Oceans provide essential benefits to people and the economy, underpinned by the extent and condition of marine ecosystems and infrastructure—or ‘blue’ capital. However, the impacts of climate change on blue capital have been largely overlooked in influential indicators such as the social cost of carbon (SCC). Here we integrate the latest ocean science and economics into a climate-economy model, capturing climate change impacts on corals, mangroves, seaports, fisheries and mariculture to estimate their welfare repercussions at a global scale. Conceptually, this ocean-based SCC (blue SCC) represents a component of the total SCC currently omitted in standard estimates. We estimate the 2020 blue SCC to be US$48 per tCO₂ (US$38–70, 25th–75th percentile) with baseline discounting, representing an almost doubling of the SCC estimate from the same model without considering ocean-related impacts. The blue SCC increases to US$168 for a discount rate of 2%.

Climate change and inequality are critical and interrelated issues. Despite growing empirical evidence on the distributional implications of climate policies and climate risks, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. Here we fill this gap through an ensemble of eight large-scale integrated assessment models that belong to different economic paradigms and feature income heterogeneity. We quantify the distributional implications of climate impacts and of the varying compensation schemes of climate policies compatible with the goals of the Paris Agreement. By 2100, climate impacts will increase inequality by 1.4 points of the Gini index on average. Maintaining global mean temperature below 1.5 °C reduces long-term inequality increase by two-thirds but increases it slightly in the short term. However, equal per-capita redistribution can offset the short-term effect, lowering the Gini index by almost two points. We quantify model uncertainty and find robust evidence that well-designed policies can help stabilize climate and promote economic inclusion.

In this work, we systematically analyse the population projections used in the emissions scenario ensembles reviewed by the Working Group III in the latest three reports of the Intergovernmental Panel on Climate Change (IPCC). We show that emissions scenarios span smaller demographic uncertainties than alternative estimates both for the world and for critical regions, such as South-East Asia, Sub-Saharan Africa, and China. Furthermore, the range of demographic projections has consistently shrunk over subsequent reports, exposing a problematic convergence towards a single socio-economic pathway: the “middle path” or SSP2. We argue that the undersampling of population uncertainties limits the range of future emission trajectories and has implications for climate transition scenarios. Emissions scenarios with a wider set of assumptions about future population should be submitted to the IPCC. The methods utilised in this study inform the development of independent audit methods for the assessment of relevant uncertainty sources in IPCC databases.