A satellite-data-driven framework to rapidly quantify air-basin-scale NO&amp;lt;sub&amp;gt;&amp;lt;i&amp;gt;x&amp;lt;/i&amp;gt;&amp;lt;/sub&amp;gt; emissions and its application to the Po Valley during the COVID-19 pandemic

Kang Sun,Shruti Jagini,Lingbo Li,Dan Li

doi:10.5194/acp-21-13311-2021

A satellite-data-driven framework to rapidly quantify air-basin-scale NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; emissions and its application to the Po Valley during the COVID-19 pandemic

Kang Sun, Shruti Jagini + Show 2 more

Open Access

https://doi.org/10.5194/acp-21-13311-2021

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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 %.

Highlights

Satellites have revolutionized our ability to observe the Earth’s atmospheric composition and air quality
J is the index of each level 3 grid cell at 0.01◦ resolution, and j ∈ s includes all grid cells satisfying the spatial aggregation criterion s. i is NO2 tropospheric VCD (TVCD) retrieved at level 2 pixel i. i ∈ t and p keep only level 2 pixels satisfying time filtering criteria and parameter filtering criteria. wi, j is the weight of level 2 pixel i at level 3 grid cell j and depends on the spatial response of pixel i at grid cell j as well as the retrieval uncertainty at pixel i (Zhu et al, 2017; Sun et al, 2018)
To assess the uncertainties induced by such simplification, we conduct sensitivity studies using end-to-end emission rate and chemical lifetime estimations described in Sect. 3.3 by switching wind speed options described in Sect. 2.3 and varying the prescribed values for L

Summary

Introduction

Satellites have revolutionized our ability to observe the Earth’s atmospheric composition and air quality. The tropospheric VCD (TVCD) retrieval of NO2 has been widely used to infer the emissions of nitrogen oxides (NOx = NO2 + NO), which is at the center stage of atmospheric chemistry by modulating ozone and secondary aerosol formation (Kroll et al, 2020). Many NOx emission inference methods have been proposed using chemical transport models (CTMs) that resolve chemistry and meteorology in space and time, including mass balance (Martin et al, 2003; Lamsal et al, 2011; Zheng et al, 2020), fourdimensional variational data assimilation (4D-Var, Qu et al, 2019; Wang et al, 2020), and Kalman filters (Miyazaki et al, 2020a; Mijling and Van Der A, 2012; Ding et al, 2020). Many NOx emission inference methods have been proposed using chemical transport models (CTMs) that resolve chemistry and meteorology in space and time, including mass balance (Martin et al, 2003; Lamsal et al, 2011; Zheng et al, 2020), fourdimensional variational data assimilation (4D-Var, Qu et al, 2019; Wang et al, 2020), and Kalman filters (Miyazaki et al, 2020a; Mijling and Van Der A, 2012; Ding et al, 2020). Ding et al (2020) and Miyazaki et al (2020b) used CTMs to estimate NOx emission reduction in China in the early phase

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