Time-resolved emission reductions for atmospheric chemistry modelling in Europe during the COVID-19 lockdowns

Abstract

Abstract. We quantify the reductions in primary emissions due to the COVID-19 lockdowns in Europe. Our estimates are provided in the form of a dataset of reduction factors varying per country and day that will allow the modelling and identification of the associated impacts upon air quality. The country- and daily-resolved reduction factors are provided for each of the following source categories: energy industry (power plants), manufacturing industry, road traffic and aviation (landing and take-off cycle). We computed the reduction factors based on open-access and near-real-time measured activity data from a wide range of information sources. We also trained a machine learning model with meteorological data to derive weather-normalized electricity consumption reductions. The time period covered is from 21 February, when the first European localized lockdown was implemented in the region of Lombardy (Italy), until 26 April 2020. This period includes 5 weeks (23 March until 26 April) with the most severe and relatively unchanged restrictions upon mobility and socio-economic activities across Europe. The computed reduction factors were combined with the Copernicus Atmosphere Monitoring Service's European emission inventory using adjusted temporal emission profiles in order to derive time-resolved emission reductions per country and pollutant sector. During the most severe lockdown period, we estimate the average emission reductions to be −33 % for NOx, −8 % for non-methane volatile organic compounds (NMVOCs), −7 % for SOx and −7 % for PM2.5 at the EU-30 level (EU-28 plus Norway and Switzerland). For all pollutants more than 85 % of the total reduction is attributable to road transport, except SOx. The reductions reached −50 % (NOx), −14 % (NMVOCs), −12 % (SOx) and −15 % (PM2.5) in countries where the lockdown restrictions were more severe such as Italy, France or Spain. To show the potential for air quality modelling, we simulated and evaluated NO2 concentration decreases in rural and urban background regions across Europe (Italy, Spain, France, Germany, United-Kingdom and Sweden). We found the lockdown measures to be responsible for NO2 reductions of up to −58 % at urban background locations (Madrid, Spain) and −44 % at rural background areas (France), with an average contribution of the traffic sector to total reductions of 86 % and 93 %, respectively. A clear improvement of the modelled results was found when considering the emission reduction factors, especially in Madrid, Paris and London where the bias is reduced by more than 90 %. Future updates will include the extension of the COVID-19 lockdown period covered, the addition of other pollutant sectors potentially affected by the restrictions (commercial and residential combustion and shipping) and the evaluation of other air quality pollutants such as O3 and PM2.5. All the emission reduction factors are provided in the Supplement.

COVID-19 lockdown-induced changes in NO<sub>2</sub> levels across India observed by multi-satellite and surface observations

“…However, thermal power plants, megacities, large urban areas, and industrial regions remain NO 2 emission hotspots (Ghude et al, 2008(Ghude et al, , 2013Prasad et al, 2012;Hilboll et al, 2013Hilboll et al, , 2017Duncan et al, 2016). Moreover, despite the measures taken to control NO x emissions, urban areas often exceed national ambient air quality standards in India (Sharma et al, 2013;Nori-Sarma et al, 2020;Hama et al, 2020) and thus require a detailed scenario analysis.…”

Estimating lockdown-induced European NO<sub>2</sub> changes using satellite and surface observations and air quality models

“…In Europe, lockdown measures were implemented on various dates during February and March 2020. These lockdowns drastically reduced traffic and also activity levels in most industries (Guevara et al, 2021;Le Quéré et al, 2020). These sectors represent a large share of NO x emissions (51 % according to EEA, 2020a).…”

“…The Copernicus Atmosphere Monitoring Service (CAMS) produces daily European air quality forecasts and analyses using an ensemble of 11 models, ensuring unique reliability and quality (Marécal et al, 2015). Using emission scaling factors to account for lockdown measures, such an ensemble of models can be used to estimate lockdown reductions in NO 2 pollution (amongst other pollutants) and account for the weather variability at the same time (Colette et al, 2020;Guevara et al, 2021).…”

Aviation Contrail Cirrus and Radiative Forcing Over Europe During 6 Months of COVID‐19

“…We search for comparable signatures in the spatial distribution and in the diurnal cycle of mean values in dense traffic areas. We expect that the observed changes are partly due to different atmospheric and surface conditions ("weather") in the compared time periods (van Heerwaarden et al, 2021) and partly due to different air traffic, besides other anthropogenic and natural emissions (Guevara et al, 2021;Le Quéré et al, 2020). The weather conditions are represented by the ECMWF forecasts, assuming that the IFS simulates the atmosphere without aviation effects.…”