DOI: 10.5061/dryad.12jm63z1q
title: Unchanged PM2.5 levels over Europe during COVID-19 were buffered by ammonia

description: The coronavirus outbreak in 2020 had devastating impact on human life,
 albeit a positive effect for the environment reducing emissions of primary
 aerosols and trace gases and improving air quality. In this paper, we
 present inverse modelling estimates of ammonia emissions during the
 European lockdowns of 2020 based on satellite observations. Ammonia has a
 strong seasonal cycle and mainly originates from agriculture. We further
 show how changes in ammonia levels over Europe, in conjunction with
 decreases in traffic-related atmospheric constituents modulated PM2.5. The
 key result of this study is a -9.8% decrease in emissions in the first
 half of 2020 compared to the same period in 2016–2019 attributed to
 restrictions related to the global pandemic. We further calculate the
 delay in the evolution of the emissions in 2020 before, during and after
 lockdowns, by a sophisticated comparison of the evolution of ammonia
 emissions during the same time periods for the reference years
 (2016–2019). Our analysis demonstrates a clear delay in the evolution of
 ammonia emissions of -77 kt, that was mainly observed in the countries
 that suffered the strictest travel, social and working measures. Despite
 the general drop in emissions during the first half of 2020 and the delay
 in the evolution of the emissions during the lockdown period, satellite
 and ground-based observations showed that European levels of ammonia
 increased. On one hand, this was due to the reduction of
 and (precursors of the atmospheric acids with which ammonia
 reacts) that caused less binding and thus less chemical removal of ammonia
 (smaller loss – higher lifetime); on the other, the majority of the
 emissions persisted, because ammonia mainly originates from agriculture, a
 primary production sector that was not influenced by the lockdown
 restrictions, as practically agricultural activity never ceased. Despite
 the projected drop in various atmospheric aerosols and trace gases, PM2.5
 levels stayed unchanged or even increased in Europe due to a number of
 reasons attributed to the complicated system. Higher water vapour
 during the European lockdowns favoured more sulfate production from
 and  (gas phase) or (aqueous phase). Ammonia first neutralised
 sulfuric acid (due to higher atmospheric abundance) also producing
 sulfate. Then, the continuously accumulating free ammonia reacted with
 nitric acid shifting the equilibrium reaction towards particulate nitrate.
 In high free ammonia atmospheric conditions such as those in Europe during
 the 2020 lockdowns, a small reduction of levels drives faster oxidation
 toward nitrate and slower deposition of total inorganic nitrate causing
 high secondary PM2.5 levels.
description: - FLEXPART v10.4 sensitivities for 6 model levels using chemistry
 loss after taking into account changes in emissions of NOx and SO2 in the
 calculations (see also associated
 paper): AVE_FOOTPRINT_L1_chem.nc, AVE_FOOTPRINT_L2_chem.nc, AVE_FOOTPRINT_L3_chem.nc, AVE_FOOTPRINT_L4_chem.nc, AVE_FOOTPRINT_L5_chem.nc, AVE_FOOTPRINT_L6_chem.nc - FLEXPART v10.4 sensitivities for 6 model levels using chemistry loss after taking into account changes in emissions of NOx and SO2 in the calculations (see also associated paper): AVE_FOOTPRINT_L1_nochem.nc, AVE_FOOTPRINT_L2_nochem.nc, AVE_FOOTPRINT_L3_nochem.nc, AVE_FOOTPRINT_L4_nochem.nc, AVE_FOOTPRINT_L5_nochem.nc, AVE_FOOTPRINT_L6_nochem.nc - Different surrounding estimates of posterior emissions covering 2°, 3° and 4° from each grid-cell: 2deg.tar.gz, 3deg.tar.gz, 4deg.tar.gz - Performance calculations for the prior and posterior emissions against the dependent observations (CrIS): Correction_R4.tar.gz - Forward simulations with FLEXPART v10.4 using prior and posterior emissions that were used for validation against independent (observations that were excluded from the inversion) observations from the EMEP network: FWD_pri.tar.gz, FWD_pos.tar.gz
description: # Unchanged PM2.5 levels over Europe during COVID-19 were buffered by
 ammonia
