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Nitrogen oxides (NO x= NO + NO 2) play a critical role in regulating tropospheric chemistry, yet NO x emission estimates are subject to large uncertainties, casting doubt on our ability to accurately model secondary pollutants such as ozone. Bottom-up emissions inventories are subject to a number of uncertainties related to estimates of emission activities, scaling factors, and fuel sources. Here, we provide an additional constraint on NO x emissions and trends using nitrate wet deposition (NWD) fluxes from the United States National Atmospheric Deposition Program (NADP) and the European Monitoring and Evaluation Programme (EMEP). We use these NWD measurements to evaluate anthropogenic and total NO x trends and magnitudes in the global Community Emissions Data System (CEDS) emissions inventory and the GEOS-Chem chemical transport model from 1980–2020. Over both the United States and Europe, observed NWD trends track well with anthropogenic NO x emissions from the CEDS inventory until 2010, after which NWD trends level out in contrast to continued decreases in CEDS. After 2010, NWD trends are able to reproduce total NO x emissions trends when the influences of both anthropogenic and background sources are considered. Observed NWD fluxes are also able to capture NO x emissions decreases over the 2020 COVID-19 lockdown period and are consistent with satellite and surface measurements of NO 2. These results suggest that NWD fluxes constrain total NO x emissions well, whether trends are driven by anthropogenic or background sources. We further compare modeled and observed NWD to provide an additional line of evidence for potential overestimates of anthropogenic NO x in emissions inventories. Over the United States, we find that NWD is overestimated in summer from 1980–2017 by 15 %–20 % on average (interquartile range: 11 %–31 %), with overestimates most prominent in the eastern US after 2000 (20 % on average), implying an overestimate of NO x emissions in the CEDS inventory (0.5×0.5 ° resolution). Over Europe, we find that modeled NWD is overestimated in all seasons from 1980–2017, with the strongest average overestimates occurring in summer and fall (175 % and 170 %, respectively). These overestimates may be reduced by cutting anthropogenic NO x emissions by 50 % in CEDS over Europe (i.e., cutting the 1980–2017 average annual emissions from 2.6 to 1.3 Tg N), but summertime and fall NO x may still need to be reduced further for observations and models to align. Overestimates may extend to other inventories such as the EMEP inventory, which estimates comparable but lower emissions than CEDS, with a 1990–2017 average of 2.1 Tg N relative to the CEDS 1990–2017 average of 2.4 Tg N. We find that NO x emission reductions over Europe improve model ozone at the surface, reducing the model summertime ozone overestimate from 14 % to 2 %. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) is among the air pollutants representing the most critical threat to human health in Europe. For designing strategies to mitigate this kind of air pollution, it is essential to identify and quantify the sources of its components. Here, we utilized the regional chemistry transport model CAMx (Comprehensive Air Quality Model with Extensions) to investigate the relationships between emissions from different categories and the concentrations of PM 2.5 and its secondary components over Central Europe during the period 2018–2019, both in terms of the contributions of emission categories calculated by the particle source apportionment technology (PSAT) and the impacts of the complete removal of emissions from individual categories (i.e., the zero-out method). During the winter seasons, emissions from other stationary combustion (including residential combustion) were the main contributor to the domain-wide average PM 2.5 concentration (3.2 µgm-3), and their removal also had the most considerable impact on it (3.4 µgm-3). During the summer seasons, the domain-wide average PM 2.5 concentration was contributed the most by biogenic emissions (0.57 µgm-3), while removing emissions from agriculture–livestock had the most substantial impact on it (0.46 µgm-3). The most notable differences between the contributions and impacts for PM 2.5 were associated with emissions from agriculture–livestock, mainly due to the differences in nitrate concentrations, which reached up to 4.5 and 1.25 µgm-3 in the winter and summer seasons, respectively. We also performed a sensitivity test of the mentioned impacts on PM 2.5 on two different modules for secondary organic aerosol formation (SOAP and VBS), which showed the most considerable differences for emissions from other stationary combustion (in winter) and road transport (in summer). [ABSTRACT FROM AUTHOR]

