International Institute for Applied Systems Analysis

Abstract. HTAP3-OPNS is a multi-model exercise designed to support the revision of the Gothenburg Protocol under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). Using an ensemble of Chemical Transport Models (CTMs) and Chemistry-Climate Models (CCMs), this study investigates the long-range transport and impacts of ground-level ozone, particulate matter (PM), and nitrogen and sulphur deposition across different global regions. The project aims to assess the contributions of regional versus extra-regional emission sources, evaluate the suitability of current models, and project changes in air pollution under future emission scenarios and climate conditions. A series of perturbation simulations will enable the development of an ensemble emulator to explore and evaluate potential mitigation strategies efficiently. This paper outlines the scientific and policy questions motivating the study, describes the experimental design, including input datasets, model configurations, and required outputs, and discusses methodologies for data handling and analysis. The results will provide crucial insights for policy decisions aiming to improve air quality, protect human health, and protect ecosystems worldwide.

The 2023 UAE Consensus (COP28) marked a watershed in global climate governance, committing parties for the first time to “transition away from fossil fuels in energy systems.” Yet the text’s constructive ambiguity leaves the operational content of this commitment uncertain. Four categories of ambiguity emerge: whether transitioning away applies uniformly globally or presupposes differentiated regional responsibilities; whether “net zero energy systems” encompasses industrial processes or only energy supply and demand; whether “mid-century” net zero must be achieved exactly by 2050 or permits some delay; and whether net zero refers to CO2 alone or all GHG. Here we assess whether any plausible interpretation permits policy retrenchment. We benchmark COP28 commitments against IPCC AR6 1.5°C-consistent pathways and develop bespoke scenarios using the MESSAGEix-GLOBIOM integrated assessment model to stress-test each ambiguity dimension. We find that targets for tripling renewable capacity and doubling energy efficiency exceed the median of cost-optimal pathways assessed by the IPCC. Across all tested configurations, reduced fossil fuel output dominates emission reductions (>90%), with carbon capture and storage serving a strictly secondary role (

Organic soils contain nearly one-third of the world’s soil carbon, despite covering only 3-4% of the global land surface. Their degradation releases large quantities of greenhouse gases (GHGs) and reduces ecosystem functions, including biodiversity support. The European Union (EU) is the second-largest global emitter of GHGs from drained organic soils after Indonesia. Although organic soils under agricultural use represent only about 2% of the EU’s total agricultural area, they are responsible for approximately 80% of Cropland and Grassland emissions released to the atmosphere. Restoring drained organic soils therefore represents a significant opportunity for achieving climate change mitigation targets in the EU. However, the economic mitigation potential of organic soil restoration remains insufficiently explored, as existing studies do not consider restoration beyond full rewetting and rarely assess potential synergies with economic incentives and restoration targets. In this study, we apply GLOBIOM-EU, an economic land-use model, to comprehensively assess the economic climate mitigation potential from restoring drained organic soils used for agriculture considering multiple restoration measures: full rewetting, rehabilitation, and paludiculture. Our results indicate that under a GHG price of 100 EUR per tCO2 equivalent (EUR tCO2e-1), 38.2-44.4 MtCO2 equivalent per year (MtCO2e yr-1) could be mitigated in 2050. Paludiculture emerges as a promising option, substantially increasing the attractiveness of rewetting organic soils; under conditions of high demand for paludiculture products, 2 million hectares of drained organic soils could be restored without additional climate mitigation incentives, delivering mitigation of approximately 17 MtCO2e yr-1 by 2050. Moreover, meeting the 2050 targets of the EU Nature Restoration Regulation (NRR) alone could mitigate 23-29% of current emissions from drained agricultural organic soils in the EU. Overall, our findings suggest that the greatest climate benefits would be achieved through the combination of restoration measures that balance mitigation potential, economic viability, and land-use competition under different policy and market conditions, while also enabling opportunities for biodiversity co-benefits. This highlights the importance of integrated policy frameworks that align climate mitigation, ecosystem restoration, and market incentives.