 [https://doi.org/10.5061/dryad.12jm63z1q](https://doi.org/10.5061/dryad.12jm63z1q) ## Description of the data and file structure 1\. Title of Dataset: Unchanged PM2.5 levels over Europe during COVID-19 were buffered by ammonia 2\. Author Information Corresponding Investigator Name: Dr Nikolaos Evangeliou Institution: NILU - Norwegian Institute for Air Research, 2007 Kjeller, Norway Email: [ne@nilu.no](mailto:ne@nilu.no) Co-investigator 1 Name: Dr Ondřej Tichý Institution: The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic Co-investigator 2 Name: Ms. Marit Svendby Otervik Institution: NILU - Norwegian Institute for Air Research, 2007 Kjeller, Norway Co-investigator 3 Name: Dr Sabine Eckhardt Institution: NILU - Norwegian Institute for Air Research, 2007 Kjeller, Norway Co-investigator 4 Name: Dr. Yves Balkanski Institution: Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA-CNRS-UVSQ, 91191, Gif-sur-Yvette, France Co-investigator 5 Name: Dr. Didier Hauglustaine Institution: Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA-CNRS-UVSQ, 91191, Gif-sur-Yvette, France 3\. Date of data collection: 2018-2022 4\. Geographic location of data collection: Europe 5\. Funding sources that supported the collection of the data: COMBAT (Quantification of Global Ammonia Sources constrained by a Bayesian Inversion Technique) project funded by ROMFORSK – Program for romforskning of the Research Council of Norway (Project ID: 275407, website: [https://prosjektbanken.forskningsradet.no/project/FORISS/275407?Kilde=FORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=0&ProgAkt.3=ROMFORSK-Program+for+romforskning](https://prosjektbanken.forskningsradet.no/project/FORISS/275407?Kilde=FORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=0&ProgAkt.3=ROMFORSK-Program+for+romforskning)) 6\. Recommended citation for this dataset: Tichý, O. et al. (2023), Data from: NH3 levels over Europe during COVID-19 were modulated by changes in atmospheric chemistry, Dryad, Dataset DATA & FILE OVERVIEW 1\. Description of dataset These data were generated to investigate the impact of the European lockdowns during March-April 2020 on the emissions and atmospheric levels of ammonia. Satellite ammonia was adopted from the Cross-Track Infrared Sounder (CrIS). Source-receptor matrices (SRMs) were calculated for 0.5°×0.5° size grid-cells over Europe (10°W–50°E, 25°N–75°N) using the Lagrangian particle dispersion model FLEXPART version 10.4 adapted to model ammonia using hourly ERA5 assimilated meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF). Satellite ammonia and FLEXPART SRMs were then used in the least squares with adaptive prior covariance (LS-APC) algorithm to calculate posterior emissions of ammonia for the first half of 2020. Clinical and demographic were not used. 2\. File List: File 1 Name: AVE_FOOTPRINT_L1_chem.nc, AVE_FOOTPRINT_L2_chem.nc, AVE_FOOTPRINT_L3_chem.nc, AVE_FOOTPRINT_L4_chem.nc, AVE_FOOTPRINT_L5_chem.nc, AVE_FOOTPRINT_L6_chem.nc File 1 Description: FLEXPART v10.4 sensitivities for 6 model levels using chemistry loss after taking into account changes in emissions of NOx and SO2 in the calculations (see also associated paper) File 2 Name: AVE_FOOTPRINT_L1_nochem.nc, AVE_FOOTPRINT_L2_nochem.nc, AVE_FOOTPRINT_L3_nochem.nc, AVE_FOOTPRINT_L4_nochem.nc, AVE_FOOTPRINT_L5_nochem.nc, AVE_FOOTPRINT_L6_nochem.nc File 2 Description: FLEXPART v10.4 sensitivities for 6 model levels using chemistry loss after leaving NOx and SO2 emissions unaffected by lockdowns in the calculations (see also associated paper) File 3 Name: 2deg.tar.gz, 3deg.tar.gz, 4deg.tar.gz File 3 Description: Different surrounding estimates of posterior emissions covering 2°, 3° and 4° from each grid-cell File 4 Name: Correction_R4.tar.gz File 4 Description: Performance calculations for the prior and posterior emissions against the dependent observations (CrIS) File 5 Name: FWD_pri.tar.gz, FWD_pos.tar.gz File 5 Description: Forward simulations with FLEXPART v10.4 using prior and posterior emissions that were used for validation against independent (observations that were excluded from the inversion) observations from the EMEP network File 6 Name: 4deg_avgEENV.tar.gz File 6 Description: Inversions results (prior, posterior NH3 for the first half of each year in 2016-2020) validation of prior and posterior concentrations against observations from EMEP. METHODOLOGICAL INFORMATION SRMs were calculated for each 0.5°×0.5° grid-cell over Europe (10°W–50°E, 25°N–75°N) using the Lagrangian particle dispersion model FLEXPART version 10.4 adapted to model ammonia. The model releases computational particles that are tracked backward in time using hourly ERA5 assimilated meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) with 137 vertical layers and a horizontal resolution of 0.5°×0.5°. FLEXPART simulates turbulence, unresolved