In the race to achieve global climate neutrality, carbon intensive industries like the clinker and cement industry are required to decarbonize rapidly. The environmental impacts related to potential transition pathways to low-carbon systems can be evaluated using prospective life cycle assessment (pLCA). This study conducts a pLCA for future global clinker production, integrating long-term transition pathways from the IMAGE integrated assessment model (IAM) to maintain global consistency. It systematically modifies the ecoinvent v3.9.1 database using the Python library premise to create future database versions representing future clinker production embedded in a future economy according to a 3.5°C-baseline, a 2°C-compliant and a 1.5°C-compliant scenario. Our study indicates that climate change impacts of clinker production may decrease from about 1.03 kg CO2-eq/kg clinker in 2020 to 0.94 (3.5°C-baseline), 0.20 (2°C-compliant), and 0.16 (1.5°C-compliant) kg CO2-eq/kg clinker in 2060 for the global average. This corresponds to a 10% (3.5°C-baseline), 81% (2°C-compliant) and 84% (1.5°C-compliant) decrease by 2060 compared to 2020. Under these scenarios, global clinker production alone would require 5%–11% of the remaining end-of-century carbon budget for the 2 °C and 1.5 °C-target, respectively. While the climate change impacts are substantially reduced, our study also indicates that the transition pathways shift the burden towards other impact categories, such as ionizing radiation, ozone depletion, material resources and land use. Developing IAM-compatible scenarios for more product groups helps to increase the coherence of pLCA studies. As this study is based on an IAM heavily reliant on carbon capture and storage and bioenergy, future research should explore the effects of different technology pathways and alternative mitigation strategies.@en

Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.@en

Correction to: Nature Climate Change https://doi-org.tudelft.idm.oclc.org/10.1038/s41558-020-00949-9, published online 11 January 2021. In the version of this Article originally published, the colours in the scale bars in Figs. 1c and 2, Extended Data Figs. 2c and 4, and Supplementary Figs. 2c and 4 were inadvertently flipped such that they were shown as being blue to red, from left to right, but should have been red to blue. The online versions of the Article have been corrected and the Supplementary Information file has been replaced. The tick marks and values have not changed.@en

Renewable energy resources, which depend on climate, may be susceptible to future climate change. Here we use climate and integrated assessment models to estimate this effect on key renewables. Future potential and costs are quantified across two warming scenarios for eight technologies: utility-scale and rooftop photovoltaic, concentrated solar power, onshore and offshore wind energy, first-generation and lignocellulosic bioenergy, and hydropower. The generated cost–supply curves are then used to estimate energy system impacts. In a baseline warming scenario, the largest impact is increased availability of bioenergy, though this depends on the strength of CO2 fertilization. Impacts on hydropower and wind energy are uncertain, with declines in some regions and increases in others, and impacts on solar power are minor. In a future mitigation scenario, these impacts are smaller, but the energy system response is similar to that in the baseline scenario given a larger reliance of the mitigation scenario on renewables.@en