Energy Transition

Scenario Discovery Analysis of Drivers of Solar and Wind Energy Transitions Through 2050

Authors' Summary: There are many systems involved in energy transitions, which makes it difficult to anticipate which factors are most likely to result in higher renewable energy adoption in the future, and the currently available projections of future renewable shares are highly uncertain.

We focus here on wind and solar energy in particular, and use a model that represents a variety of the different systems involved (including energy, agriculture, land use, and water) to create a set of nearly 4,000 scenarios that span a wide range of possible futures. Each scenario is driven by a combination of different parameter inputs chosen based on factors that we expect to impact wind and solar energy shares.

By analyzing this set of scenarios, we can find the most important drivers, and combinations of drivers, globally and in each of the 32 different regions represented in our model. Additionally, we look at the scenarios that produced the highest fractions of wind and solar energy and identify four different combinations of parameters that can lead to these high renewable fractions. For each of the four paths, we explore the implications in terms of outcomes like water consumption, air pollution, and food prices, and discuss the resulting tradeoffs.

Mitigating Emissions in the Global Steel Industry: Representing CCS and Hydrogen Technologies in Integrated Assessment Modeling

Abstract: We conduct a techno-economic assessment of two low-emissions steel production technologies and evaluate their deployment in emissions mitigation scenarios utilizing the MIT Economic Projection and Policy Analysis (EPPA) model. Specifically, we assess direct reduced iron-electric arc furnace with carbon capture and storage (DRI-EAF with CCS) and H2-based direct reduced iron-electric arc furnace (H2 DRI-EAF) which utilizes low carbon hydrogen to reduce CO2 emissions.

Our techno-economic analysis based on the current state of technologies found that DRI-EAF with CCS increased costs ~7% relative to the conventional steel technology. H2 DRI-EAF increased costs by ~18% when utilizing Blue hydrogen and ~79% when using Green hydrogen. The exact pathways for hydrogen production in different world regions, including the extent of CCS and hydrogen deployment in steelmaking are highly speculative at this point. In illustrative scenarios using EPPA, we find that, using base cost assumptions, switching from BF-BOF to DRI-EAF or scrap EAF can provide significant emissions mitigation within steelmaking. With further reductions in the cost of advanced steelmaking, we find a greater role for DRI-EAF with CCS, whereas reductions in both the cost of advanced steelmaking and hydrogen production lead to a greater role for H2 DRI-EAF.

Our findings can be used to help decision-makers assess various decarbonization options and design economically efficient pathways to reduce emissions in the steel industry. Our cost evaluation can also be used to inform other energy-economic and integrated assessment models designed to provide insights about future decarbonization pathways.

Air Quality Related Equity Implications of U.S. Decarbonization Policy

Abstract: Climate policies that target greenhouse gas emissions can improve air quality by reducing co-emitted air pollutant emissions. However, the extent to which climate policy could contribute to the targets of reducing existing pollution disparities across different populations remains largely unknown. We quantify potential air pollution exposure reductions under U.S. federal carbon policy, considering implications of resulting health benefits for exposure disparities across U.S. racial/ethnic groups.

We focus on policy cases that achieve reductions of 40-60% in 2030 economy-wide carbon dioxide (CO2) emissions, when compared with 2005 emissions. The 50% CO2 reduction policy case reduces average fine particulate matter (PM2.5) exposure across racial/ethnic groups, with greatest benefit for non-Hispanic Black (-0.44 μg/m3) and white populations (-0.37 μg/m3). The average exposure disparity for racial/ethnic minorities rises from 12.4% to 13.1%. Applying an optimization approach to multiple emissions reduction scenarios, we find that no alternate combination of reductions from different CO2 sources would substantially mitigate exposure disparities.

Results suggest that CO2-based strategies for this range of reductions are insufficient for fully mitigating PM2.5 exposure disparities between white and ethnic/racial minority populations; addressing disparities may require larger-scale structural changes.

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