mesoscale motions and includes a deep convection scheme. SRMs were calculated for 7 days backward in time, at temporal intervals that matched satellite measurements and at spatial resolution of 0.25°×0.25°. This 7-day backward tracking is sufficiently long to include almost all ammonia sources that contribute to surface concentrations at the receptors given a typical atmospheric lifetime of about half a day. The proposed inversion method is based on a comparison of the CrIS satellite observations with the model profile retrievals to estimate the spatiotemporal NH3 emissions. The comparison of remote-sense observations such as CrIS with model (or in-situ) profiles is not straightforward as in the cases of ground-based observations. Here, we use the more rigorous approach of the “instrument operator” (see equation below), after interpolation of the model profile to the first six levels of the satellite product. The inverse problem is constructed for each spatial element of the computational domain. Inspired by construction of covariance matrix in Cao et al., we consider 2°, 3° and 4° surroundings. The generated prior and posterior concentrations after applying prior and posterior emissions to the SRMs are evaluated against the dependent observations of CrIS ammonia. This is a measure of the performance of the inversion. Prior and posterior emissions of ammonia were used as input into FLEXPART v10.4 to simulate ammonia forward in time. The resulting prior and posterior ammonia concentrations over Europe were validated against independent (observations that were excluded from the inversion) observations from the EMEP network (the EMEP measurements of ammonia can be downloaded from [https://ebas.nilu.no](https://ebas.nilu.no)). DATA-SPECIFIC INFORMATION FOR: AVE_FOOTPRINT_L1_chem.nc, AVE_FOOTPRINT_L2_chem.nc, AVE_FOOTPRINT_L3_chem.nc, AVE_FOOTPRINT_L4_chem.nc, AVE_FOOTPRINT_L5_chem.nc, AVE_FOOTPRINT_L6_chem.nc, AVE_FOOTPRINT_L1_nochem.nc, AVE_FOOTPRINT_L2_nochem.nc, AVE_FOOTPRINT_L3_nochem.nc, AVE_FOOTPRINT_L4_nochem.nc, AVE_FOOTPRINT_L5_nochem.nc, AVE_FOOTPRINT_L6_nochem.nc 1\. Number of variables: 4 2\. Number of cases/rows: 240x200 3\. Variable List: latitude: grid cell center longitude: grid cell center time: days since 1970-01-01 00:00 footprint: gridded SRM calculated with FLEXPARTv10.4 model 4\. Missing data codes: None 5\. Abbreviations used: N/A; not applicable 6\. Other relevant information: All files include the same 4 variables with the same naming. The name of each netCDF file denotes relevant differences of each file. For instance, L1 refers to SRM height 0-0.717 km, L2 to 0.717-1.46 km, L3 to 1.46-2.20 km, L4 to 2.20-2.93 km, L5 to 2.93-3.64 km, L5 to 3.64-4.33 km. The ending "_chem.nc" denotes that chemistry loss after taking into account changes in emissions of NOx and SO2 during the lockdowns have been considered in the SRM calculations. Accordingly, "_nochem.nc" denotes that levels of NOx and SO2 were kept as high as in previous years during the lockdowns. DATA-SPECIFIC INFORMATION FOR: 2deg.tar.gz, 3deg.tar.gz, 4deg.tar.gz 1\. Number of variables: 5 2\. Number of cases/rows: 240x200 3\. Variable List: hX: posterior emissions of ammonia prior_weeks: prior emissions of ammonia measurements_vsat: operator of satellite ammonia (see vsat in main manuscript) posterior_conc: operator of posterior concentrations of ammonia calculated from SRMs and posterior emissions (also mentioned as posterior vmod) prior_conc: operator of prior concentrations af ammonia calculated from SRMs and prior emissions (also mentioned as prior vmod) 4\. Missing data codes: None 5\. Abbreviations used: N/A; not applicable 6\. Other relevant information: Each compressed file contains 4 identical directories namely "INVCOVID_ec5", "INVCOVID_ec6", "INVCOVID_ne", and "INVCOVID_vd" for 4 different priors used (ECLIPSEv5+GFED+GEIA, ECLISEv6+GFED4, NE and VD, as described in Evangeliou et al. [2021], [https://doi.org/10.5194/acp-21-4431-2021](https://doi.org/10.5194/acp-21-4431-2021)). In each of them there are 5 matlab files named as hX_20??