Warming-induced greenhouse gas emissions from permafrost constitute a major uncertainty in assessments of Earth system stability, remaining carbon budgets, and the feasibility of long-term climate targets. While gradual permafrost thaw is represented in several complex Earth system models, abrupt thaw processes such as thermokarst development and active-layer detachment remain absent, despite their potential to generate rapid and substantial emissions. Here, we quantify the contribution of both gradual and abrupt permafrost thaw to CO2 and CH4 emissions and associated climate risks using the compact Earth system model OSCAR, extended with a newly implemented inventory-based module for abrupt permafrost thaw dynamics. Probabilistic projections of global temperature, sea-level rise, and direct economic damage costs are enabled across seven state-of-the-art scenarios from the Network for Greening the Financial System.Our results show that permafrost carbon feedback introduces pronounced nonlinearities into climate outcomes. Risks associated with gradual thaw scale closely with global warming, whereas abrupt thaw exhibits complex, scenario-dependent effects that disproportionately influence upper-tail risks. These findings suggest that neglecting permafrost thaw may lead to systematic underestimation of tail risks. By explicitly linking permafrost thaw processes to climate risk metrics, this study contributes to reducing a key blind spot in climate‑impact assessments.

Accurate estimates of land-use change CO2 fluxes (FLUC) are essential for understanding the terrestrial carbon cycle and for informing national and global climate reporting. FLUC can be quantified using a range of approaches, including bookkeeping models, dynamic global vegetation models (DGVMs), national greenhouse gas inventories, Earth observation-based products, and atmospheric inversions. However, systematic comparison of FLUC estimates across approaches remains challenging due to fundamental methodological differences. Additionally, individual approaches are often associated with substantial uncertainties.Here, we provide an overview of the main sources of uncertainty and methodological discrepancies across approaches, while highlighting recent advances and identifying promising directions to further harmonize and improve FLUC estimates. Key sources of uncertainty and inconsistency include differing objectives and definitions across approaches, differences in the separation of natural and anthropogenic drivers (leading to FLUC differences of up to 2.8 PgC yr-1), incomplete process representation (contributing up to 30% uncertainty in FLUC), uncertainties in land-use data (up to 30% uncertainty), and constraints related to spatial resolution. At the same time, several important methodological improvements have been achieved recently, including the consideration of environmental changes in bookkeeping-based FLUC estimates and the correction for replaced sinks and sources (RSS) in DGVM-based FLUC estimates. Ongoing research projects are addressing several remaining challenges, including the improvement of regrowth estimates, the quantification of disturbance impacts, and the consolidation and harmonization of different land-use datasets. These developments build primarily on combining high-resolution Earth observation-based databases with the flexibility and traceability of semi-empirical modelling. Together, these advances provide an important contribution towards more consistent and robust estimates of land-use change CO2 fluxes within and across approaches.

Due to insufficient climate action to date, the world is on track to exceed 1.5°C of global warming in the coming decade. Stringent climate action towards net zero, followed by continued net negative carbon emissions, may allow temperatures to be brought back below that level after a prolonged period of climate overshoot. Even if global mean temperatures are reversed, how such overshoot shapes regional climate patterns in the long term remains poorly understood. Here, we investigate the long-term effects of climate overshoot using explainable machine learning models to identify persistent and reversible changes in regional temperature patterns for ensembles of two different overshoot scenarios until 2300. Our approach allows for robust detection of statistically significant differences on the regional level. We address three questions: (1) which regional temperature distributions return to their pre-overshoot state, (2) which stabilize at altered conditions, and (3) how distinguishable high overshoot and low overshoot pathways remain up to 2300. To complement the machine learning analysis, we apply principal component analysis to compare pre- and post-overshoot climate states and assess their degree of convergence. Our analysis provides a methodological framework to detect climate reversibility and stabilisation on the regional level, highlighting where long-term changes persist despite global temperature decline.

