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Background: The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results: The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions: This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

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.

This dataset compiles diagnostic scenarios from several Integrated Assessment Models (IAM) and Energy System Models (ESM) to facilitate systematic comparison of a broad range of results across these models. These diagnostic scenarios were developed in the Horizon 2020 project ECEMF (https://ecemf.eu). Visit the ECEMF Scenario Explorer hosted by IIASA at https://data.ece.iiasa.ac.at/ecemf for more information and interactive user interface to work with the scenario data.

This dataset contains the parameterization of a no-policy baseline scenario of the global 11-regional MESSAGEix-GLOBIOM integrated assessment model. Regions, time periods, commodities, technologies and relations included in this model are described in a separate repository. The dataset relies on the MESSAGEix modeling framework (Huppmann et al. 2019) and can be imported into MESSAGEix via the read_excel() functionality for which a tutorial is available. After the import the scenario can be solved and modified to create new scenarios. Note that the published scenario as included in the ENGAGE global scenarios dataset has been run with a release candidate of version 3.4.0 of MESSAGEix.

Energy enables the functioning of modern society. However, humanity’s reliance on fossil fuels since the industrial revolution has contributed to many societal problems including climate change, environmental degradation and pollution, and the transition to a renewable and carbon-free energy system is one of the grand challenges for the 21st century. The aim of this editorial is to outline the importance of a fast and transparent sharing of energy research and discuss key themes of the Energy Gateway of F1000Research.

The core objective of this work is to downscale the cost-effective heat supply of different European decarbonization scenarios generated by the aggregate model GENeSYS-MOD from the national to the community level in Austria and thus disclose the heat density of district heating in 2050. We assume that district heating encompasses geothermal, synthetic gas, hydrogen, waste, and large-scale heat pumps as renewable heat sources. The results determine district heating in 68 Austrian communities in Austria in 2050, which corresponds to 6% of the total number of communities. We find that GENeSYS-MOD results are capable in covering local trends in district heating since high shares of the projected heat densities at the local levels achieve values indicating economic viability. Further research should follow on how locally determined district heating and heat densities could be returned into more aggregate models, such as GENeSYS-MOD, in the sense of a feedback loop. That allows refining assumptions in the large-scale upper-level models, which in turn will increase the plausibility and realism of pathways at the European level.

Keynote presentation at the APA-Science event "Alles nur heiße Luft? Wie man richtig über's Klima redet"

Vortrag im Rahmen der Reihe "Wissen4Future" der ScientistsForFuture (Lecture as part of the "Wissen4Future" series of ScientistsForFuture)

Wissenschaftliche Grundlagen und Handlungsoptionen zur Klimakrise in Österreich - Vortrag anlässlich der Eröffnung des "Klimaforums", einer interaktiven Ausstellung des "Klimadashboard" im Designforum Wien, 4. November 2022

As part of the IPCC's 6th Assessment Report (AR6), authors from Working Group III on Mitigation of Climate Change undertook a comprehensive exercise to collect and assess quantitative, model-based scenarios related to the mitigation of climate change. Building on previous assessments, such as those undertaken for the 5th Assessment Report (AR5) and the Special Report on Global Warming of 1.5°C (SR15), the calls for AR6 for scenarios have been expanded and includes economy-wide GHG emissions, energy, and sectoral scenarios from global to national scales, thus more broadly supporting the assessment across multiple chapters (see Annex III, Part 2 of the WGIII report for more details). The compilation and assessment of the scenario ensemble was conducted by authors of the IPCC AR6 report, and the resource is hosted by the International Institute for Applied Systems Analysis (IIASA) as part of a cooperation agreement with Working Group III of the IPCC. The scenario ensemble contains 3,131 quantitative scenarios with data on socio-economic development, greenhouse gas emissions, and sectoral transformations across energy, land use, transportation, buildings and industry. These scenarios derive from 191 unique modelling frameworks, 95+ model families that are either globally comprehensive, national, multi-regional or sectoral. The criteria for submission included that the scenario is presented in a peer-reviewed journal accepted for publication no later than October 11th, 2021, or published in a report determined by the IPCC WG III Bureau to be eligible grey literature by the same date. The AR6 scenario database is documented in Annex III.2 of the Sixth Assessment Report of Working Group III. For the purpose of the assessment, scenarios have been grouped in various categories relating to, among other things, climate outcomes, overshoot, technology availability and policy assumptions.

