Energy Transition

An economy-wide framework for assessing the stranded assets of the energy production sector under climate policies

Abstract: Climate change mitigation efforts, which require the transition away from carbon-intensive activities, can pose financial risks for owners of fossil fuel assets and investors that the finance companies are engaged in greenhouse gas-emitting activities. For instance, fossil fuel extraction may be significantly scaled-back, and coal-power plants may be idled or even phased out prematurely, thus becoming stranded assets for the shareholders.

Using a global general equilibrium model with detailed energy sector and capital stock structures, we estimate the corresponding stranded assets under various emissions mitigation scenarios. Our findings reveal that, depending on the policy scenario, the global net present value of unrealized fossil fuel output through 2050 relative to a “no policy” scenario is between 21.5 and 30.6 trillion USD, and that of stranded assets in coal power generation is between 1.3 and 2.3 trillion USD.

The analytical framework presented in our study complements existing research, in which macroeconomic variables required for estimating the stranded assets are often derived from models with more simplified assumptions. Therefore, individual firms and financial institutions can combine our economy-wide analysis with details on their own investment portfolios to determine their climate-related transition risk exposure.

 

Representing socio-economic uncertainty in human system models

Summary: Simulation models are often used to explore future development pathways and their impacts on energy, emissions, economies and the environment. This requires making assumptions about various socio-economic conditions, such as how fast populations and economies will grow, the cost of technology options, or the amount of fossil fuels available. Different assumptions have significant impacts on model results, yet analyses typically only test a few alternatives.

Here, we develop and use probability distributions to capture this uncertainty. We draw samples from these distributions, run an energy-economic model hundreds of times, and quantify the resulting uncertainty in model outcomes, providing insight into their likelihood. We focus on results related to emissions and output from different economic sectors, as well as energy and electricity technologies. We also apply approaches to find scenarios of interest from within the database of scenarios.

We find that many patterns of energy and technology development are possible under a given long-term environmental pathway (such as a 2C scenario) or a given economic outcome (such as high or low GDP). This approach can help identify biases in perceptions of what “needs” to happen to achieve certain outcomes, and shows that there are many pathways to a successful energy transition. 

MultiSector Dynamics: Scientific Challenges and a Research Vision for 2030, A Community of Practice Supported by the United States Department of Energy's Office of Science

Executive Summary: 

This report outlines a vision for MultiSector Dynamics (MSD) as an emerging transdisciplinary field that seeks to advance our understanding of how human-Earth systems interactions shape the resources, goods, and services on which society depends. The core objective of this MSD Vision Report is to clarify core definitions, share research questions, highlight scientific opportunities, and provide steps for improving the MSD community’s capacity to support needed scientific progress.

The report has several technical audiences in mind. These include current MSD researchers, scientists working in complementary fields who wish to learn more about opportunities for engagement, and research program managers at the US Department of Energy (DOE). Additionally, the research-to-operations (R2O2R) and community building elements of the report hold value for a broad array of US federal agencies as well as other governments and international organizations. As a transdisciplinary endeavor, the vision presented here should have elements that directly interest sectoral analysts engaged in energy, water, agriculture, transportation, health, etc. We hope these audiences will find the report a helpful reference and a source of opportunities for shaping the future of MSD science. 

The report incorporates ideas and insights from the members of the recently established MSD Community of Practice (CoP). MSD finds its roots in a number of research fields and communities, including integrated assessment; impacts, adaptation, and vulnerability; Earth system science; and complex adaptive systems. However, the MSD CoP draws its conceptual basis from a 2016 workshop sponsored and led by the DOE, "Understanding Dynamics and Resilience in Complex Interdependent Systems: Prospects for a Multi-Model Framework and Community of Practice," organized with other federal agencies and hosted by the US Global Change Research Program. The rationale for the CoP is that research on understanding risks and opportunities arising from tightly connected human and natural systems is fragmented across several fields, requiring improved collaboration and synthesis to accelerate needed scientific advances. A CoP Facilitation Team and a Scientific Steering Group (SSG) were launched in 2019 to advance the needed collaborations and scientific synthesis. Since that time, an initial core group of projects supported by DOE’s MSD research program has provided input to the development of the CoP through activities including a community questionnaire to identify current tools and research interests, regular meetings of technical working groups (WGs), MSD community briefings, research workshops, and the MSD CoP website.

The members of the MSD SSG and Facilitation Team are responsible for drafting this report, based on the above community inputs as well as a formal review of recent research within related fields such as Earth system science, integrated assessment modeling, economics, decision science, socio-ecological systems, socio-environmental systems, complexity science, systems engineering, energy transitions, urban systems, and coastal dynamics. Members of the major projects in the DOE MSD research program provided extensive comments on a first draft of the report (see Chapter 2.2 for descriptions and links to projects' websites for additional information). Robert Vallario, program manager for the DOE Earth and Environmental Systems Modeling MSD research program area, has provided insights, perspectives, and comments that have been critically important throughout the process. The SSG and the Facilitation Team thank these individuals for their many contributions and ongoing support. In addition, the Facilitation Team thanks the DOE Office of Science, Earth and Environmental System Modeling program for financial support of its activities through the Integrated Multisector Multiscale Modeling (IM3) project.

MultiSector Dynamics: Advancing the science of complex adaptive human-Earth systems

Abstract: The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce.

Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.

The Changing Nature of Climate-Related Risks in Global Wind Power Resources

Abstract: Under the ambitious low-carbon goals set forth by the recent Paris Accord as well as the prospects for large penetration of renewable energy-generation technologies, the need for advances in quantitative insights and foresights into the current and future availability of renewable energy resources is greater than ever. We have analyzed the changing risks in worldwide wind-power resource availability using large-ensemble simulations that span a range of human-forced climate scenarios. To enable this analysis, we construct estimates of wind power density (WPD) via a hybrid method that combines the emerging patterns of change in near-surface winds from climate models with the large-ensemble, probabilistic projections of the MIT Integrated Global System Model (IGSM).  Globally speaking, at a “75% consensus” threshold criterion (at least 3 out of every 4 members agree in the sign of change), by mid-century under an emissions scenario that assumes no further actions to limit emissions, an increase of about 2% in annual-averaged WPD is expected.  Under the most aggressive mitigation scenario considered associated with a global climate warming target of 1.5˚C, the expected increase is reduced to 0.5%. There is a notable seasonality to these expected global changes, with global WPD increases during December-February, and decreases across all remaining seasons. Salient and coherent geographic patterns are also found, however, there is a strong sensitivity of these results to the strictness of model-trend consensus applied, particularly in the spatial extent of the results that exceed the consensus criterion. At 90% consensus (at least 9 out of every 10 ensemble members must agree in sign of change) only 5%-8% of globe passes this threshold in the ensemble of WPD changes.  When contrasting the global-scale trends with respect to onshore and offshore regions, annual WPD will increase slightly offshore (median and average less than 1%) but slightly decrease onshore (-1% in the median), yet the seasonality of these WPD changes is more pronounced.

Pages

Subscribe to Energy Transition