NO_<i>x</i> emissions in France in 2019–2021 as estimated by the high-spatial-resolution assimilation of TROPOMI NO₂ observations

Abstract

Since 2018, the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) has provided unprecedented images of nitrogen dioxide (NO2) tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of TROPOMI–PAL data to estimate the national to urban NOx emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework (CIF) coupled to the CHIMERE regional transport model at a spatial resolution of 10 km × 10 km. The seasonal to inter-annual variations in the French NOx emissions are analyzed. Special attention is paid to the current capability to quantify strong anomalies in the NOx emissions at intra-annual scales, such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. At the annual scale, the inversions suggest a decrease in the average emissions over 2019–2021 of −3 % compared to the national budget from the Copernicus Atmosphere Monitoring Service regional inventory (CAMS-REG) for the year 2016, which is used as a prior estimate of the national-scale emissions for each year by the Bayesian inversion framework. This is lower than the decrease of −14 % from 2016 to the average over 2019–2021 in the estimates of the French Technical Reference Center for Air Pollution and Climate Change (CITEPA). The lower decrease in the inversion results may be linked in large part to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and to the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the anthropogenic NOx emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas with high emission levels (e.g., −26 % from April 2019 to April 2020 in the Paris urban area), reflecting reductions in the intensity of vehicle traffic reported during the lockdown period. However, the system does not show large emission decreases for some of the largest cities in France (such as Bordeaux, Nice and Toulouse), even though they were also impacted by the lockdown measures. Despite the current limitations for the monitoring of emissions at the national scale, or for some of the largest cities in France, these results open positive perspectives regarding the ability to support the validation or improvement of inventories with satellite observations, at least at the local level. This leads to discussions on the need for a stepwise improvement of the inversion configuration for a better extraction and extrapolation in space and time of the information from the satellite observations.