As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects have to be addressed. We identify key methodological challenges and the existing methods and applications that have been or can be used to address these challenges within a three-step approach: (1) pre-processing the ensemble; (2) selecting a few scenarios or analysing the full ensemble; and (3) providing users with efficient access to the information.

There is a debate within the scientific and policy making community as to the suitability of global integrated assessment models (IAMs) for long-term planning exercises of the global power system. This study informs this debate and proposes a methodological framework for soft-linking of global IAMs with detailed global power system models. With the proposed open-source framework, the scenario results from IAMs can be fed into a power system model to assess given scenarios with enhanced spatial, technological, and temporal resolution. Results from these simulations can be redirected to the IAM through iterative bi-directional soft-linking. A proof of concept application of the proposed framework is presented by linking global IAM MESSAGEix-GLOBIOM with global power system model PLEXOS-World. Among others, the results highlight that the assumption of unconstrained electricity flows inside large regional copperplates causes an overestimation of variable renewables integration potential within MESSAGEix-GLOBIOM. We propose areas for informed improvements in MESSAGEix-GLOBIOM.

Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change. The current scenarios, however, are criticized because they feature strategies with pronounced overshoot of the global temperature goal, requiring a long-term repair phase to draw temperatures down again through net-negative emissions. Some impacts might not be reversible. Hence, we explore a new set of net-zero CO2 emissions scenarios with limited overshoot. We show that upfront investments are needed in the near term for limiting temperature overshoot but that these would bring long-term economic gains. Our study further identifies alternative configurations of net-zero CO2 emissions systems and the roles of different sectors and regions for balancing sources and sinks. Even without net-negative emissions, CO2 removal is important for accelerating near-term reductions and for providing an anthropogenic sink that can offset the residual emissions in sectors that are hard to abate.

There is a debate within the scientific and policy making community as to the suitability of global integrated assessment models (IAMs) for long-term planning exercises of the global power system. This study informs this debate and proposes a methodological framework for soft-linking of global IAMs with detailed global power system models. With the proposed open-source framework, the scenario results from IAMs can be fed into a power system model to assess given scenarios with enhanced spatial, technological, and temporal resolution. Results from these simulations can be redirected to the IAM through iterative bi-directional soft-linking. A proof of concept application of the proposed framework is presented by linking global IAM MESSAGEix-GLOBIOM with global power system model PLEXOS-World. Among others, the results highlight that the assumption of unconstrained electricity flows inside large regional copperplates causes an overestimation of variable renewables integration potential within MESSAGEix-GLOBIOM. We propose areas for informed improvements in MESSAGEix-GLOBIOM.

Low-carbon pathways consistent with the 2°C and 1.5°C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

This data set includes global climate change mitigation scenarios as summarized by Riahi et al., 2021. The scenarios are developed as part of the ENGAGE project and were assessed in terms of the their investment implications (Bertram et al., 2021), their land-use dynamics (Hasegawa et al., 2021) as we all as with respect to their costs and benefits (Drouret et al., 2021). The scenarios include a current national policies scenario and an NDC scenario that depict relevant near-term GHG emission tends and targets. In the long-term, two types of CO2 emission budgets are implemented, so called “net-zero budgets” and “end-of-century” budgets. The “net-zero-budget” scenarios assume climate policies that limit the remaining cumulative CO2 emissions until net zero CO2 emissions are reached. These scenarios limit the temperature overshoot and do not rely on global net-negative CO2 emissions to keep warming below the intended temperature limit. In contrast, the “end-of-century budget” scenarios assume long-term climate policies that limit cumulative CO2 emissions over the full course of the 21st century. Depending on the availability of carbon dioxide removal options, these scenarios may comprise high temperature overshoot and global net negative CO2 emissions in the second half of the century. The near-term dimension of current national policies until 2020 or NDCs until 2030 is then combined with reaching the net-zero and full-century CO2 emissions budgets. To cover a relevant range of temperature outcomes (which in addition to the budgets themselves also determined by mitigation of non-CO2 GHG and aerosol emissions), the budgets are varied between 200 and 3000 GtCO2 in steps of 50 – 500 GtCO2. The data is available for download at the ENGAGE Scenario Explorer. The license permits use of the scenario ensemble for scientific research and science communication, but restricts redistribution of substantial parts of the data. Please refer to the FAQ and legal code for more informa

