Influence of anthropogenic emission reductions due to COVID-19 restrictions on an atmospheric chemistry model

Abstract:

Restrictions imposed to contain the COVID-19 pandemic were one the largest and fastest perturbations ever to global atmospheric composition. They give us an unprecedented and unintended perturbation experiment with which to test the fidelity of the processes represented in our chemistry transport modes.We use estimates for the change in emissions, based on mobile phone mobility data and other sources to run two simulations of the GEOS-Chem model both globally and regionally. The first assumes that the emissions for 2020 are the same as the emissions for 2019, the second assumes that the emissions for 2020 fall in response to the COVID restrictions based on our estimates of the reduced emissions. We use emissions estimates driven by mobile phone mobility data and other sources for these simulations. We analyse the model response by comparison with globally available surface observations of atmospheric composition (NO₂, O₃, PM_2.5, etc). We focus on the model and observed response of secondary pollutants such as O₃ and PM_2.5 to reduced primary emissions as a test of secondary chemistry. We find large changes in NO₂ concentrations which reflect the reduced emissions. However, the complexity of the photochemical system means that we see a buffering in the system so that a 10% reduction in NOx emissions leads to a roughly 8% reduction in NO₂ concentrations. We find that changes in O₃ concentration are relatively small but there are more significant changes in the diurnal cycle with increases at night compensate for by decreases during the day. The impact on PM_2.5 is complex and depend on the composition of the aerosol and how that varies both geographically and temporally. Model success or failure in being able to simulate the response to these perturbation gives insight into the usefulness of these model for making policy decisions for future improvements in air quality.