*int1_R*.mat representing posterior emissions of ammonia for 2016-2020 (first half of the year). In addition, there are 5 matlab files named as prior20??half.mat for the same period 2016-2020 representing the prior emissions of ammonia. The variables 'measurements_vsat', 'posterior_conc', 'prior_conc' are given in matlabl file scatter_2020*.mat, and variables 'measurements_vsat', 'posterior_vmod', 'prior_vmod' in vmod_2020*.mat, all used to record the performance of the inversion. DATA-SPECIFIC INFORMATION FOR: 4deg_avgEENV.tar.gz 1\. Number of variables: 5 2\. Number of cases/rows: 240x200 3\. Variable List: hX: posterior emissions of ammonia prior_weeks: prior emissions of ammonia measurements_vsat: operator of satellite ammonia (see vsat in main manuscript) posterior_conc: operator of posterior concentrations of ammonia calculated from SRMs and posterior emissions (also mentioned as posterior vmod) prior_conc: operator of prior concentrations af ammonia calculated from SRMs and prior emissions (also mentioned as prior vmod) 4\. Missing data codes: None 5\. Abbreviations used: N/A; not applicable 6\. Other relevant information: The calculations here were performed used a priori emissions of NH3 as the average of the following inventories, ECLIPSEv5+GFED+GEIA, ECLISEv6+GFED4, NE and VD, as described in Evangeliou et al. [2021], [https://doi.org/10.5194/acp-21-4431-2021](https://doi.org/10.5194/acp-21-4431-2021)) and they are named in the manuscript as avgEENV. In each of them there are 5 matlab files named as hX_20??_int1_R4_priorEm6_alg1.mat representing posterior emissions of ammonia for 2016-2020 (first half of the year). In addition, there are 5 matlab files named as prior6_20??half.mat for the same period 2016-2020 representing the prior emissions of ammonia. The variables 'measurements_vsat', 'posterior_conc', 'prior_conc' are given in matlab file stations_vmodVSobs_avgEENV.mat, and variables 'st_OBSdays', 'st_coord', 'st_ind_obs', 'st_list', 'st_obs_coord', 'st_post6_vmod_days', 'st_prior6_vmod_days', all used to record the performance of the inversion. DATA-SPECIFIC INFORMATION FOR: FWD_pri.tar.gz, FWD_pos.tar.gz 1\. Number of variables: 20 + comments field 2\. Number of cases/rows: 240x200 3\. Variable List: latitude: grid cell center longitude: grid cell center time: seconds since 2019-12-25 00:00 footprint: gridded SRM calculated with FLEXPARTv10.4 model height: height above ground RELCOM: release point name RELLNG1: release longitude lower left corner RELLNG2: release longitude upper right corner RELLAT1 :release latitude lower left corner RELLAT2: release latitude upper right corner RELZZ1: release height bottom RELZZ2: release height top RELKINDZ: release kind RELSTART: release start relative to simulation start RELEND: release end relative to simulation start RELPART: number of release particles RELXMASS: total release particle mass LAGE: age class ORO: surface altitude/outgrid surface altitude spec001_mr: surface concentration in ng m-3" 4\. Missing data codes: None 5\. Abbreviations used: N/A; not applicable 6\. Other relevant information: Each compressed file represent a tree of the set-up of forward simulation of ammonia using FLEXPARTv10.4 and prior or posterior emissions (WD_pri.tar.gz, FWD_pos.tar.gz). Under directory "OUT/" one can find the resulting concentrations of ammonia that were used to validate emissions against independent measurements from EMEP (obtained through [https://ebas.nilu.no](https://ebas.nilu.no)). The netCDF file named "grid_conc_20191225000000.nc" contains the aforementioned 20 variables described above. DATA-SPECIFIC INFORMATION FOR: Correction_R4.tar.gz 1\. Number of variables: 3 2\. Number of cases/rows: 240x200 3\. Variable List: measurements_vsat: operator of satellite ammonia (see vsat in main manuscript) posterior_conc: operator of posterior concentrations of ammonia calculated from SRMs and posterior emissions (also mentioned as posterior vmod) prior_conc: operator of prior concentrations af ammonia calculated from SRMs and prior emissions (also mentioned as prior vmod) 4\. Missing data codes: None 5\. Abbreviations used: N/A; not applicable 6\. Other relevant information: The compressed file consists of 4 directories namely prior1-4, which are results for 4 priors used (Prior1: ECLISEv6+GFED4, Prior2: ECLIPSEv5+GFED+GEIA, Prior3: NE and Prior4: VD, as described in Evangeliou et al. [2021], [https://doi.org/10.5194/acp-21-4431-2021](https://doi.org/10.5194/acp-21-4431-2021)). Each directory consists of a matlab file that includes variables 'measurements_vsat', 'posterior_conc', 'prior_conc'. Update March 2023: \- 4deg_avgEENV.tar.gz file was added containing the inversion results using the avgEENV dataset as a priori information. This prior creates a better fit of the posterior modelled concentrations to ground-based independent observations of NH3 over Europe in the first half of 2020.