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for timeseries aggregation, downscaling and unit conversion. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

Exploring potential future pathways for developing Asia’s energy consumption, CO2 emissions and infrastructure investment needs is essential to understanding how the countries of this rapidly growing region may contribute to the global climate targets set out in the 2015 Paris Agreement. To this end, this study employs the state-of-the-art global integrated assessment model MESSAGEix-GLOBIOM to investigate mid-century decarbonization strategies for developing Asia to 2050. Our results indicate that a radical change in the energy portfolio is required to reach the target of ‘well below’ 2°C. Specifically, our scenarios point to a rapid reduction of fossil fuel utilization, enhancement of low-carbon energy supply, and boosting of energy efficiency efforts. Such a transformation leads to a deep cut in CO2 emissions by 78% and 93% by 2050 in scenarios consistent with the 2°C and 1.5°C targets, respectively. Electricity generation and final energy consumption become dominated by low-carbon energy by 2050 in these scenarios. In terms of investment needs beyond a baseline scenario, the 2°C and 1.5°C pathways imply that the scale of low-carbon investment may need to double and triple, respectively. These increases would be partially offset by disinvestment in coal, oil and natural gas extraction and conversion infrastructure. Decarbonizing the energy system also impacts the capital needed for making progress on other sustainable development goals (SDGs), such as air pollution, clean water and food security.

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO2eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossil-fuel-dependent countries.

These webpages document the IIASA Integrated Assessment Modeling (IAM) framework, also referred to as MESSAGEix-GLOBIOM. MESSAGEix-GLOBIOM is a global model, covering 11 world regions and was originally developed for the quantification of the so-called Shared Socio-economic Pathways (SSPs). The documentation includes information on the spatial and temporal structure of the model, the socio-economic drivers, the energy supply and demand sector representation, the agriculture, forest and other land-use component, and the macro-economic and climate modules. It also links to the underlying MESSAGEix mathematical modeling framework which includes information on the equations governing the model dynamics.

The ambition of the openENTRANCE project is to develop and establish an open, transparent and integrated modelling platform for assessing low-carbon transition pathways of the European energy system. In this context, the open source energy system model GENeSYS-MOD is one of the core models having been developed enabling quantitative scenario pathway studies of the future European energy system. The four quantitative studies presented in the openENTRANCE project and in this paper build upon the four storylines developed at the beginning of the openENTRANCE project. A storyline is a narrative describing possible future trajectories (pathways) of the energy transition. Storylines should be understood as possible future developments of the European energy system, which could occur equally without having a preference for one of them. Three of the storylines, and subsequently quantified scenario pathway studies in openENTRANCE comply with the (European fraction of the) 1.5 ∘C global temperature increase limit. The fourth one approaches the 2.0 ∘C limit. The quantified scenario pathway results not only show the needs of the fully open energy system model GENeSYS-MOD to find feasible solutions of the underlying analytical optimization problem, but more importantly highlight what needs to be done in the future European energy system if we seriously intend to limit global warming!

To understand how global warming can be kept well below 2 degrees Celsius and even 1.5 degrees Celsius, climate policy uses scenarios that describe how society could reduce its greenhouse gas emissions. However, current scenarios have a key weakness: they typically focus on reaching specific climate goals in 2100. This choice may encourage risky pathways that delay action, reach higher-than-acceptable mid-century warming, and rely on net removal of carbon dioxide thereafter to undo their initial shortfall in reductions of emissions. Here we draw on insights from physical science to propose a scenario framework that focuses on capping global warming at a specific maximum level with either temperature stabilization or reversal thereafter. The ambition of climate action until carbon neutrality determines peak warming, and can be followed by a variety of long-term states with different sustainability implications. The approach proposed here closely mirrors the intentions of the United Nations Paris Agreement, and makes questions of intergenerational equity into explicit design choices.