As the Intergovernmental Panel on Climate Change (IPCC) enters its seventh assessment cycle (AR7), the scientific community faces a pivotal moment of reflection regarding the role of global modelled scenarios in shaping the international climate policy landscape. The Sixth Assessment Report (AR6) highlighted pathways toward the Paris Agreement but also surfaced tensions between cost-optimal global scenarios and heterogeneous levels of national development, mitigation capabilities, and historical responsibilities for climate change. This invited presentation frames the session by interrogating current approaches to justice in climate mitigation research and proposes a research agenda for its transformation.We first establish a typology of justice-related critiques on the current generation of scenarios. This typology distinguishes between three interrelated dimensions of the modelling process. Structural limitations of the research culture pertain to the geographic and disciplinary concentration of modelling expertise in the Global North, specifically in Europe, North America, and Japan, which has historically privileged certain epistemological contexts while perspectives from Low- and Middle-Income Countries (LMICs) and Small Island Developing States (SIDS) remain underexplored. This lack of diversity shapes narratives constructed and solutions deemed feasible. Next, we discuss methodological biases inherent in model architectures. Standard modelling approaches privilege scenarios that allocate high mitigation burdens to regions with high technical mitigation potential but low institutional and financial capacity, effectively neglecting the principle of common but differentiated responsibilities and respective capabilities. These choices effectively prioritise technoeconomic efficiency over intergenerational and interregional equity. Finally, we discuss epistemological boundaries limiting the breadth of indicators relevant to informing national policy, and the limited contextualisation of scenario outputs within heterogenous policy regimes that face differentiated costs of capital and risks.Responding to these challenges, we propose a tiered research agenda designed to integrate considerations of justice into scenario design and use. Tier one advocates for incremental refinements within existing frameworks. This includes improving the transparency of model inputs, downscaling global results to policy-relevant national scales and for relevant indicators, and systematically integrating climate impacts and loss-and-damage considerations. Tier two calls for more fundamental advancements in scenario frameworks, including emerging work that replaces blind economic growth narratives with convergent pathways centred on Decent Living Standards (DLS) and multidimensional well-being. This involves reconceptualization of the solution space to prioritize demand-side transformations, sufficiency-based lifestyles, and protection of ecological thresholds that support both human and non-human life. We also emphasize the need for scenarios that explicitly model effort-sharing principles from the outset, incorporating differentiated carbon budgets and international climate finance flows as internal model objectives rather than ex-post calculations. Tier three focuses on procedural justice through participatory co-production. We argue that the legitimacy of future scenarios depends on the sustained engagement of a broader set of stakeholders, including social scientists, humanities scholars, and frontline communities, in the design and interpretation of narratives. This shift requires institutional reforms to support modelling capacity in the Global South and to move beyond tokenistic consultation toward genuine co-production of knowledge.While models cannot fully capture equity and justice, strengthening them is essential to inform just collective action.

Glaciers in the Danube Basin are projected to disappear almost entirely by 2100. This study quantifies both the trajectory of glacier loss and its hydrological consequences across the basin.The Open Global Glacier Model (OGGM) is employed, driven by downscaled and bias-corrected meteorological forcing from multiple CMIP6 General Circulation Models to simulate the evolution of 800 glaciers from the Randolph Glacier Inventory 6.0 across three SSP-RCP scenarios. Results indicate substantial glacier loss across all scenarios, with most of the glaciated area disappearing by 2060. Even under the optimistic SSP1-2.6 pathway, only a minor fraction of glacier area and volume persists through 2100.To assess the hydrological consequences of glacier retreat, the hydrological model Community Water Model (CWatM) is used. CWatM is calibrated for the entire Danube basin at 645 discharge stations, with daily temporal and one arcminute spatial resolution, incorporating glacier runoff contributions derived from OGGM. Paired simulations are conducted with and without glacier runoff to quantify the contribution of glacier runoff to river streamflow using historical meteorological forcing (1990–2020). Additionally, an attribution analysis is performed comparing the hydrological regime under glacier runoff with that under non-glaciated conditions in presently glaciated areas.This study reveals the spatial and temporal patterns of glacier decline and demonstrates how glacier runoff contribution and attribution evolve along the Inn, Drau, and Danube rivers from headwaters to the river mouth, providing insights into the changing water balance of the Danube.

Extreme heat is among the deadliest meteorological hazards and poses an increasing threat to human health and socioeconomic systems, including labor productivity.Here, we present global and regional projections of population exposure to extreme heat stress and associated labor productivity losses across a range of emissions scenarios from the Shared Socioeconomic Pathways (SSPs) and NGFS (Network for Greening the Financial System), which are widely employed in private and financial sector risk assessments.Robust projections of heat stress impacts require climate data that accurately represent temperature and humidity conditions during the hottest hour of the day, when physiological strain typically peaks. To this end, our analysis builds on a newly derived global dataset of future changes in the Heat Index (HI), a widely used metric of human heat stress integrating the combined effects of temperature and humidity, with enhanced temporal accuracy. Sub-daily relative humidity during the hottest hour is reconstructed from ISIMIP3 daily near-surface specific humidity using a physically and statistically consistent correction framework, enabling a more realistic representation of peak heat stress than standard ISIMIP3 humidity output.Our results reveal pronounced hotspots of intensifying heat stress and labor productivity losses in densely populated low-latitude regions, including South Asia and West Africa, that are strongly dependent on labor-intensive sectors. In these regions, most projected heat-related productivity losses could be avoided by limiting global warming to 1.5 °C.