Limiting global warming to the greatest extent possible is critical for reducing the adverse effects of climate change on humanity and the planet. To achieve long-term temperature mitigation targets, such as 1.5℃ or 2℃, it is crucial to reckon not only with the total emissions reductions required but also with the anticipated "committed" greenhouse gas (GHG) emissions from existing infrastructure. While data on the former is more accessible, information on the latter is often confined to snapshot publications with limited transparency on geographic or technological scales.

In this study, we introduce a comprehensive bottom-up model of "committed" energy supplies for the United States, aimed at informing climate policy decision-making. This work addresses critical questions about the existing energy system, allowing us to estimate the size of the remaining gap between locked-in US emissions from existing infrastructure and modeled emissions trajectories leading to 1.5℃ and 2℃ targets. The model incorporates facility-level lifecycle emissions for both fossil and non-fossil sources, utilizing well-level data for natural gas and oil, and power plant data for coal, renewables, and biomass. Designed for regular updates to accommodate additional energy projects or early retirements, the model ensures relevance and accuracy over time.

Utilizing this model, we analyze the GHG emissions gap across various project-relevant timescales, comparing locked-in US emissions with pathways to 1.5℃ and 2℃ targets based on the latest models from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Our findings reveal that, while some space exists between the modeled scenario pathway and already locked-in emissions over certain lifetime scales, a minimal number of new fossil energy projects could entirely eliminate this window. Additionally, Monte Carlo analysis is employed to illustrate the robustness of our conclusions to uncertainties in model parameters.

This committed energy system model serves as a core input to the recently-published "climate test" decision-support tool. This tool is specifically designed for policymakers tasked with evaluating individual fossil infrastructure projects and their alignment with climate targets under US law. Together, these tools empower government agencies to make scientifically informed and climate-protective decisions for our energy future, facilitating our collective efforts to realize overarching climate goals.

The U.S. government's commitment to achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 aligns seamlessly with the global climate mitigation objectives outlined in the Paris Agreement. The overarching goal is to limit the average temperature increase to 1.5 °C or less by 2100, compared to preindustrial levels. To realize this ambitious domestic mid-century target, there is an imperative need for the rapid adoption of energy-efficient technologies and the decarbonization of pivotal sectors such as power and transportation. This involves embracing electrification, fuel switching, and the expansion of variable renewable energy sources and storage technologies. Furthermore, an increased emphasis on electrification is crucial for both the buildings and industrial sectors.

While the power and transportation sectors, contributing 29% and 25% to total U.S. national GHG emissions, have extensively outlined and modeled their decarbonization strategies, meeting the 2035 and 2050 targets demands a concerted effort due to the substantial scale of the power sector and the heterogeneous nature of the transport sector. The industrial sector, responsible for 23% of total U.S. GHG emissions, poses a unique challenge due to its activities that are challenging to electrify. Addressing these activities requires the exploration of technologies that are either less understood or have not yet been scaled. Finding innovative solutions in this realm is crucial for achieving the broader climate goals.

Emerging technologies call for the application of forward-looking life cycle assessment (LCA) methodologies. These methodologies enable the comprehensive consideration of technology scaling and process enhancements, including learning by doing. Additionally, the future system context in which these technologies are envisioned to operate holds equal significance in many instances. Background scenarios systematically generated by integrated assessment models (IAMs) proficiently incorporate the evolving dynamics of the energy-economy-land-climate system. These IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, enhancing the comparability of prospective LCAs utilizing various IAMs.

In this context, we present an open-source framework for prospective LCA, known as the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON). LiAISON facilitates the examination of non-linear relationships between technology foreground and the future energy system background, encompassing a spectrum of midpoint and resource-use metrics.

The LiAISON framework has been used to assess the environmental impact of various hydrogen production methods in the United States. This involved combining data from two integrated assessment models, IMAGE and GCAM, to enable life cycle assessment (LCA) across different scenarios. The framework is currently applied to a case study involving industrial heat supply in the US. The study not only analyzes LCA results with temporal and geospatial details for two technologies but also aims to create a foundational framework that can be extended to incorporate other scenarios generated by integrated assessment models and U.S. open-source life cycle inventory databases.

The Global Change Analysis Model (GCAM) is an open source, publicly available market equilibrium integrated assessment model, which integrates human and natural earth systems science. GCAM examines the multisector dynamics between the socioeconomic, energy, water, land, climate, and emissions systems at 5-year time steps through 2100 and operates with a spatial resolution of 32 economic regions, 283 land regions, and 233 water basins. The model has been developed at Pacific Northwest National Laboratory’s Joint Global Change Research Institute (PNNL JGCRI) for over 30 years and has been used to explore questions related to energy transition, decarbonization and carbon mitigation, technology development and policies, air pollution, energy/water/food nexus, climate impacts, and many others. The GCAM community also continues to develop versions of GCAM with state-level detail in larger countries such as GCAM-USA, GCAM-China, GCAM-Canada, and others. This presentation will give an overview of GCAM, the range of analyses that have been conducted using the model, and how GCAM can supplement traditional ISSST analyses.