ALBERT

Description: This document provides technical information on the two datasets behind the NGFS scenarios. It is intended to answer technical questions for those who want to perform analyses on the datasets themselves. It is an update of the Technical Documentations published in June 2020 and 2021 alongside the first two sets of NGFS Scenarios. It is therefore aligned with the third set of NGFS Scenarios, released in September 2022.

Description: Economic development in sub-Saharan Africa has increased carbon emissions and will continue to do so. However, changes in emissions in the past few decades and their underlying drivers are not well understood. Here we use a Kaya decomposition to show that rising carbon intensity has played an increasingly important role in emission growth in sub-Saharan Africa since 2005. These changes have mainly been driven by the increasing use of oil, especially in the transportation sector. Combining investment data in the power sector with economic and population projections, we find that investments in new coal-fired capacity may become a major driver of future carbonization. Our results highlight the importance of making low-carbon technologies available and financially attractive to sub-Saharan African countries to avoid a lock-in of emission-intensive energy use patterns.

Description: This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.

Description: Scenarios from integrated assessment models play a central role in helping policymakers envisage pathways to limit global warming to well below 2 °C. We demonstrate that many models maintain a preference for inefficient combustion, in particular by relying on coal and bioenergy. In contrast to recent evidence from innovation studies, scenarios are optimistic on deployment of lumpy energy-systems technologies, such as carbon capture and storage, while insufficiently reflecting empirically observed innovation dynamics in more granular technologies such as solar photovoltaics. Our analysis shows that two key options for rapid decarbonization remain systematically undersampled in models that underpin IPCC scenarios: A) strong growth in intermittent renewables, in particular solar PV, together with electrification of sectors; and B) widespread adoption of efficient end use technologies enabling high service provision at low levels of energy demand. A combination of continued PV growth and sector coupling with low to medium energy demand (a corridor of 250 to 500 EJ of primary energy) would render carbon neutrality by 2050 feasible, thus enabling near-term cost-effective climate change mitigation and reducing the need for carbon dioxide removal in the 2nd half of the century. Models would benefit from updated cost assumptions, higher resolution on granular end-use technologies, higher resolution on sector coupling, and an overall consideration of demand-side solutions. Such updates – of which some are starting to be explored by modeling teams - are likely to demonstrate that some mitigation pathways are cost saving, rather than costly.

Description: A rapid phase-out of unabated coal use is essential to limit global warming to below 2°C. This review presents a comprehensive assessment of coal transitions in mitigation scenarios consistent with the Paris Agreement, using data from more than 1500 publicly available scenarios generated by more than 30 integrated assessment models. Our ensemble analysis uses clustering techniques to categorize coal transition pathways in models and bridges evidence on technological learning and innovation with historical data of energy systems. Six key findings emerge: First, we identify three archetypal coal transitions within Paris-consistent mitigation pathways. About 38% of scenarios are ‘coal phase out’ trajectories and rapidly reduce coal consumption to near zero. ‘Coal persistence’ pathways (42%) reduce coal consumption much more gradually and incompletely. The remaining 20% follow ‘coal resurgence’ pathways, characterised by increased coal consumption in the second half of the century.. Second, coal persistence and resurgence archetypes rely on the widespread availability and rapid scale-up of carbon capture and storage technology (CCS). Third, coal-transition archetypes spread across all levels of climate policy ambition and scenario cycles, reflecting their dependence on model structures and assumptions. Fourth, most baseline scenarios – including the shared socio-economic pathways (SSPs) - show much higher coal dependency compared to historical observations over the last 60 years. Fifth, coal-transition scenarios consistently incorporate very optimistic assumptions about the cost and scalability of CCS technologies, while being pessimistic about the cost and scalability of renewable energy technologies. Sixth, evaluation against coal-dependent baseline scenarios suggests that many mitigation scenarios overestimate the technical difficulty and costs of coal phase- outs. To improve future research, we recommend using up-to-date cost data and evidence about innovation and diffusion dynamics of different groups of zero or low-carbon technologies. Revised SSP quantifications need to incorporate projected technology learning and consistent cost structures, while reflecting recent trends in coal consumption.