Recent years have seen an increase in the use of wood for energy production of over 30 %, and this trend is expected to continue due to the current energy crisis and geopolitical instability. At present, residential wood burning (RWB) is one of the most important sources of organic aerosols (OAs) and black carbon (BC), posing a significant risk to air quality and health. Simultaneously, as a substantial aerosol source, RWB also holds relevance in the context of aerosol radiative effects and climate. While BC is recognized for its large light absorption cross-section, the role of OAs in light absorption is still under evaluation due to their heterogeneous composition and source-dependent optical properties. Existing studies that characterize wood-burning aerosol emissions in Europe primarily concentrate on urban and background sites and focus on BC properties. Despite the significant RWB emissions in rural areas, these locations have received comparatively less attention. The present scenario underscores the imperative for an improved understanding of RWB pollution, aerosol optical properties, and their subsequent connection to climate impacts, particularly in rural areas. We have characterized atmospheric aerosol particles from a central European rural site during wintertime in the village of Retje in Loški Potok, Slovenia, from 1 December 2017 to 7 March 2018. The village experienced extremely high aerosol concentrations produced by RWB and near-ground temperature inversion. The isolated location of the site and the substantial local emissions made it an ideal laboratory-like place for characterizing RWB aerosols with low influence from non-RWB sources under ambient conditions. The mean mass concentrations of OA and BC were 35 µgm-3 (max⁡=270 µgm-3) and 3.1 µgm-3 (max⁡=24 µgm-3), respectively. The mean total particle number concentration (10–600 nm) was 9.9×103 particles cm -3 (max⁡=59×103 particles cm -3). The mean total light absorption coefficients at 370 and 880 nm measured by an AE33 Aethalometer were 120 and 22 Mm -1 and had maximum values of 1100 and 180 Mm -1 , respectively. The aerosol concentrations and absorption coefficients measured during the campaign in Loški Potok were significantly larger than reported values for several urban areas in the region with larger populations and a larger extent of aerosol sources. Here, considerable contributions from brown carbon (BrC) to the total light absorption were identified, reaching up to 60 % and 48 % in the near-UV (370 nm) and blue (470 nm) wavelengths. These contributions are up to 3 times higher than values reported for other sites impacted by wood-burning emissions. The calculated mass absorption cross-section and the absorption Ångström exponent for RWB OA were MAC OA,370nm=2.4 m 2 g -1 , and AAE BrC,370-590nm=3.9 , respectively. Simple-forcing-efficiency (SFE) calculations were performed as a sensitivity analysis to evaluate the climate impact of the RWB aerosols produced at the study site by integrating the optical properties measured during the campaign. The SFE results show a considerable forcing capacity from the local RWB aerosols, with a high sensitivity to OA absorption properties and a more substantial impact over bright surfaces like snow, typical during the coldest season with higher OA emissions from RWB. Our study's results are highly significant regarding air pollution, optical properties, and climate impact. The findings suggest that there may be an underestimation of RWB emissions in rural Europe and that further investigation is necessary. [ABSTRACT FROM AUTHOR]

For over 6 months, the 2014–2015 effusive eruption at Holuhraun, Iceland, injected considerable amounts of sulfur dioxide (SO2) into the lower troposphere with a daily rate of up to one-third of the global emission rate, causing extensive air pollution across Europe. The large injection of SO2 , which oxidises to form sulfate aerosol (SO42-), provides a natural experiment offering an ideal opportunity to scrutinise state-of-the-art general circulation models' (GCMs) representation of aerosol–cloud interactions (ACIs). Here we present Part 1 of a two-part model inter-comparison using the Holuhraun eruption as a framework to analyse ACIs. We use SO2 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument and ground-based measurements of SO2 and SO42- mass concentrations across Europe, in conjunction with a trajectory analysis using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, to assess the spatial and chemical evolution of the volcanic plume as simulated by five GCMs and a chemical transport model (CTM). IASI retrievals of plume altitude and SO2 column load reveal that the volcanic perturbation is largely contained within the lower troposphere. Compared to the satellite observations, the models capture the spatial evolution and vertical variability of the plume reasonably well, although the models often overestimate the plume altitude. HYSPLIT trajectories are used to attribute to Holuhraun emissions 111 instances of elevated sulfurous surface mass concentrations recorded at European Monitoring and Evaluation Programme (EMEP) stations during September and October 2014. Comparisons with the simulated concentrations show that the modelled ratio of SO2 to SO42- during these pollution episodes is often underestimated and overestimated for the young and mature plume, respectively. Models with finer vertical resolutions near the surface are found to better capture these elevated sulfurous ground-level concentrations. Using an exponential function to describe the decay of observed surface mass concentration ratios of SO2 to SO42- with plume age, the in-plume oxidation rate constant is estimated as 0.032 ± 0.002 h-1 (1.30 ± 0.08 d e -folding time), with a near-vent ratio of 25 ± 5 (µgm-3 of SO2 / µgm-3 of SO42-). The majority of the corresponding derived modelled oxidation rate constants are lower than the observed estimate. This suggests that the representation of the oxidation pathway/s in the simulated plumes is too slow. Overall, despite their coarse spatial resolutions, the six models show reasonable skill in capturing the spatial and chemical evolution of the Holuhraun plume. This capable representation of the underlying aerosol perturbation is essential to enable the investigation of the eruption's impact on ACIs in the second part of this study. [ABSTRACT FROM AUTHOR]