The MESSAGE Integrated Assessment Model (IAM) developed by IIASA has been a central tool of energy-environment-economy systems analysis in the global scientific and policy arena. It played a major role in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC); it provided marker scenarios of the Representative Concentration Pathways (RCPs) and the Shared Socio-Economic Pathways (SSPs); and it underpinned the analysis of the Global Energy Assessment (GEA). Alas, to provide relevant analysis for current and future challenges, numerical models of human and earth systems need to support higher spatial and temporal resolution, facilitate integration of data sources and methodologies across disciplines, and become open and transparent regarding the underlying data, methods, and the scientific workflow. In this manuscript, we present the building blocks of a new framework for an integrated assessment modeling platform; the \ecosystem" comprises: i) an open-source GAMS implementation of the MESSAGE energy++ system model integrated with the MACRO economic model; ii) a Java/database backend for version-controlled data management, iii) interfaces for the scientific programming languages Python & R for efficient input data and results processing workflows; and iv) a web-browser-based user interface for model/scenario management and intuitive \drag-and-drop" visualization of results. The framework aims to facilitate the highest level of openness for scientific analysis, bridging the need for transparency with efficient data processing and powerful numerical solvers. The platform is geared towards easy integration of data sources and models across disciplines, spatial scales and temporal disaggregation levels. All tools apply best-practice in collaborative software development, and comprehensive documentation of all building blocks and scripts is generated directly from the GAMS equations and the Java/Python/R source code.

The radical change in recent global climate governance calls for China and Europe to ramp up their efforts in leading the world to reach the long-term climate goals. By analyzing the results from the state-of-the-art global integrated assessment model, MESSAGEix-GLOBIOM, this paper aims to understand the future levels of financial investment needed for building and maintaining energy-related infrastructure in the two regions for fulfilling stringent targets consistent with 'well below 2 °C'. The results indicate that a rapid upscaling and structural change of these investments towards decarbonization are necessitated by the climate stringent scenarios. China and Europe need to increase their low carbon investments by 65% and 38% in a scenario reaching the 2° target relative to their respective reference scenarios which assume no such target from 2016–2050. In a more stringent climate policy scenario of the 1.5° target, these investment needs will increase by 149% and 79% for China and Europe respectively. Among all the energy sectors, energy efficiency, renewable electricity generation and electricity transmission and distribution are the three largest investing targets for the two regions. However, those investments will not likely be realized without strong policy incentives. Implications for green finance and multilateral cooperation initiatives are discussed in the context of the scenario results.

We propose a novel method to find Nash equilibria in games with binary decision variables by including compensation payments and incentive-compatibility constraints from non-cooperative game theory directly into an optimization framework in lieu of using first-order conditions of a linearization, or relaxation of integrality conditions. The reformulation offers a new approach to obtain and interpret dual variables to binary constraints using the benefit or loss from deviation rather than marginal relaxations. The method endogenizes the trade-off between overall (societal) efficiency and compensation payments necessary to align incentives of individual players. We provide existence results and conditions under which this problem can be solved as a mixed-binary linear program.We apply the solution approach to a stylized nodal power-market equilibrium problem with binary on-off decisions. This illustrative example shows that our approach yields an exact solution to the binary Nash game with compensation. We compare different implementations of actual market rules within our model, in particular constraints ensuring non-negative profits (no-loss rule) and restrictions on the compensation payments to non-dispatched generators. We discuss the resulting equilibria in terms of overall welfare, efficiency, and allocational equity.

Energy systems support technical solutions fulfilling the United Nations' Sustainable Development Goal for clean water and sanitation (SDG6), with implications for future energy demands and greenhouse gas emissions. The energy sector is also a large consumer of water, making water efficiency targets ingrained in SDG6 important for long-term energy planning. Here, we apply a global integrated assessment model to quantify the cost and characteristics of infrastructure pathways balancing SDG6 clean water targets with long-term energy transformations limiting climate warming to 1.5 ˚C. The rapid expansions of water infrastructure and water efficiency to meet SDG6 targets increase energy decarbonization costs by 3 to 8 %. Conversely, under the 1.5 ˚C policy, shifts to electricity-intensive water systems in SDG6 pathways raises water prices by 2 to 9 %. Through water conservation and integrated water-energy planning we can achieve a collection of sustainability targets while avoiding incremental costs. This working paper was subsequently published in Environmental Research Letters and is available here, http://pure.iiasa.ac.at/id/eprint/15591/.