The role of inequality for the evaluation and policy response to climate change has received great attention in recent years. Yet, endogenizing the evolvement of inequality has so far not been addressed with standard IAMs widely used. We address this research gap by developing an inequality module based on household deciles and an optimization routine for each group of households. Capturing skill premia, capital income dynamics, and consumption heterogeneity including energy and food consumption, we are able to endogenously simulate the impact of carbon prices and other macroeconomic drivers on the evolvement of inequality consistent with the IAM socioeconomic and climate scenarios. Moreover, we validate the module by a hind-casting exercise and find broad consistence with observed inequality trends.@en

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.@en

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.

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Buildings are key in supporting human activities and well-being by providing shelter and other important services to their users. Buildings are, however, also responsible for major energy use and greenhouse gas (GHG) emissions during their life cycle. Improving the quality of services provided by buildings while reaching low energy demand (LED) levels is crucial for climate and sustainability targets. Building sector models have become essential tools for decision support on strategies to reduce energy demand and GHG emissions. Yet current models have significant limitations in their ability to assess the transformations required for LED. We review building sector models ranging from the subnational to the global scale to identify best practices and critical gaps in representing transformations toward LED futures. We focus on three key dimensions of intervention (socio-behavioral, infrastructural, and technological), three megatrends (digitalization, sharing economy, and circular economy), and decent living standards. This review recommends the model developments needed to better assess LED transformations in buildings and support decision-making toward sustainability targets.

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