A satellite-data-driven framework to rapidly quantify air-basin-scale NO <sub> <i>x</i> </sub> emissions and its application to the Po Valley during the COVID-19 pandemic
Kang Sun, Lingbo Li, Shruti Jagini, Dan Li
Abstract
Abstract. The evolving nature of the COVID-19 pandemic necessitates timely estimates of the resultant perturbations to anthropogenic emissions. Here we present a novel framework based on the relationships between observed column abundance and wind speed to rapidly estimate the air-basin-scale NOx emission rate and apply it at the Po Valley in Italy using OMI and TROPOMI NO2 tropospheric column observations. The NOx chemical lifetime is retrieved together with the emission rate and found to be 15–20 h in winter and 5–6 h in summer. A statistical model is trained using the estimated emission rates before the pandemic to predict the trajectory without COVID-19. Compared with this business-as-usual trajectory, the real emission rates show three distinctive drops in March 2020 (−42 %), November 2020 (−38 %), and March 2021 (−39 %) that correspond to tightened COVID-19 control measures. The temporal variation of pandemic-induced NOx emission changes qualitatively agrees with Google and Apple mobility indicators. The overall net NOx emission reduction in 2020 due to the COVID-19 pandemic is estimated to be 22 %.