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No COVID-19 Climate Silver Lining in the US Power Sector

2020-08-15 · Max Luke, Priyanshi Somani, Turner Cotterman, Dhruv Suri, Stephen J. Lee

Recent studies conclude that the global coronavirus (COVID-19) pandemic decreased power sector CO$_2$ emissions globally and in the United States. In this paper, we analyze the statistical significance of CO2 emissions reductions in the U.S. power sector from March through December 2020. We use Gaussian process (GP) regression to assess whether CO2 emissions reductions would have occurred with reasonable probability in the absence of COVID-19 considering uncertainty due to factors unrelated to the pandemic and adjusting for weather, seasonality, and recent emissions trends. We find that monthly CO2 emissions reductions are only statistically significant in April and May 2020 considering hypothesis tests at 5% significance levels. Separately, we consider the potential impact of COVID-19 on coal-fired power plant retirements through 2022. We find that only a small percentage of U.S. coal power plants are at risk of retirement due to a possible COVID-19-related sustained reduction in electricity demand and prices. We observe and anticipate a return to pre-COVID-19 CO2 emissions in the U.S. power sector.

📄 PDF Abstract BibTeX arXiv:2008.06660

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highlandenergy/no-covid-19-climate-silver-lining-in-the-us-power-sector 공식 구현

Methods 이 논문이 사용한 방법론

Gaussian Process Gaussian Processes are non-parametric models for approximating functions. They rely upon a measure of similarity between points (the kernel function) to predict the value for…

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