Measuring the atmospheric impacts of COVID-19-related emissions reductions
Researchers used interagency modeling and observational capabilities to understand the impacts of reduced pollution related to the COVID-19 pandemic on Earth’s energy balance.
Lockdown measures enacted to control the spread of COVID-19 led to a worldwide reduction in emissions of tiny atmospheric particles known as aerosols. Through their interactions with solar energy and clouds, aerosols play a significant role in shaping Earth’s energy balance (or the balance between incoming energy from the sun and outgoing energy from the Earth) and climate that is still inadequately understood. NOAA and NASA researchers used multi-agency observational and modeling capabilities to investigate the climate effects of this sharp drop in aerosol pollution, which provided an opportunity to test how well models simulate interactions between aerosols, clouds, and solar energy.
Satellite observations showed a 7% decline in the amount of solar energy reflected back to space at the top of Earth’s atmosphere and a 32% drop in aerosol concentrations over the East Asian Marginal Seas in March 2020, coinciding with COVID-19 lockdown measures. Using model simulations, researchers separated the impacts of weather from the impacts of aerosols on the amount of solar energy reflected to space. Results showed that pandemic-related emissions reductions account for about one-third of the drop in solar clear-sky reflection (or the fraction of the sun’s energy that is reflected back into space under cloud-free conditions).[1] The rest of the reduction was attributed to weather variability and long-term emissions trends.
Multi-agency observational and modeling capabilities were critical to monitoring and understanding impacts on Earth’s energy balance from reduced aerosol pollution. The framework developed in this research can be used to study the atmospheric impacts of the ongoing pandemic in other parts of the world and to enhance the predictive capabilities of climate and weather models.
[1] Yi Ming, Norman G. Loeb, Pu Lin, Zhaoyi Shen, Vaishali Naik, Clare E. Singer, Ryan X. Ward, Fabien Paulot, Zhibo Zhang, Nicolas Bellouin, Larry W. Horowitz, Paul A. Ginoux, V. Ramaswamy. Geophysical Research Letters. DOI: 10.1002/essoar.10503579.1