Climate change mitigation measures are often projected to reduce anthropogenic carbon dioxide concentrations. Yet, it seems there is ample evidence suggesting that we have a limited understanding of the impacts of these measures and their combinations. For example, the Inflation Reduction Act (IRA) enacted in the U.S. in 2022 contains significant provisions, such as the electric vehicle (EV) tax credits, to reduce CO2 emissions. However, the impact of such provisions is not fully understood across the U.S., particularly in the context of their interactions with other macroeconomic systems. In this paper, we employ an Integrated Assessment Model (IAM), the Global Change Assessment Model (GCAM), to estimate the future CO2 emissions in the U.S. GCAM is equipped to comprehensively characterize the interactions among different systems, e.g., energy, water, land use, and transportation. Thus, the use of GCAM-USA that has U.S. state-level resolution allows the projection of the impacts and consequences of major provisions in the IRA, i.e., EV tax credits and clean energy incentives. To compare the performance of these incentives and credits, a policy effectiveness index is used to evaluate the strength of the relationship between the achieved total CO2 emissions and the overarching emission reduction costs. Our results show that the EV tax credits as stipulated in the IRA can only marginally reduce carbon emissions across the U.S. In fact, it may lead to negative impacts in some states. However, simultaneously combining the incentives and tax credits improves performance and outcomes better than the sum of the individual effects of the policies. This demonstrates that the whole is greater than the sum of the parts in this decarbonization approach. Our findings provide insights for policymakers with a recommendation that combining EV tax credits with clean energy incentives magnifies the intended impact of emission reduction.
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Consequences of equivalency metric design for energy transitions and climate change
Assessments of the climate impacts of energy technologies and other emissions sources can depend strongly on the equivalency metric used to compare short- and long-lived greenhouse gas emissions. However, the consequences of metric design choices are not fully understood, and in practice, a single metric, the global warming potential (GWP), is used almost universally. Many metrics have been proposed and evaluated in recent decades, but questions still remain about which ones perform better and why. Here, we develop new insights on how the design of equivalency metrics can impact the outcomes of climate policies. We distill the equivalency metric problem into a few key design choices that determine the metric values and shapes seen across a wide range of different proposed metrics. We examine outcomes under a hypothetical 1.5 or 2∘C policy target and discuss extensions to other policies. Across policy contexts, the choice of time parameters is particularly important. Metrics that emphasize the immediate impacts of short-lived gases such as methane can reduce rates of climate change but may require more rapid technology changes. Differences in outcomes across metrics are more pronounced when fossil fuels, with or without carbon capture and storage, play a larger role in energy transitions. By identifying a small set of consequential design decisions, these insights can help make metric choices and energy transitions more deliberate and effective at mitigating climate change.
more » « less- NSF-PAR ID:
- 10379749
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Climatic Change
- Volume:
- 175
- Issue:
- 1-2
- ISSN:
- 0165-0009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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