T. Chatzivasileiadis
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Mediterranean tree crops provide land-based mitigation services by storing carbon long-term in soil and wood. However, their mitigation potential has often been overlooked due to the lack of robust, context-specific estimates. This limits the development of targeted policies to support farmers involved in “carbon farming”—the use of agricultural practices to enhance CO2 absorption. This study presents a model-based carbon accounting framework for assessing the climatic and economic benefits of agriculture-based mitigation in Mediterranean tree crop ecosystems. The approach does not rely on extensive field monitoring as its primary data source; however, it is calibrated and validated against targeted field measurements and experimental datasets generated within the LIFE CLIMATREE project, which constitute the validation basis of the analysis. The framework quantifies carbon removals and emissions under three management scenarios, ranging from business-as-usual practices to mitigation-rich management. Across representative Mediterranean countries and tree crops, mitigation-rich practices result in additional removals of approximately 1–2.5 t CO₂ ha⁻¹ yr⁻¹, with considerable variation across crop types and regions. These additional removals translate into meaningful economic values when assessed using indicative carbon prices, highlighting the potential contribution of tree crop management to climate action and agricultural sustainability. The findings support the development of carbon markets, eco-labeling, and agri-environmental schemes under the new Common Agricultural Policy. They also contribute to improving the accuracy of national GHG inventories in the LULUCF sector, which currently do not differentiate between orchard species or management practices. This evidence base is essential for shaping more effective climate policies and incentivizing sustainable land use.
Amid escalating climate impacts, understanding private sector adaptation is critical. Here using data of actual adaptation expenditures from nearly 300,000 businesses in five coastal regions, we reveal variations in private sector adaptation across sectors and regions. The agriculture sector leads in adaptation efforts, while transport, construction and utilities—that is potential sources of system-wide cascading effects—lag. Small, medium and large businesses prioritize hard and soft measures, barely investing in ecosystem-based adaptations. Adding to the multifaceted discourse on adaptation effectiveness, our panel data reveal positive, although inelastic in the short run, relationships between private sector adaptations and aggregate regional economic performance. Business adaptations in the construction, transport and health sectors associate positively with regional economic performance, with the accommodation and food services sector yielding the highest return per euro invested in adaptation. Combining these findings with existing assessments of adaptation could support the development of societally effective adaptation strategies.
The power of bridging decision scales
Model coupling for advanced climate policy analysis
Climate policy faces increasingly complex challenges that span multiple human decision scales in nature-society systems. Contemporary climate policy models, while valuable and increasingly versatile in handling spatial and temporal scales, struggle to capture interacting multiscale decisions on the socioeconomic side. This perspective draws attention to the power of coupling among different modeling families, taking integrated assessment models (IAM), computable general equilibrium models (CGE), and agent-based models (ABM) as examples. Recent computational advances, maturity of models, availability of data, and interdisciplinary expertise make model coupling an increasingly feasible, effective, and useful tool for climate policy analysis. We examine the unique contributions of each modeling approach, highlight synergies from uniting their strengths, and discuss alternatives to and conditions for coupling. In addressing methodological challenges, we present examples of effective coupling of IAM-ABM-CGE, emphasizing the importance of maintaining model integrity while enhancing policy relevance. By bridging human decision scales and leveraging complementary strengths, coupled models can provide nuanced insights into climate-economy interactions, ultimately supporting effective and equitable-not just efficient and optimal-climate policies.
Climate-induced hazards are becoming more frequent and severe, causing escalating economic losses worldwide. Consequently, climate change adaptation is increasingly necessary to protect people, nature and the economy. However, little is known about who is adapting and how much they spend on adaptation measures, especially in the private sector. This article focuses on firms—the backbone of economic development, yet understudied in climate adaptation research. Here we present insights from a unique panel dataset detailing businesses’ adaptation investments across 28 European countries (2018–2022), 5 hazard types, and 19 economic sectors. Our descriptive analysis reveals low but increasing adaptation investments across Europe (0.15–0.92% of national gross domestic product, annually increasing by 30.6–37.4%). Moreover, we highlight considerable differences in adaptation intensity across sectors, including low adaptation intensity in manufacturing and retail trade. Additionally, our econometric analysis indicates that public adaptation spending crowds in private investments in adaptation, highlighting opportunities to facilitate autonomous adaptation.
Economic costs of climate change are conventionally assessed at the aggregated global and national levels, while adaptation is local. When present, regionalised assessments are confined to direct damages, hindered by both data and models’ limitations. This article goes beyond the aggregated analysis to explore direct and indirect economic consequences of sea level rise (SLR) at regional and sectoral levels in Europe. Using a dynamic computable general equilibrium model and novel datasets, we estimate the distribution of losses and gains across regions and sectors. A comparison of a high-end scenario against a no-climate-impact baseline suggests a GDP loss of 1.26% (€871.8 billion) for the whole EU&UK. Conversely our refined assessments show that some coastal regions lose 9.56–20.84% of GDP, revealing striking regional disparities. Inland regions grow due to the displaced demand from coastal areas, but the GDP gains are small (0–1.13%). While recovery benefits the construction sector, public services and industry face significant downturns. We show that prioritising recovery of critical sectors locally reduces massive regional GDP losses, at negligible costs to the overall European economy. Our analysis traces regional economic restructuring triggered by SLR, underscoring the necessity of region-specific adaptation policies that embrace uneven geographic impacts and unique sectoral profiles to inform resilient strategy design.