In May–June 2019, smoke plumes from wildfires in Alberta, Canada, were advected all the way to Europe. To analyze the evolution of the plumes and to estimate the amount of smoke aerosols transported to Europe, retrievals from the spaceborne lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the masses of smoke aerosols were retrieved from the CALIOP observations. The accuracy of the CALIOP mass retrievals was compared with the accuracy of ground-based lidars/ceilometer near the source in North America and after the long-range transport in Europe. Overall, CALIOP and the ground-based lidars/ceilometer produced comparable results. Over North America the CALIOP layer mean mass was 30 % smaller than the ground-based estimates, whereas over southern Europe that difference varied between 12 % and 43 %. Finally, the CALIOP mass retrievals were compared with simulated aerosol concentrations from two reanalysis models: MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) and CAMS (Copernicus Atmospheric Monitoring System). The simulated total column aerosol optical depths (AODs) and the total column mass concentration of smoke agreed quite well with CALIOP observations, but the comparison of the layer mass concentration of smoke showed significant discrepancies. The amount of smoke aerosols in the model simulations was consistently smaller than in the CALIOP retrievals. These results highlight the limitations of such models and more specifically their limitation to reproduce properly the smoke vertical distribution. They indicate that CALIOP is a useful tool monitoring smoke plumes over secluded areas, whereas reanalysis models have difficulties in representing the aerosol mass in these plumes. This study shows the advantages of spaceborne aerosol lidars, e.g., being of paramount importance to monitor smoke plumes, and reveals the urgent need of future lidar missions in space. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at the regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN–MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tgyr-1), which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+ 13 %) and anthropogenic VOCs (- 17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50 ∘ N but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism, leading to differences of up to 10 % in the total emissions. However, the top-down emissions are very sensitive to the bias correction of the observed columns, as the biogenic emissions are 3 times lower when the correction is not applied. Furthermore, the use of different a priori biogenic emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. The sensitivity run using CAMS-GLOB-BIOv3.1 as a priori emissions in the inversion results in 30 % lower emissions with respect to the optimization using MEGAN–MOHYCAN. In regions with large temperature and cloud cover variations, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]

Rural-to-urban transformation (RUT) is the process of turning a rural or natural land surface into an urban one, which brings about important modifications in the surface, causing well-known effects like the urban heat island (UHI), reduced wind speeds, and increased boundary layer heights. Moreover, with concentrated human activities, RUT introduces new emission sources which greatly perturb local and regional air pollution. Particulate matter (PM) is one of the key pollutants responsible for the deterioration of urban air quality and is still a major issue in European cities, with frequent exceedances of limit values. Here we introduce a regional chemistry–climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, (i) urban emissions and (ii) urban canopy meteorological forcing (UCMF; i.e. the impact of modified meteorological conditions on air quality), we also analyse two less studied contributors to RUT's impact on air quality: (iii) the impact of modified dry-deposition velocities (DVs) due to urbanized land use and (iv) the impact of modified biogenic emissions due to urbanization-induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations, whereby each contributor is added one by one to the reference state, while focus is given on PM 2.5 (particulate matter with diameter less then 2.5 µm). Its primary and secondary components, namely primary elemental carbon (PEC), sulfates (PSO 4), nitrates (PNO 3), ammonium (PNH 4), and secondary organic aerosol (SOA), are analysed too. The validation using surface measurements showed a systematic negative bias for the total PM 2.5 , which is probably caused by underestimated organic aerosol and partly by the negative bias in sulfates and elemental carbon. For ammonium and nitrates, the underestimation is limited to the warm season, while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured. We evaluated the RUT impact on PM 2.5 over a sample of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µgm-3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µgm-3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µgm-3 (in both seasons), which was mainly controlled by enhanced vertical eddy diffusion, while increases were modelled over rural areas. The transformation of rural land use into an urban one caused an increase in dry-deposition velocities by around 30 %–50 %, which alone resulted in a decrease in PM 2.5 by 0.1–0.25 µgm-3 in both seasons. Finally, the impact of biogenic emission modifications due to modified land use and meteorological conditions caused a decrease in summer PM 2.5 of about 0.1 µgm-3 , while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µgm-3 for PEC, 0.05 and 0.02 µgm-3 for PSO 4 , 0.1 and 0.08 µgm-3 for PNO 3 , 0.04 and 0.03 µgm-3 for PNH 4 , and 0 and 0.05 µgm-3 for SOA. The main contributor of each of these components was the impact of emissions, which was usually larger than the total impact due to the fact that UCMF was counteracted with a decrease. For each aerosol component, the impact of modified DV was a clear decrease in concentration, and finally, the modifications of biogenic emissions impacted SOA predominantly, causing a summer decrease, while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased). In summary, we showed that when analysing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one also has to consider the effect of modified land use and its impact on dry deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that they act on PM 2.5 predominantly through SOA modifications, which only turned out to be important during summer. [ABSTRACT FROM AUTHOR]

We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km × 3 km and focus on nitrogen dioxide (NO2). A regional emission inventory issued by the German Environmental Agency, with a spatial resolution of 1 km × 1 km, is used as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data ("temporal profiles") driving the model. The model setup with improved vertical mixing is shown to produce the best results. Simulated NO2 surface concentrations are compared to measurements from a total of 275 in situ measurement stations in Germany, where the model was able to reproduce average noontime NO2 concentrations with a bias of ca. - 3 % and R=0.74. The best agreement is achieved when correcting for the presumed NOy cross sensitivity of the molybdenum-based in situ measurements by computing an NOy correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO3) mixing ratios. A comparison between modelled NO2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of + 5.5 % and R=0.87 for monthly means. Lastly, simulated NO2 concentration profiles are compared to noontime NO2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of - 25.3 % to + 12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to + 50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO2 to the mixing processes in the boundary layer and the diurnal distribution of emissions. [ABSTRACT FROM AUTHOR]