gains (0–1.13%) due to increased demand from impaired coastal production.

Coastal Regions Incur More Extreme Sectoral Impacts Than Inland Regions

Sectoral analysis shows that construction benefits from recovery efforts in coastal regions, while public services and other sectors face downturns. Inland regions experience more moderate changes across sectors due to shifting demand from coastal areas.

Sea Level Rise Triggers Sectoral Rearrangement of Both Coastal and Inland Regional Economies

SLR causes changes in the relative importance of sectors within regional economies. Construction generally sees an increase in value-added share across both coastal and inland regions due to heightened demand for public infrastructure investments. Public services experience a relative decline in most regions.

Targeted Recovery of Critical Sectors Substantially Reduces GDP Losses in Certain Regions

Prioritizing recovery investments in critical sectors locally can significantly reduce GDP losses in affected regions compared to a market-driven recovery approach. This targeted recovery has a negligible distortionary effect on the overall EU&UK economy but substantial regional impacts.

Discussion

This report highlights the spatially specific nature of SLR consequences and the importance of regionalized assessments for designing effective adaptation policies. Our novel methodology combines a regional SCGE model with detailed economic data on regional capital stocks and sector-specific physical impacts, providing a bottom-up assessment of total macroeconomic consequences of SLR.

Our findings reveal significant regional disparities in economic impacts, with coastal regions facing substantial losses while inland regions may benefit from increased demand. The results underscore the need for integrated climate adaptation policies that align with economic and social cohesion objectives.

Future research should focus on assessing the effectiveness of public and private adaptation measures in diminishing SLR impacts and exploring scenarios of drastic relocation of capital and labor across regions and sectors.

Data Availability

The datasets generated during this study are available in the Zenodo repository: https://zenodo.org/records/10058720. The SLR data used from the COACCH project are available at: SDGs Targets Indicators SDG 13: Climate Action Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.
Target 13.2: Integrate climate change measures into national policies, strategies, and planning. GDP losses due to SLR
Regional disparities in economic impacts SDG 11: Sustainable Cities and Communities Target 11.5: Significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global GDP caused by disasters.
Target 11.B: Substantially increase the number of cities adopting integrated policies towards climate resilience. GDP losses due to SLR
Regional disparities in economic impacts SDG 9: Industry, Innovation, and Infrastructure Target 9.1: Develop quality, reliable, sustainable, and resilient infrastructure. Infrastructure recovery in critical sectors SDG 8: Decent Work and Economic Growth Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading, and innovation. Sectoral Value Added (VA) changes due to SLR impacts

The analysis highlights the interconnectedness of climate change impacts with various SDGs, emphasizing the need for integrated policies that address both environmental sustainability and economic resilience.

Fuente: nature.com

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